inventory management

Prediction Machines: The Simple Economics of Artificial Intelligence
by Ajay Agrawal , Joshua Gans and Avi Goldfarb
Published 16 Apr 2018

Just as the first applications of computing applied to familiar arithmetic problems like census tabulations and ballistics tables, many of the first applications of inexpensive prediction from machine learning applied to classic prediction problems. In addition to fraud detection, these included creditworthiness, health insurance, and inventory management. Creditworthiness involved predicting the likelihood that someone would pay back a loan. Health insurance involved predicting how much an individual would spend on medical care. Inventory management involved predicting how many items would be in a warehouse on a given day. More recently, entirely new classes of prediction problems emerged. Many were nearly impossible before the recent advances in machine intelligence technology, including object identification, language translation, and drug discovery.

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It is the process of taking an order and executing it by making it ready for delivery to its intended customer. In electronic commerce, fulfillment includes a number of steps such as locating items in a large warehouse-type facility, picking the items off shelves, scanning them for inventory management, placing them in a tote, packing them in a box, labeling the box, and shipping it for delivery. Many early applications of machine learning to fulfillment related to inventory management: predicting which products would sell out, which did not need reordering because of low demand, and so on. These well-established prediction tasks had been a key part of offline retail and warehouse management for decades.

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Whereas we once solved photography with chemistry, when arithmetic became cheap enough, we transitioned to an arithmetic-based solution: digital cameras. A digital image is just a string of zeros and ones that can be reassembled into a viewable image using arithmetic. The same goes for prediction. Prediction is being used for traditional tasks, like inventory management and demand forecasting. More significantly, because it is becoming cheaper it is being used for problems that were not traditionally prediction problems. Kathryn Howe, of Integrate.ai, calls the ability to see a problem and reframe it as a prediction problem “AI Insight,” and, today, engineers all over the world are acquiring it.

The Phoenix Project: A Novel About IT, DevOps, and Helping Your Business Win
by Gene Kim , Kevin Behr and George Spafford
Published 14 Jul 2013

He said he wanted a ‘sense of urgency’ and ‘hands on keyboards, not people sitting on the bench.’ Obviously, we didn’t do a good enough job coordinating everyone’s efforts, and…” Wes doesn’t finish his sentence. Patty picks up where he left off, “We don’t know for sure, but at the very least, the inventory management systems are now completely down, too. No one can get inventory levels in the plants or warehouses, and they don’t know which raw materials we need to replenish. All the finance guys are about to jump from window ledges, because they may not be able to close the books for the quarter on time.

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He looks at his watch for a moment. “No, just keep those damned vendors from crashing our phone systems again, you hear?” Patty looks invigorated as she flips through all her notes by the elevator banks. She says, “Ron mentioned how critical the phones and the MRP systems are, but I’m sure there’s more, like the inventory management systems. I’ll work on creating the complete list of applications and infrastructure that support Ron. If any of them are fragile, we need to get them added to our replacement list. This is a great opportunity to be proactive.” “You read my mind,” I say, smiling. “That preventive work supports the most important objectives of the company.

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In describing her responsibilities, she summarizes, “Ultimately, the way I measure our understanding of customer needs and wants is whether customers would recommend us to their friends. Any way you cut it, our metrics aren’t very good.” When I ask why, she sighs. “Most of the time, we’re flying blind. Ideally, our sales data would tell us what customers want. You’d think that with all the data in our order entry and inventory management systems, we could do this. But we can’t, because the data are almost always wrong.” Patty glances my way meaningfully as Maggie continues, “Our data quality is so bad that we can’t rely on it to do any sort of forecasting. The best data that we have right now come from interviewing our store managers every two months and the customer focus groups we do twice a year.

Digital Accounting: The Effects of the Internet and Erp on Accounting
by Ashutosh Deshmukh
Published 13 Dec 2005

SRM tool functionalities, such as supplier self-service, auctions, contract management and purchasing intelligence, are also available in planned sourcing. If the final product or parts of the product are to be outsourced, then such subcontracting can be automated through materials management. The rest of the functionalities are inventory management and VMI, which are seen later. Inventory management involves maintaining the required inventory quantity and value. The quantity on hand, quantity in the receiving department, quantity on order and quantity at different locations can be seen at any point in time. As materials are requisitioned to production, the inventory levels — that is, inventory quantity and inventory value — are updated.

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Organizations understood that ecommerce is a pervasive concept and will affect the demand chain (demand forecasting, delivery of products to customers and cash collections, customer profitability analysis, Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 8 Deshmukh best ways of delivery, etc.), supply chain (production planning, purchasing of raw materials and services and consequent payments, inventory management, transportation and distribution, etc.), internal business processes, technology applications and business models, among other things. As B2B e-commerce took off, there was a proliferation of Web portals, exchanges, online auctions and community e-marketplaces that provided a centralized place on the Internet for buying and selling of products.

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Structure of accounting/business software Business function modules •Treasury functions •Production planning and control •Warehouse management •Project management •Human resources management •Supply chain management •Supplier relationship Management •Customer relationship Management Accounting modules •Sales order entry •Accounts receivable •Purchasing •Inventory Management •Accounts payable •Job costing •Fixed assets •Payroll •General ledger •Enterprise reporting Customization tools • Modifying functionalities software and database • Data import and export • Customizing screens, views, and reports RDBMS or data warehouse E-commerce modules Web support for: •Accounting oEnterprise reporting oOnline expense management oWeb enabled closing •Treasury functions Web support for: •Electronic data interchange •Customer relationship management •Supplier relationship management •Supply chain management •Electronic marketplaces and exchanges enable various inter- and intra-organizational Web-based processes.

Democratizing innovation
by Eric von Hippel
Published 1 Apr 2005

One consequence of the information asymmetry between users and manufacturers is that users tend to develop innovations that are functionally novel, requiring a great deal of user-need information and use-context information for their development. In contrast, manufacturers tend to develop innovations that are improvements on well-known needs and that require a rich understanding of solution information for their development. For example, firms that use inventory-management systems, such as retailers, tend to be the developers of new approaches to inventory management. In contrast, manufacturers of inventory-management systems and equipment tend to develop improvements to the equipment used to implement these user-devised approaches (Ogawa 1998). If we extend the information-asymmetry argument one step further, we see that information stickiness implies that information on hand will also differ among individual users and manufacturers.

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He too found the sticky-information effect—this time visible in the division of labor within product-development projects. He studied patterns in the development of a sample of 24 inventory-management innovations. All were jointly developed by a Japanese equipment manufacturer, NEC, and by a user firm, Seven-Eleven Japan (SEJ). SEJ, the leading convenience-store 72 Chapter 5 company in Japan, is known for its inventory management. Using innovative methods and equipment, it is able to turn over its inventory as many as 30 times a year, versus 12 times a year for competitors (Kotabe 1995). An example of such an innovation jointly developed by SEJ and NEC is just-intime reordering, for which SEJ created the procedures and NEC the handheld equipment to aid store clerks in carrying out their newly designed tasks.

The 80/20 Principle: The Secret of Achieving More With Less
by Richard Koch
Published 15 Dec 1999

The areas divided by size and weight…can now also be divided by part number into areas of high or low activity. In general, fast-moving items should be located as close to the shoulder-hip zone as possible, to minimize operator movement and reduce fatigue.4 Inventory management in the future Despite its historical overtones of the brown coat and the dusty store, inventory management is a fast-moving and exciting area. “Virtual inventory,” with on-line order processing, is becoming widespread, lowering costs but also improving service to distributors and customers. Innovators such as Baxter International’s hospital supply business are having great success with “customer-intimate” inventory systems.

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The current chapter provides a summary of the other four applications of the 80/20 Principle in my hit parade. * * * 1 Strategy 2 Quality 3 Cost reduction and service improvement 4 Marketing 5 Selling 6 Information technology 7 Decision making and analysis 8 Inventory management 9 Project management 10 Negotiation * * * Figure 34 The Top 10 business applications of the 80/20 Principle DECISION MAKING AND ANALYSIS Business requires decisions: frequent, fast, and often without much idea whether they are right or wrong. Since 1950, business has increasingly been blessed, or if you prefer plagued, by management scientists and analytical managers incubated in business schools, accounting firms and consultancies, who can bring analysis (usually linked to extensive and expensive data gathering) to bear on any issue.

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When a business keeps performing below its budgets, you may be sure you have a dog. When a business consistently outperforms expectations, there is at least a good chance that it can be multiplied by ten or a hundred times. In these circumstances, most people settle for modest growth. Those who seize the day become seriously rich. INVENTORY MANAGEMENT We saw in Chapter 5 that simplicity requires few products. Managing stock is another key discipline flowing from the 80/20 Principle. Good stock keeping, following the 80/20 Principle, is vital to profits and cash; it is also an excellent check on whether a business is pursuing simplicity or complexity.

How We Got to Now: Six Innovations That Made the Modern World
by Steven Johnson
Published 28 Sep 2014

Big stores did much better than small stores. There have always been inherent advantages to maintaining a large inventory of items in a store: the customer has more options to choose from, and items can be purchased in bulk from wholesalers for less money. But in the days before bar codes and other forms of computerized inventory-management tools, the benefits of housing a vast inventory were largely offset by the costs of keeping track of everything. If you kept a thousand items in stock instead of a hundred, you needed more people and time to figure out which sought-after items needed restocking and which were just sitting on the shelves taking up space.

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If you kept a thousand items in stock instead of a hundred, you needed more people and time to figure out which sought-after items needed restocking and which were just sitting on the shelves taking up space. But bar codes and scanners greatly reduced the costs of maintaining a large inventory. The decades after the introduction of the bar-code scanner in the United States witnessed an explosion in the size of retail stores; with automated inventory management, chains were free to balloon into the epic big-box stores that now dominate retail shopping. Without bar-code scanning, the modern shopping landscape of Target and Best Buy and supermarkets the size of airport terminals would have had a much harder time coming into being. If there was a death ray in the history of the laser, it was the metaphoric one directed at the mom-and-pop, indie stores demolished by the big-box revolution

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If there was a death ray in the history of the laser, it was the metaphoric one directed at the mom-and-pop, indie stores demolished by the big-box revolution. — WHILE THE EARLY SCI-FI FANS of War of the Worlds and Flash Gordon would be disappointed to see the mighty laser scanning packets of chewing gum—its brilliantly concentrated light harnessed for inventory management—their spirits would likely improve contemplating the National Ignition Facility, at the Lawrence Livermore Labs in Northern California, where scientists have built the world’s largest and highest-energy laser system. Artificial light began as simple illumination, helping us read and entertain ourselves after dark; before long it had been transformed into advertising and art and information.

Alternatives to Capitalism
by Robin Hahnel and Erik Olin Wright

Whenever consumer councils and federations (which will function like clearing houses for adjustments) discover that changes do not cancel out, the national consumer federation will have to discuss adjustments with industry federations of worker councils. Computerized inventory management systems and “real time” supply chains are already fixtures in the global economy, which makes adjustments much smoother than they would have been only a few decades ago. (p. 85) The actual process by which these adjustments will occur is not very clear to me, but even with the best inventory management systems one can imagine, there will still be excess inventory of some goods in the system and shortfalls in others. The most obvious way that excess inventory will be dealt with is by allowing people to acquire these things less expensively.

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Nobody in a participatory economy needs to acquire detailed information about the production capabilities of production units, and nobody requires the services of supercomputers. Where relatively new modern technology would be helpful in running a participatory economy is in adjusting for changes during the year from what was planned and approved. Computerized inventory management systems and “real time” supply chains—which are now fixtures in the global economy—make adjustments during the year much smoother than they would have been a few decades ago. 7Readers interested in these technical issues should see Michael Albert and Robin Hahnel, Chapter 5 in The Political Economy of Participatory Economics (New Jersey: Princeton University Press, 1991); “Socialism as It Was Always Meant to Be,” Review of Radical Political Economics 24, no. 3–4 (Fall and Winter 1992): 46–66; “Participatory Planning,” Science and Society 56, no. 1 (Spring 1992): 39–59; and Hahnel, “Wanted: A Pollution Damage Revealing Mechanism,” forthcoming in the Review of Radical Political Economics.

Getting Better: Why Global Development Is Succeeding--And How We Can Improve the World Even More
by Charles Kenny
Published 31 Jan 2011

The same skills are needed to fix a television in New York or Nairobi; considerably different skills are required to be a good inventory manager. Furthermore, improvements in process technologies have to take account of the existing institutional context. Toyota’s Production System approach is built around innovation as a constant but incremental process based on small improvements to the existing system, for example. This suggests a long-term and context-specific path of improvement in process technologies that would have the sticky characteristics we are looking for. Institutions such as inventory management techniques, regulatory structures, or regime type might be central to the growth story.

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Technology would spread without regard to distance and borders, ending up about the same everywhere. The medieval would not cohabit with the modern. In turn, this would create a powerful force for income convergence. Again, we’ve seen that hope was optimistic. The process technologies—institutions like laws and inventory management systems—that appear central to raising incomes per capita flow less like water and more like bricks. But ideas and inventions—the importance of ABCs and vaccines for DPT—really might flow more easily across borders and over distances. Or at least they might flow with somewhat less regard to local idiosyncrasies and customs.

Always Day One: How the Tech Titans Plan to Stay on Top Forever
by Alex Kantrowitz
Published 6 Apr 2020

In today’s knowledge economy, ideas matter, but we still mostly spend our time on execution work. We develop a new product or service, and then spend our time supporting it instead of coming up with something else. If you sell dresses, for instance, supporting each design requires loads of execution work: pricing, sourcing, inventory management, sales, marketing, shipping, and returns. Additional support work props up these processes, including basic tasks in human resources, contracts, and accounting. The burden of execution work has made it nearly impossible for companies with one core business to develop and support another (Clayton Christensen calls this the “innovator’s dilemma”).

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See also Google Alter Girl (Syverson), 201 Amazon, 21–53 abuses of power by, 196 and Amazon Web Services (AWS), 45, 169, 171, 175 and artificial intelligence/machine learning, 42, 43, 109, 145–46, 219–20, 221 automation program at (Hands off the Wheel), 37–40, 41–44 and community support, 217 daily surveys at, 49–50 Day One culture of, 5–7 dominance of, 3 and Echo, 109, 111, 145–46, 147 employees of, 33–34, 41–46 employee training offered by, 35 Engineer’s Mindset at, 16 Go grocery store of, 21–22, 25, 53 headquarters of, 21, 53, 217 invention culture at, 16, 22–26, 45, 51 invention system at, 26–30, 36, 101 inventory management at, 37–40, 42–43 leadership principles at, 23–25, 47–48, 50 New York Times article on, 48–51 recruitment AI issues of, 219–20, 221 reinvention embraced by, 8 robot employees of, 30–35 tax breaks sought by, 217–18 technical creativity cultivated at, 51–52 work culture at, 48–51 written proposals at, 26–29 See also Bezos, Jeff Apple, 129–61 and AirPods, 133 and Apple Car, 148–51, 161 and Apple Watch, 133 collaboration absent from, 17, 131, 137–38, 142–43, 146–47, 150–51, 159 design imperative at, 134–36, 144, 149–50 dominance of, 3 and Engineer’s Mindset, 17, 131, 143, 151, 161 environment of, 136–37 hierarchies and top-down organization at, 131, 136, 143, 150, 151, 161 and HomePod, 129–31, 146–48, 151, 161 invention at, 131, 136–37, 160–61 and iPhone, 108, 133, 140–42, 149, 155–59, 160–61 and IS&T issues, 152–55 leadership of, 134 and Macs, 133 and privacy face-off with FBI, 155–59 products developed by, 7–8 refinement culture of, 132–33, 142–43 and revenue declines, 140–41 secrecy and silos enforced at, 137–40, 142–44, 146–47, 149, 151 and Siri, 142–46, 161 and user feedback, 144 values of, 159 visionary culture at, 17 See also Cook, Tim aQuantive, 163–65, 187, 196 artificial intelligence and machine learning advances in, 109 at Amazon, 42, 43, 109, 145–46, 219–20, 221 at Apple, 145, 150–51 automation technology’s integration of, 13, 14 bias potential in, 219–21 Bostrom on, 203–5 and dystopian scenarios, 195, 197 at Facebook, 75–81, 88 and face-recognition technology, 75–76 at Google, 109, 111–12, 114, 119–23 impact on employment, 36, 201–2, 204–5 and inventive cultures, 9–10 at Microsoft, 13, 164, 166, 170, 175–80 and Pentagon’s Maven project, 119–23 in predictive stocking, 38–40 recruitment of professors to private sector, 197 Athey, Susan, 166–71 automation and erosion of meaning, 198–202 impact on employment, 35–36, 216, 223–24 in inventory management, 37–40, 41–44 and predictability of humans, 37–38, 44 widespread application of, 11–14 Automation Anywhere, 13 Bach, Robbie, 164 Baldwin, Micah, 29, 49, 52 Ballmer, Steve at annual meetings, 181–82 leadership of Microsoft, 7, 18, 164–65, 167, 169–70, 171 Nadella’s succession of, 7, 18, 165, 171 Baquet, Dean, 49 Bauer, Ken, 139–40 Bezos, Jeff and Amazon Echo, 109 on careers in tech industry, 35 on Day Two, 5–6 drive of, 46–47 and Engineer’s Mindset, 15, 16, 18 fourteen leadership principles of, 23–25, 47 and invention culture of Amazon, 16, 22–23, 25, 53, 101 leadership style of, 3 and New York Times article, 49 and PowerPoint ban, 26 technical creativity cultivated by, 52 and Washington Post, 61–62 and written proposals, 26–29 Zuckerberg’s request to shadow, 61–62 See also Amazon “bias for action” principle, 24 bias in technology, potential for, 219–20 Birch, Rosa, 86–88 Black Mirror series, 191–92, 193–94 Bloodworth, James, 33 Bostrom, Nick, 203 Bosworth, Andrew, 84–85 Breisacher, Tyler, 119–20, 122 Brin, Sergey, 98, 106, 107, 110, 110n, 113 Brooker, Charlie, 192 Brownlee, Marques, 129–31, 147, 158 Cambridge Analytica, 83, 84, 158 Cameron, David, 192 Candela, Joaquin, 76–80 Carney, Jay, 49 Case, Anne, 201 Chan Zuckerberg Initiative, 218 Chew, Chee, 103–4, 105 China, 74, 135, 141, 142, 157, 192 Christensen, Clayton, 9 Claire, Craig Le, 14 cloud computing, 10, 166, 167–71, 175 collaboration Apple’s lack of, 17, 131, 137–38, 142–43, 146–47, 150–51, 159 communication tools enabling, 96–99, 115–16, 123, 125, 128 and Dweck’s “growth mindset” model, 185 and Engineer’s Mindset, 16–17, 17 at Google, 95, 96–99, 101, 105, 112, 114–16, 118–19, 128 at Microsoft, 166, 183–89, 190 at Square, 212 technology for, 10, 212, 225 transparency in support of, 96, 115–16 community, sense of, 200–201 compensation models, algorithmic, 81–82 conformity, teaching, 214–15 Cong, Jose, 98, 99 Conger, Kate, 94 Cook, Tim and Apple Car, 148–49 and Engineer’s Mindset, 17, 131 and hierarchies at Apple, 131, 136 and iPhone sales, 140–41 leadership style of, 134, 136–37 and privacy face-off with FBI, 156–57 and revenue declines, 140–41 and Siri, 143 and visionary culture of Apple, 17 See also Apple copying other products, 70–74 Cornell’s School of Industrial and Labor Relations, 207–8, 210 Cowie, Jefferson, 201–2 Cox, Chris, 71 creativity, value of, 215 Cuban, Mark, 7, 58 Cue, Eddy, 134 “customer obsession” principle, 25 Damore, James, 93–95, 127 DataRobot, 13 Day One culture, 5–7 Dean, Jeff, 109, 111–12, 120 deaths of despair, 201 Deaton, Angus, 201, 202 democratic invention.

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See also Google Alter Girl (Syverson), 201 Amazon, 21–53 abuses of power by, 196 and Amazon Web Services (AWS), 45, 169, 171, 175 and artificial intelligence/machine learning, 42, 43, 109, 145–46, 219–20, 221 automation program at (Hands off the Wheel), 37–40, 41–44 and community support, 217 daily surveys at, 49–50 Day One culture of, 5–7 dominance of, 3 and Echo, 109, 111, 145–46, 147 employees of, 33–34, 41–46 employee training offered by, 35 Engineer’s Mindset at, 16 Go grocery store of, 21–22, 25, 53 headquarters of, 21, 53, 217 invention culture at, 16, 22–26, 45, 51 invention system at, 26–30, 36, 101 inventory management at, 37–40, 42–43 leadership principles at, 23–25, 47–48, 50 New York Times article on, 48–51 recruitment AI issues of, 219–20, 221 reinvention embraced by, 8 robot employees of, 30–35 tax breaks sought by, 217–18 technical creativity cultivated at, 51–52 work culture at, 48–51 written proposals at, 26–29 See also Bezos, Jeff Apple, 129–61 and AirPods, 133 and Apple Car, 148–51, 161 and Apple Watch, 133 collaboration absent from, 17, 131, 137–38, 142–43, 146–47, 150–51, 159 design imperative at, 134–36, 144, 149–50 dominance of, 3 and Engineer’s Mindset, 17, 131, 143, 151, 161 environment of, 136–37 hierarchies and top-down organization at, 131, 136, 143, 150, 151, 161 and HomePod, 129–31, 146–48, 151, 161 invention at, 131, 136–37, 160–61 and iPhone, 108, 133, 140–42, 149, 155–59, 160–61 and IS&T issues, 152–55 leadership of, 134 and Macs, 133 and privacy face-off with FBI, 155–59 products developed by, 7–8 refinement culture of, 132–33, 142–43 and revenue declines, 140–41 secrecy and silos enforced at, 137–40, 142–44, 146–47, 149, 151 and Siri, 142–46, 161 and user feedback, 144 values of, 159 visionary culture at, 17 See also Cook, Tim aQuantive, 163–65, 187, 196 artificial intelligence and machine learning advances in, 109 at Amazon, 42, 43, 109, 145–46, 219–20, 221 at Apple, 145, 150–51 automation technology’s integration of, 13, 14 bias potential in, 219–21 Bostrom on, 203–5 and dystopian scenarios, 195, 197 at Facebook, 75–81, 88 and face-recognition technology, 75–76 at Google, 109, 111–12, 114, 119–23 impact on employment, 36, 201–2, 204–5 and inventive cultures, 9–10 at Microsoft, 13, 164, 166, 170, 175–80 and Pentagon’s Maven project, 119–23 in predictive stocking, 38–40 recruitment of professors to private sector, 197 Athey, Susan, 166–71 automation and erosion of meaning, 198–202 impact on employment, 35–36, 216, 223–24 in inventory management, 37–40, 41–44 and predictability of humans, 37–38, 44 widespread application of, 11–14 Automation Anywhere, 13 Bach, Robbie, 164 Baldwin, Micah, 29, 49, 52 Ballmer, Steve at annual meetings, 181–82 leadership of Microsoft, 7, 18, 164–65, 167, 169–70, 171 Nadella’s succession of, 7, 18, 165, 171 Baquet, Dean, 49 Bauer, Ken, 139–40 Bezos, Jeff and Amazon Echo, 109 on careers in tech industry, 35 on Day Two, 5–6 drive of, 46–47 and Engineer’s Mindset, 15, 16, 18 fourteen leadership principles of, 23–25, 47 and invention culture of Amazon, 16, 22–23, 25, 53, 101 leadership style of, 3 and New York Times article, 49 and PowerPoint ban, 26 technical creativity cultivated by, 52 and Washington Post, 61–62 and written proposals, 26–29 Zuckerberg’s request to shadow, 61–62 See also Amazon “bias for action” principle, 24 bias in technology, potential for, 219–20 Birch, Rosa, 86–88 Black Mirror series, 191–92, 193–94 Bloodworth, James, 33 Bostrom, Nick, 203 Bosworth, Andrew, 84–85 Breisacher, Tyler, 119–20, 122 Brin, Sergey, 98, 106, 107, 110, 110n, 113 Brooker, Charlie, 192 Brownlee, Marques, 129–31, 147, 158 Cambridge Analytica, 83, 84, 158 Cameron, David, 192 Candela, Joaquin, 76–80 Carney, Jay, 49 Case, Anne, 201 Chan Zuckerberg Initiative, 218 Chew, Chee, 103–4, 105 China, 74, 135, 141, 142, 157, 192 Christensen, Clayton, 9 Claire, Craig Le, 14 cloud computing, 10, 166, 167–71, 175 collaboration Apple’s lack of, 17, 131, 137–38, 142–43, 146–47, 150–51, 159 communication tools enabling, 96–99, 115–16, 123, 125, 128 and Dweck’s “growth mindset” model, 185 and Engineer’s Mindset, 16–17, 17 at Google, 95, 96–99, 101, 105, 112, 114–16, 118–19, 128 at Microsoft, 166, 183–89, 190 at Square, 212 technology for, 10, 212, 225 transparency in support of, 96, 115–16 community, sense of, 200–201 compensation models, algorithmic, 81–82 conformity, teaching, 214–15 Cong, Jose, 98, 99 Conger, Kate, 94 Cook, Tim and Apple Car, 148–49 and Engineer’s Mindset, 17, 131 and hierarchies at Apple, 131, 136 and iPhone sales, 140–41 leadership style of, 134, 136–37 and privacy face-off with FBI, 156–57 and revenue declines, 140–41 and Siri, 143 and visionary culture of Apple, 17 See also Apple copying other products, 70–74 Cornell’s School of Industrial and Labor Relations, 207–8, 210 Cowie, Jefferson, 201–2 Cox, Chris, 71 creativity, value of, 215 Cuban, Mark, 7, 58 Cue, Eddy, 134 “customer obsession” principle, 25 Damore, James, 93–95, 127 DataRobot, 13 Day One culture, 5–7 Dean, Jeff, 109, 111–12, 120 deaths of despair, 201 Deaton, Angus, 201, 202 democratic invention.

The AI-First Company
by Ash Fontana
Published 4 May 2021

The low cost of such a product is outweighed by the high payoff of getting a new customer. Sales: AI-based sales products prioritize leads. These tools increase the chance that the lead will close. The low cost of using these products is, again, outweighed by the high payoff of gaining a new customer. Inventory: AI-assisted inventory management can identify gaps in stock levels in order to restock on a timely basis and therefore catch customers when they want to buy—for example, running computer vision algorithms over videos collected in grocery stores to identify out-of-stock items so that the staff can quickly restock, meaning that customers can buy more.

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That is, intelligent applications that run ML algorithms over a combination of rich input data, exhaust data, and external data to make predictions, or, ideally, decisions for the customers. The opportunity for AI-First companies is to build applications like this, as illustrated by the following examples: CRM that predictively manages leads for sales, marketing, and fundraising in narrow domains; inventory management software that shows when inventory is likely to be out and orders more, ahead of time; supply-chain tracking that predicts breaks in the supply chain and suggests work-arounds; and product management tools that automatically collect feature ideas (and bugs to fix) from customer support tickets.

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A/B test, 271 accessibility of data, 72, 107 accuracy, 175, 203–4 in proof of concept phase, 59–60 active learning-based systems, 94–95 acyclic, 150, 271 advertising, 227, 240 agent-based models (ABMs), 103–5, 271 simulations versus, 105 aggregated data, 81, 83 aggregating advantages, 222–65 branding and, 255–56 data aggregation and, 241–45 on demand side, 225 disruption and, 239–41 first-mover advantage and, 253–55 and integrating incumbents, 244–45 and leveraging the loop against incumbents, 256–61 positioning and, 245–56 ecosystem, 251–53 staging, 249–51 standardization, 247–51 storage, 246–47 pricing and, 236–39 customer data contribution, 237 features, 238–39 transactional, 237, 281 updating, 238 usage-based, 237–38, 281 on supply side, 224–25 talent loop and, 260–61 traditional forms of competitive advantage versus, 224–25 with vertical integration, see vertical integration aggregation theory, 243–44, 271 agreement rate, 216 AI (artificial intelligence), 1–3 coining of term, 5 definitions and analogies regarding, 15–16 investment in, 7 lean, see Lean AI AI-First Century, 3 first half of (1950–2000), 3–9 cost and power of computers and, 8 progression to practice, 5–7 theoretical foundations, 4–5 second half of (2000–2050), 9 AI-First companies, 1, 9, 10, 44 eight-part framework for, 10–13 learning journey of, 44–45 AI-First teams, 127–42 centralized, 138–39 decentralized, 139 management of, 135–38 organization structure of, 138–39 outsourcing, 131 support for, 134–35 when to hire, 130–32 where to find people for, 133 who to hire, 128–30 airlines, 42 Alexa, 8, , 228, 230 algorithms, 23, 58, 200–201 evolutionary, 150–51, 153 alliances of corporate and noncorporate organizations, 251 Amazon, 34, 37, 84, 112, 226 Alexa, 8, 228, 230 Mechanical Turk, 98, 99, 215 analytics, 50–52 anonymized data, 81, 83 Apple, 8, 226 iPhone, 252 application programming interfaces (APIs), 86, 118–22, 159, 172, 236, 271 applications, 171 area underneath the curve (AUC), 206, 272 artificial intelligence, see AI artificial neural network, 5 Atlassian Corporation, 243 augmentation, 172 automation versus, 163 availability of data, 72–73 Babbage, Charles, 2 Bank of England, 104–5 Bayesian networks, 150, 201 Bengio, Yoshua, 7 bias, 177 big-data era, 28 BillGuard, 112 binary classification, 204–6 blockchain, 109–10, 117, 272 Bloomberg, 73, 121 brain, 5, 15, 31–32 shared, 31–33 branding, 256–57 breadth of data, 76 business goal, in proof of concept phase, 60 business software companies, 113 buying data, 119–22 data brokers, 119–22 financial, 120–21 marketing, 120 car insurance, 85 Carnegie, Andrew, 226 cars, 6, 254 causes, 145 census, 118 centrifugal process, 49–50 centripetal process, 50 chess, 6 chief data officer (CDO), 138 chief information officer (CIO), 138 chief technology officer (CTO), 139 Christensen, Clay, 239 cloud computing, 8, 22, 78–79, 87, 242, 248, 257 Cloudflare, 35–36 clustering, 53, 64, 95, 272 Coase, Ronald, 226 compatibility, 251–52 competitions, 117–18 competitive advantages, 16, 20, 22 in DLEs, 24, 33 traditional forms of, 224–25 see also aggregating advantages complementarity, 253 complementary data, 89, 124, 272 compliance concerns, 80 computer chips, 7, 22, 250 computers, 2, 3, 6 cost of, 8–9 power of, 7, 8, 19, 22 computer vision, 90 concave payoffs, 195–98, 272 concept drift, 175–76, 272 confusion matrix, 173–74 consistency, 256–57 consultants, 117–18, 131 consumer apps, 111–13, 272 consumer data, 109–14 apps, 111–13 customer-contributed data versus, 109 sensor networks, 113–14 token-based incentives for, 109–10 consumer reviews, 29, 43 contractual rights, 78–82 clean start advantage and, 78–79 negotiating, 79 structuring, 79–82 contribution margin, 214, 272 convex payoffs, 195–97, 202, 272 convolutional neural networks (CNNs), 151, 153 Conway, John, 104 cost of data labeling, 108 in ML management, 158 in proof of concept phase, 60 cost leadership, 272 DLEs and, 39–41 cost of goods sold (COGS), 217 crawling, 115–16, 281 Credit Karma, 112 credit scores, 36–37 CRM (customer relationship management), 159, 230–31, 255, 260, 272 Salesforce, 159, 212, 243, 248, 258 cryptography, 272 crypto tokens, 109–10, 272 CUDA, 250 customer-generated data, 77–91 consumer data versus, 109 contractual rights and, 78–82 clean start advantage and, 78–79 negotiating, 79 structuring, 79–82 customer data coalitions, 82–84 data integrators and, 86–89 partnerships and, 89–91 pricing and, 237 workflow applications for, 84–86 customers costs to serve, 242 direct relationship with, 242 needs of, 49–50 customer support agents, 232, 272 customer support tickets, 260, 272 cybernetics, 4, 273 Dark Sky, 112, 113 DARPA (Defense Advanced Research Projects Agency), 5 dashboards, 171 data, 1, 8, 69, 273 aggregation of, 241–45 big-data era, 28 complementary, 89 harvesting from multiple sources, 57 incomplete, 178 information versus, 22–23 missing sources of, 177 in proof of concept phase, 60 quality of, 177–78 scale effects with, 22 sensitive, 57 starting small with, 56–58 vertical integration and, 231–32 data acquisition, 69–126, 134 buying data, 119–22 consumer data, 109–14 apps, 111–13 customer-contributed data versus, 109 sensor networks, 113–14 token-based incentives for, 109–10 customer-generated data, see customer-generated data human-generated data, see human-generated data machine-generated data, 102–8 agent-based models, 103–5 simulation, 103–4 synthetic, 105–8 partnerships for, 89–91 public data, 115–22 buying, see buying data consulting and competitions, 117–18 crawling, 115–16, 281 governments, 118–19 media, 118 valuation of, 71–77 accessibility, 72, 107 availability, 72–73 breadth, 76 cost, 73 determination, 74–76 dimensionality, 75 discrimination, 72–74 fungibility, 74 perishability and relevance, 74–75, 201 self-reinforcement, 76 time, 73–74 veracity, 75 volume of, 76–77 data analysts, 128–30, 132, 133, 137, 273 data as a service (DaaS), 116, 120 databases, 258 data brokers, 119–22 financial, 120–21 marketing, 120 data cleaning, 162–63 data distribution drift, 178 data drift, 176, 273 data-driven media, 118 data engineering, 52 data engineers, 128–30, 132, 133, 137, 161, 273 data exhaust, 80, 257–58, 273 data infrastructure engineers, 129–32, 137, 273 data integration and integrators, 86–90, 276 data labeling, 57, 58, 92–100, 273 best practices for, 98 human-in-the-loop (HIL) systems, 100–101, 276 management of, 98–99 measurement in, 99–100 missing labels, 178 outsourcing of, 101–2 profitability metrics and, 215–16 tools for, 93–97 data lake, 57, 163 data learning effects (DLEs), 15–47, 48, 69, 222, 273 competitive advantages of, 24, 33 data network effects, 19, 26–33, 44, 273 edges of, 24 entry-level, 26–29, 31–33, 36–37, 274 network effects versus, 24–25 next-level, 26–27, 29–33, 36–37, 278 what type to build, 33 economies of scale in, 34 formula for, 17–20 information accumulation and, 21 learning effects and, 20–21 limitations of, 21, 42–43 loops around, see loops network effects and, 24–26 powers of, 34–42 compounding, 36–38 cost leadership, 39–41 flywheels, 37–38 price optimization, 41–42 product utility, 35–36 winner-take-all dynamics, 34–35 product value and, 39 scale effects and, 21–23 variety and, 34–35 data learning loops, see loops data lock-in, 247–48 data networks, 109–10, 143–44, 273 normal networks versus, 26 underneath products, 25–26 data pipelines, 181, 216 breaks in, 87, 181 data platform, 57 data processing capabilities (computing power), 7, 8, 19, 22 data product managers, 129–32, 274 data rights, 78–82, 246 data science, 52–56 decoupling software engineering from, 133 data scientists, 54–56, 117, 128–30, 132–39, 161, 274 data stewards, 58, 274 data storage, 57, 81, 246–47, 257 data validators, 161 data valuation, 71–77 accessibility in, 72, 107 availability in, 72–73 breadth in, 76 cost in, 73 determination in, 74–76 dimensionality in, 75 discrimination in, 72–74 fungibility in, 74 perishability and relevance in, 74–75, 201 self-reinforcement in, 76 time in, 73–74 veracity in, 75 decision networks, 150, 153 decision trees, 149–50, 153 deduction and induction, 49–50 deep learning, 7, 147–48, 274 defensibility, 200, 274 defensible assets, 25 Dell, Michael, 226 Dell Technologies, 226 demand, 225 denial-of-service (DoS) attacks, 36 designers, 129 differential privacy, 117, 274 dimensionality reduction, 53, 274 disruption, 239–41 disruption theory, 239, 274 distributed systems, 8, 9 distribution costs, 243 DLEs, see data learning effects DoS (denial-of-service) attacks, 36 drift, 175–77, 203, 274 concept, 175–76 data, 176 minimizing, 201 e-commerce, 29, 31, 34, 37, 41, 84 economies of scale, 19, 34 ecosystem, 251–52 edges, 24, 274 enterprise resource planning (ERP), 161, 250, 274 entry-level data network effects, 26–29, 31–33, 36–37, 274 epochs, 173, 275 equity capital, 230 ETL (extract, transform, and load), 58, 275 evolutionary algorithms, 150–51, 153 expected error reduction, 96 expected model change, 96 Expensify, 85–86 Facebook, 25, 43, 112, 119, 122 features, 63–64, 145, 275 finding, 64–65 pricing and, 238–39 federated learning, 117, 275 feedback data, 36, 199–200 feed-forward networks, 151, 153 financial data brokers for, 120–21 stock market, 72, 74, 120–21 first-movers, 253–55, 275 flywheels, 37–38, 243–44 Ford, Henry, 49 fungibility of data, 74 Game of Life, 104 Gaussian mixture model, 275 generative adversarial networks (GANs), 152, 153 give-to-get model, 36 global multiuser models, 275 glossary, 271–82 Google, 111–12, 115, 195, 241, 251, 253–54 governments, 118–19 gradient boosted tree, 53, 275 gradient descent, 208 graph, 275 Gulf War, 6 hedge funds, 227 heuristics, 139, 231, 275 Hinton, Geoffrey, 7 histogram, 53, 275 holdout data, 199 horizontal products, 210–12, 276 HTML (hypertext markup language), 116, 276 human-generated data, 91–102 data labeling in, 57, 58, 92–100, 273 best practices for, 98 human-in-the-loop (HIL) systems, 100–101, 276 management of, 98–99 measurement in, 99–100 missing labels, 178 outsourcing of, 101–2 profitability metrics and, 215–16 tools for, 93–97 human learning, 16–17 hyperparameters, 173, 276 hypertext markup language (HTML), 116, 276 IBM (International Business Machines), 5–8, 255 image recognition, 76–77, 146 optical character, 72, 278 incumbents, 276 integrating, 245–46 leveraging the loop against, 256–61 independent software vendors (ISVs), 161, 248, 276 induction and deduction, 49–50 inductive logic programming (ILP), 149, 153 Informatica, 86 information, 1, 2, 276 data versus, 22–23 informational leverage, 3 Innovator’s Dilemma, The (Christensen), 239 input cost analysis, 215–16 input data, 199 insourcing, 102, 276 integration, 86–90, 276 predictions and, 171 testing, 174 integrations-first versus workflow-first companies, 88–89 intellectual leverage, 3 intellectual property (IP), 25, 251 intelligence, 1, 2, 5, 15, 16 artificial, see AI intelligent applications, 257–60, 276 intelligent systems, 19 interaction frequency, 197 interactive machine learning (IML), 96–97, 276 International Telecommunications Union (ITU), 250–51 Internet, 8, 19, 32, 69, 241–42, 244 inventory management software, 260 investment firms, 232 iPhone, 252 JIRA, 243 Kaggle, 9, 56, 117 Keras, 251 k-means, 276 knowledge economy, 21 Kubernetes, 251 language processing, 77, 94 latency, 158 layers of neurons, 7, 277 Lean AI, 48–68, 277 customer needs and, 49–50 decision tree for, 50–52 determining customer need for AI, 50–60 data and, 56–58 data science and, 54–56 sales and, 58–60 statistics and, 53–54 lean start-up versus, 61–62 levels in, 65–66 milestones for, 61 minimum viable product and, 62–63 model features lean start-ups, 61–62 learning human formula for, 16–17 machine formula for, 17–20 learning effects, 20–22, 277 moving beyond, 20–21 legacy applications, 257, 277 leverage, 3 linear optimization, 42 LinkedIn, 122 loans, 35, 37, 227 lock-in, 247–48 loops, 187–221, 273 drift and, 201 entropy and, 191–92 good versus bad, 191–92 metrics for measuring, see metrics moats versus, 187–88, 192–94 physics of, 190–92 prediction and, 202–3 product payoffs and, 195–98, 202 concave, 195–98 convex, 195–97, 202 picking the product to build, 198 repeatability in, 188–89 scale and, 198–201, 203 and data that doesn’t contribute to output, 199–200 loss, 207–8, 277 loss function, 275, 277 machine-generated data, 102–8 agent-based models, 103–5 simulation, 103–4 synthetic, 105–8 machine learning (ML), 9, 145–47, 277 types of, 147–48 machine learning engineers, 39, 56, 117–18, 129, 130, 132, 138, 139, 161, 277 machine learning management loop, 277 machine learning models (ML models), 9, 26, 27, 31, 52–56, 59, 61, 134 customer predictions and, 80–81 features of, 61, 63 machine learning models, building, 64–65, 143–54 compounding, 148–52 diverse disciplines in, 149–51 convolutional neural networks in, 151, 153 decision networks in, 150, 153 decision trees in, 149–50, 153 defining features, 146–47 evolutionary algorithms in, 150–51, 153 feed-forward networks in, 151, 153 generative adversarial networks in, 152, 153 inductive logic programming in, 149, 153 machine learning in, 151–52 primer for, 145–47 recurrent neural networks in, 151, 153 reinforcement learning in, 152, 153 statistical analysis in, 149, 153 machine learning models, managing, 155–86 acceptance, 157, 162–66 accountability and, 164 and augmentation versus automation, 163 budget and, 164 data cleaning and, 162–63 distribution and, 165 executive education and, 165–66 experiments and, 165 explainability and, 166 feature development and, 163 incentives and, 164 politics and, 163–66 product enhancements and, 165 retraining and, 163 and revenues versus costs, 164 schedule and, 163 technical, 162–63 and time to value, 164 usage tracking and, 166 decentralization versus centralization in, 156 experimentation versus implementation in, 155 implementation, 158–66 data, 158–59 security, 159–60 sensors, 160 services, 161 software, 159 staffing, 161–162 loop in, 156, 166–81 deployment, 171–72 monitoring, see monitoring model performance training, 168–69 redeploying, 181 reproducibility and, 170 rethinking, 181 reworking, 179–80 testing, 172–74 versioning, 169–70, 281 ROI in, 164, 176, 181 testing and observing in, 156 machine learning researchers, 129–34, 135–36, 138, 277 management of AI-First teams, 135–38 of data labeling, 98–99 of machine learning models, see machine learning models, managing manual acceptance, 208–9 manufacturing, 6 marketing, customer data coalitions and, 83 marketing segmentation, 277 McCulloch, Warren, 4–5 McDonald’s, 256 Mechanical Turk, 98, 99, 215 media, 118 medical applications, 90–91, 145, 208 metrics, 203 measurement, 203–9 accuracy, 203–4 area underneath the curve, 206, 272 binary classification, 204–6 loss, 207–8 manual acceptance, 208–9 precision and recall, 206–7 receiver operating characteristic, 205–6, 279 usage, 209 profitability, 209–18 data labeling and, 215–16 data pipes and, 216 input cost analysis, 215–16 research cost analysis, 217–18 unit analysis, 213–14 and vertical versus horizontal products, 210–12 Microsoft, 8, 247 Access, 257 Outlook, 252 military, 6, 7 minimum viable product (MVP), 62–63, 277 MIT (Massachusetts Institute of Technology), 4, 5 ML models, see machine learning models moats, 277 loops versus, 187–88, 192–94 mobile phones, 113 iPhone, 252 monitoring, 277 monitoring model performance, 174–78 accuracy, 175 bias, 177 data quality, 177–78 reworking and, 179–80 stability, 175–77 MuleSoft, 86, 87 negotiating data rights, 79, 80 Netflix, 242, 243 network effects, 15–16, 20, 22, 23, 44, 278 compounding of, 36 data network effects versus, 24–25 edges of, 24 limits to, 42–43 moving beyond, 24–26 products with versus without, 26 scale effects versus, 24 traditional, 27 value of, 27 networks, 7, 15, 17 data networks versus, 26 neural networks, 5, 7, 8, 19, 23, 53, 54, 277–78 neurons, 5, 7, 15 layers of, 7, 276 next-level data network effects, 26–27, 29–33, 36–37, 278 nodes, 21, 23–25, 27, 44, 278 NVIDIA, 250 Obama administration, 118 Onavo, 112 optical character recognition software, 72, 278 Oracle, 247, 248 outsourcing, 216 data labeling, 101–2 team members, 131 overfitting, 82 Pareto optimal solution, 56, 278 partial plots, 53, 278 payoffs, 195–98 concave, 195–98 convex, 195–97, 202 perceptron algorithm, 5 perishability of data, 74–75, 201 personalization, 255–56 personally identifiable information (PII), 81, 278 personnel lock-in, 248 perturbation, 178, 278 physical leverage, 3 Pitts, Walter, 4–5 POC (proof of concept), 59–60, 63, 278 positioning, 245–56 power generators, 209, 278 power teachers, 209 precision, 278 precision and recall, 206–7 prediction usability threshold (PUT), 62–64, 90, 91, 173, 200–202, 279 predictions, 34–35, 48, 63, 65, 148, 202–3 predictive pricing, 41, 42 prices charged by data vendors, 73 pricing of AI-First products, 236–39 customer data contribution and, 237 features and, 238–39 transactional, 237, 280 updating and, 238 usage-based, 237–38, 281 of data integration products, 87 optimization of, 41–42 personalized, 41 predictive, 41, 42 ROI-based, 235–36, 279 Principia Mathematica, 4 prisoner’s dilemma, 104 probability, in data labeling, 107 process automation, 6 process lock-in, 248 products, 59 features of, 61, 63 lock-in and, 248 utility of, 35–36 value of, 39 profit, 213 profitability metrics, 209–18 data labeling and, 215–16 data pipes and, 216 input cost analysis, 215–16 research cost analysis, 217–18 unit analysis, 213–14 and vertical versus horizontal products, 210–12 proof of concept (POC), 59–60, 63, 278 proprietary information, 44, 279 feedback data, 199–200 protocols, 248 public data, 115–22 buying, see buying data consulting and competitions, 117–18 crawling, 115–16, 281 governments, 118–19 media, 118 PUT (prediction usability threshold), 62–64, 90, 91, 173, 200–202, 278 quality, 175, 177–78 query by committee, 96 query languages, 279 random forest, 53, 64, 279 recall, 279 receiver operating characteristic (ROC) curve, 205–6, 279 recurrent neural networks (RNNs), 151, 153 recursion, 150, 279 regression, 64 reinforcement learning (RL), 103, 147–48, 152, 153, 279 relevance of data, 74–75 reliability, 175 reports, 171 research and development (R & D), 42 cost analysis, 217–18 revolutionary products, 252 robots, 6 ROI (return on investment), 55, 63–65, 93, 164, 176, 181, 198, 279 pricing based on, 235–36, 279 Russell, Bertrand, 4 sales, 58–60 Salesforce, 159, 212, 243, 248, 258 SAP (Systems Applications and Products in Data Processing), 6, 159, 161, 247, 248 SAS, 253 scalability, in data labeling, 106 scale, 20–22, 227, 279 economies of, 19, 34 loops and, 198–200, 203 in ML management, 158 moving beyond, 21–23 network effects versus, 24 scatter plot, 53, 280 scheme, 279 search engines, 31 secure multiparty computation, 117, 279 security, 159 Segment, 87–88 self-reinforcing data, 76 selling data, 122 sensors, 113–14, 160, 280 shopping online, 29, 31, 34, 37, 41, 84 simulation, 103–4, 280 ABMs versus, 105 social networks, 16, 20, 44 Facebook, 25, 43, 112, 119, 122 LinkedIn, 122 software, 159 traditional business models for, 233–34 software-as-a-service (SaaS), 87, 280 software development kits (SDKs), 112, 280 software engineering, decoupling data science from, 133 software engineers, 139, 134–37 Sony, 7 speed of data labeling, 108 spreadsheets, 171 Square Capital, 35 stability, 175–77 staging, 249–51 standardization, 247–48, 249–50 statistical analysis, 149, 153 statistical process control (SPC), 156, 173, 280 statistics, 53–54 stocks, 72, 74, 120–21 supervised machine learning, 147–48, 280 supply, 225 supply-chain tracking, 260 support vector machines, 280 synthetic data, 105–8, 216 system of engagement, 280 system of record, 243, 281 systems integrators (SIs), 161, 248, 281 Tableau, 253 talent loop, 260–61, 281 Taylor, Frederick W., 6 teams in proof of concept phase, 60 see also AI-First teams telecommunications industry, 250–51 telephones mobile, 113 iPhone, 253 networks, 23–25 templates, 171 temporal leverage, 3 threshold logic unit (TLU), 5 ticker data, 120–21 token-based incentives, 109–10 tools, 2–3, 93–97 training data, 199 transactional pricing, 237, 280 transaction costs, 243 transfer learning, 147–48 true and false, 204–6 Turing, Alan, 5 23andMe, 112 Twilio, 87 uncertainty sampling, 96 unit analysis, 213–14 United Nations, 250 unsupervised machine learning, 53, 147–48, 281 Upwork, 99 usability, 255–56 usage-based pricing, 237–38, 281 usage metrics, 209 user interface (UI), 89, 159, 281 utility of network effects, 42 of products, 35–36 validation data, 199 value chain, 18–19, 281 value proposition, 59 values, missing, 178 variable importance plots, 53, 281 variance reduction, 96 Veeva Systems, 212 vendors, 73, 161 data, prices charged by, 73 independent software, 161, 248, 276 lock-in and, 247–48 venture capital, 230 veracity of data, 75 versioning, 169–70, 281 vertical integration, 226–37, 239, 244, 252, 281 vertical products, 210–12, 282 VMWare, 248 waterfall charts, 282 Web crawlers, 115–16, 282 weights, 150, 281 workflow applications, 84–86, 253, 259, 282 workflow-first versus integrations-first companies, 88–89 yield management systems, 42 Zapier, 87 Zendesk, 233 zettabyte, 8, 282 Zetta Venture Partners, 8–9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z ABOUT THE AUTHOR Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList.

Essential Scrum: A Practical Guide to the Most Popular Agile Process
by Kenneth S. Rubin
Published 19 Jul 2012

See PBI estimation grooming tasks related to, 104–105 mapping to sprints, 316–318 measuring velocity and, 133 organizing task work, 352–353 overview of, 100–101 parallel work and swarming, 350 as placeholders for requirements, 80–81 prioritizing, 103–104 representing technical debt, 155 selecting in sprint planning, 343–344 sign-offs and, 372 size estimates, 102–103 user stories adding detailed items, 315 Product development benefits of Scrum for, 10 calculating duration from estimated size and measure velocity, 119–120 defined, 413 economies of scale, 48 focusing on idle work not idle workers, 51–52 inventory management, 50 vs. product manufacturing, 32–33 Product manufacturing comparing plan-driven development with agile development, 59 economies of scale, 48 inventory management, 49–50 vs. product development, 32–33 Product owner accountability of, 173 chief product owner, 183–184 collaborating with development team, 170–171 collaborating with stakeholders, 171 combining with other roles, 181–182 for commercial development, 177–179 for component development, 180–181 creating/verifying acceptance criteria, 169–170 a day in the life of, 174–176 deciding if work is done, 367 decision making by, 173 defined, 414 domain skills of, 171–172 function relative to estimation process, 123 grooming product backlog, 105–106, 169 for internal development, 176–177 managing economics, 167–168 for outsourced development, 180 overview of, 165–166 in overview of Scrum roles, 15–16 participant in product planning, 288–289 participant in product portfolio, 268 participant in requirements conversation, 84 participant in sprint execution, 348 participant in sprint planning, 335 participant in sprint retrospective, 377 participant in sprint review, 364–365 people skills of, 172–173 planning functions of, 168–169 principal responsibilities of, 166 proxy product owner, 183 rules of Planning Poker, 132 in sprint planning, 21–22 team approach to, 182–183 understanding value of technical stories, 90–91 who should fill this role, 176 Product owner proxy, 183, 414 Product planning creating product backlog, 294–295 a day in the life of product owner, 175 defined, 414 defining product roadmap, 295–297 economic filter for go/no-go decision making, 275–276 economic sensibility in, 299–300 incremental/provisional funding in, 304–305 learning fast and pivoting as necessary, 305 in multilevel planning, 259 new product example, 290–291 other types of work in, 298–299 overview of, 287 participants in, 288–289 planning level details for, 258 process of, 290 product backlog and, 259–260 product owner participating in, 168–169 product roadmap and, 260–261 product vision, 259, 291–294 short time horizon as focus of, 302 speed and efficiency of, 302–303 targeting realistic confidence threshold, 300–302 timing of, 287–288 validated learning in, 303–304 Product roadmap defining, 295–297 definition of, 414 product planning and, 260–261 release planning and, 262–263 Product vision.

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It’s obvious that if we sit on a lot of inventory and then something changes, we experience one or more forms of significant waste. To minimize risks, competent manufacturers manage inventory in an economically sensible way—they keep some inventory on hand but use a healthy dose of just-in-time inventory management. Product development organizations, generally speaking, are not nearly as cognizant of their work in process. Part of the problem stems from the fact that in product development we deal with knowledge assets that aren’t physically visible in the same way as parts on the factory floor. Knowledge assets are far less intrusive, such as code on a disk, a document in a file cabinet, or a visual board on the wall.

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See also Prediction and adaptation principle, in agile development balancing predictive work with adaptive work, 43–44 based on product review, 371 daily scrum as inspect-and-adapt activity, 354 defined, 402 discovering your own path forward, 396 and exploration in approach to development, 39–40 as focus of planning rather than conformance, 249–251 leveraging variability, 35–36 plan-driven development compared with agile development, 59 responsibilities of development team, 197–198 sprint retrospective and, 375 sprint review and, 363 Agile development concerns about adopting, 225 defined, 402 managers promoting agile values, 233–234 no end state in, 395 overview of, 1–3 plan-driven approach compared with, 59–60 product backlog in, 1 sharing best practices, 396–397 The Agile Manifesto (Beck), xxxi, 30, 204–205, 210 Agile principles accepting that you can’t get it right up front, 38–39 adapting to real-time information and replanning based on, 54 adaptive, exploratory approach, 39–40 balancing predictive work with adaptive work, 43–44 batch sizes in, 48–49 cost of change and, 40–43 cost of delays and, 52–54 embracing helpful variability, 32–33 focusing on idle work, 51–52 inspection, adaptation, and transparency, 35–36 inventory management, 49–50 iterative and incremental approach to development, 33–35 keeping options open, 37–38 learning loops in, 45–46 measuring progress by asset validation, 54–55 minimizing unnecessary formality, 57–58 organizing workflow for fast feedback, 46–47 overview of, 29–32 prediction and adaptation, 37 quality built-in to development process, 56–57 reducing uncertainty, 36–37 sustainable pace in performance of work, 56 validated learning in, 44–45 value-centric delivery in, 55 variability and uncertainty and, 32 work in process (WIP) and, 48 Agile Retrospectives (Derby and Larsen), 379 All-at-once product development defined, 402 in origins of Scrum, 3 All-before-any approach defined, 402 to work in process, 48 Anticipatory process.

The TypeScript Workshop: A Practical Guide to Confident, Effective TypeScript Programming
by Ben Grynhaus , Jordan Hudgens , Rayon Hunte , Matthew Thomas Morgan and Wekoslav Stefanovski
Published 28 Jul 2021

Exercise 6.01: Implementing a Type Alias In this exercise, we will use our knowledge of types to build a function that creates products. Let's say, for example, you are working on a shopping application and when the inventory manager adds a product to the inventory, you need to push that product to your array of products. This exercise demonstrates a few ways in which type aliases can be useful by allowing you to define your Product model once and reuse it throughout your code. Now, in an actual inventory management application, you might have a frontend page that allows a user to input the product name and supporting information manually. For the purpose of this exercise, let's assume the products you want to add are named Product_0 through to Product_5 and all have a price of 100, while the number of each of these products added to the inventory is 15.

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We will construct a class that manages product objects and use interfaces to enforce rules related to how our class should be implemented. We will also use interfaces to shape our product object and class methods. In a typical web application, this code would probably be part of a product management interface – an inventory management application, for example. Alternativley, it could also be part of the product creation process, where you have a form that takes user data and processes it: Note The code file for this exercise can be found here: https://packt.link/SR8eg. For this chapter, in order to run any TypeScript file, you need to go into the file directory and execute npx ts-node filename.ts.

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For the purpose of this exercise, let's assume the products you want to add are named Product_0 through to Product_5 and all have a price of 100, while the number of each of these products added to the inventory is 15. This may not be truly reflective of an actual scenario in an inventory management application, but remember, our key goal is to use a type alias. So for now, a simple for loop to complete the aforementioned tasks will suffice: Note All files in this chapter can be executed by running npx ts-node filename.ts on the terminal. The code file for this exercise can be found here: https://packt.link/EAiHb.

Dual Transformation: How to Reposition Today's Business While Creating the Future
by Scott D. Anthony and Mark W. Johnson
Published 27 Mar 2017

As with the SaaS model, one key advantage of the model is that Netflix captured fees from customers before delivering movies and created substantial user “stickiness,” as people are more likely to start a subscription than to stop one. In 2000, Netflix had discussions about selling to Blockbuster for $50 million. Blockbuster, then the market leader, passed. Netflix set to work building sophisticated inventory management systems to help ensure that people could get the DVDs they wanted when they wanted them. The company also invested heavily to build algorithms that predicted users’ desired content based on their ratings of movies they rented. The so-called recommendations engine is so critical to Netflix that in 2008 it announced a public contest wherein the team that most improved the performance of the engine would get $1 million, as long as they crossed a 10 percent improvement threshold.

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Everyone but the most technologically savvy had to watch on a relatively small computer versus a big, crystal-clear television set. The what (discover and enjoy content) remained the same, but the how of streaming versus mail delivery differed significantly. Keys to succeeding with a mail-based model include effective inventory management, warehousing, and physical distribution. Keys to succeeding with a streaming business include developing and managing a complicated and ever-changing host of technologies. Netflix managed to make the transition. By 2010 Blockbuster had filed for bankruptcy protection, with its assets ultimately sold to DISH Network.

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TABLE AF-1 Disruption by industry Industry Disruptive trends New competitors Growth opportunities Consumer banking Peer-to-peer lending and payments, blockchain Telecommunications companies (e.g., Globe), technology giants Data-driven advisory support for businesses Shipping 3-D printing, drone delivery, smart, connected devices Amazon Real-time tracking, new inventory management services Medical devices Smart, connected devices, customized medicines Apple, IBM, Nestlé Wellness and prevention Automotive Driverless cars, integration of cars and commerce Uber, Apple, Google Transport and logistics services and solutions Professional services Democratized knowledge, platforms, software, artificial intelligence Hourlynerd, LegalZoom Software-enabled complex services Appendix: Dual Transformation Toolkit This appendix presents a set of checklists, discussion guides, and simple analytical models that help you apply key concepts in the book.

Toyota Production System: Beyond Large-Scale Production
by Taiichi Ohno and Norman Bodek
Published 1 Jan 1978

The greatest waste of all is excess inventory. If there is too much inventory for the plant to store, we must build a warehouse, hire workers to carry the goods to this warehouse, and probably buy a carrying cart for each worker. In the warehouse, people would be needed for rust prevention and inventory management. Even then, some stored goods still rust and suffer damage. Because of this, additional workers will be needed to repair the goods before removal from the warehouse for use. Once stored in the warehouse, the goods must be inventoried regularly. This requires additional workers. When the situation reaches a certain level, some people consider buying computers for inventory control.

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This book shows how to make TPM work in unionized plants and how to position TPM to support and complement other strategic manufacturing improvement initiatives. ISBN 1-56327-087-0 / 224 pages / $45.00 / Order IMPTPM-B163 Integrating Kanban with MRPII Automating a Pull System for Enhanced JIT Inventory Management Raymond S. Louis Manufacturing organizations continuously strive to match the supply of products to market demand. Now for the first time, the automated kanban system is introduced utilizing MRPII. This book describes an automated kanban system that integrates MRPII, kanban bar codes and a simple version of electronic data interchange into a breakthrough system that substantially lowers inventory and significantly eliminates non-value adding activities.

The Unusual Billionaires
by Saurabh Mukherjea
Published 16 Aug 2016

After this episode, Asian Paints hired management consultants Booz Allen Hamilton to guide them on the way forward. The key benefits of this exercise were: a) the best practices of all the manufacturing plants were brought together to improve operating efficiencies; b) working capital cycles were brought down by rationalization of both raw material and finished goods’ inventory management processes; c) freeing up of bandwidth of managers which allowed them to focus more on the core business rather than spend time managing inefficient manual processes; and d) improved organizational structure across three business units—domestic decorative, international and industrial paints.

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Supply chain management is a critical aspect for success in the paints industry given the voluminous nature of products, low margins for dealers, seasonality of demand and the large number of stock-keeping units (SKUs). Asian Paints has a track record of remaining a leader on this front. Some initiatives it has taken to strengthen this moat include being the first company to (a) use mainframes in the early 1970s to forecast demand for better inventory management; (b) start branch billing on computers in the late 1970s; (c) import a colour computer in 1979 which helped reduce tinting time from five or six days down to four hours; and (d) use GPS (Global Positioning System) for tracking movement of trucks carrying finished goods in the channel (implemented between 2010 and 2015).

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When I visited one of the largest dealers of paints in the western suburbs of Mumbai, the tinting machine was neatly tucked away in a corner of the shop. For dealers, tinting machines did away with the necessity of stocking large number of SKUs. This reduced the requirement space for dealers and improved their inventory management. More importantly, dealers could offer many more colour options to customers who, typically, want to experiment with different shades. Jenson and Nicholson introduced these machines in the mid-1990s. Berger came second in 1996, introducing tinting machines to dealer stores at a time when the emulsion category of paints in India was solely controlled by ICI (with its Dulux brand) and Asian Paints (with its Apcolite and Royale brands).

The Network Imperative: How to Survive and Grow in the Age of Digital Business Models
by Barry Libert and Megan Beck
Published 6 Jun 2016

Embrace Digital Everything There’s not much that can’t be made better by the addition of digital technology. Think of almost anything you might want to do; there’s an app for that. Ten years ago, we were less open with our technology. We welcomed digital into our professional lives in the forms of resource planning, inventory management, word processing, and data crunching, but we kept our personal lives relatively tech-free. No longer. Now we socialize, decorate our homes, get educated, create art, order dinner, date, adjust the thermostat, exercise, navigate, give to charity, shop, and shop some more, using digital technology—online and, increasingly often, through apps on our personal devices.

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The web team decides to put employee John on the project. Web design is not John’s specialty, but his last project recently ended and he has some bandwidth. When the work begins, John struggles to update his knowledge of web design and manage his other ongoing responsibilities. One month in, the inventory management system goes down and John refocuses his effort on fixing it, delaying the web design project by three weeks. Two months in, the project leader quits, and a new leader comes on board with a different vision, requiring a month of rework. John has trouble getting the access he needs from the IT department to properly test the new site, and he’s told to wait his turn as IT has a huge backlog.

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You
by Sangeet Paul Choudary , Marshall W. van Alstyne and Geoffrey G. Parker
Published 27 Mar 2016

Once OpenTable had enough restaurants on board, they built out the consumer side, which allowed them to start booking tables and collecting a lead generation fee from the restaurants. The Indian bus reservation platform redBus gained traction in a similar manner. It provided bus operators with a seating inventory management system, then opened the platform to consumers once bus operators had started using the software. Delicious is a social networking site that allows users to share lists of web bookmarks—links to Internet content that individuals love and that they want to revisit again and again. Delicious gained initial traction by allowing early users to produce valuable content in stand-alone mode, using Delicious to store browser bookmark lists in the cloud for their personal consumption.

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In the end, of course, the choice of a sponsorship/management model comes down to the purposes for which the platform is being developed and the goals of those designing it. The wireless radio frequency identification (RFID) technology is used to create smart tags that can be attached by the millions to products for inventory control. In effect, the RFID system is an inventory management platform that retailers can access to interact with the goods they distribute. The RFID platform was sponsored by a huge consortium of retailers, and the tags themselves are now manufactured by many companies which compete on the basis of price as well as design. The shared model of sponsorship and management means that the RFID technology itself doesn’t generate enormous profits for anyone—the tags sell for just a few cents apiece.

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New entrants have created ecosystems that can create and disrupt content and software more quickly and easily than large firms with thousands of employees once did. • Industries with non-scalable gatekeepers. Retailing and publishing are two examples of industries that traditionally have employed expensive, non-scalable human gatekeepers—buyers and inventory managers in the case of retail, editors in the case of publishing. Both are already undergoing disruption thanks to the rise of digital platforms, with millions of producers (artisans, craftspeople, writers) creating and marketing their own goods through platforms like Etsy, eBay, and Amazon. • Highly fragmented industries.

Competing on Analytics: The New Science of Winning
by Thomas H. Davenport and Jeanne G. Harris
Published 6 Mar 2007

To determine the optimal sourcing strategy (determining the right mix of joint replenishment, coordinated replenishment, and single sourcing) as well as manage all the logistics to get a product from manufacturer to customer, Amazon.com applies advanced optimization and supply chain management methodologies and techniques across its fulfillment, capacity expansion, inventory management, procurement, and logistics functions. For example, after experimenting with a variety of packaged software solutions and techniques, Yu concluded that no existing approach to modeling and managing supply chains would fit their needs. They ultimately invented a proprietary inventory model employing nonstationary stochastic optimization techniques, which allows them to model and optimize the many variables associated with their highly dynamic, fast-growing business.

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As a result of what we learned about the companies we studied, we believe it is impractical for these advanced skills to be broadly distributed throughout the organization. Most organizations will need to have centralized groups that can perform more sophisticated analyses and set up detailed experiments, and we found them in most of the companies we interviewed. It’s unlikely, for example, that a “single echelon, uncapacitated, nonstationary inventory management algorithm,” employed by one analytical competitor we studied in the supply chain area, would be developed by an amateur analyst. You don’t learn about that sort of thing in a typical MBA program. Regardless of where the professional analysts are located in their firms, many of the analytical competitors we interviewed stressed the importance of a close and trusting relationship between these analysts and the decision makers.

The Wide Lens: What Successful Innovators See That Others Miss
by Ron Adner
Published 1 Mar 2012

But as these innovation strategies diffused more broadly across organizations, their mastery stopped being a source of differentiation and became, instead, simply an operational requirement for getting in the game. Today we are witnessing another transition point. The enormous benefits that accrued to firms who mastered supply chain management—global procurement, just-in-time-production, lean inventory management—are still real, but they are now widely shared. In industry after industry, we see a major change taking place as firms shift from using supply chains to offer better products to embracing partnerships and collaboration to offer better “solutions.” It isn’t enough for an auto manufacturer to produce a reliable, fast, efficient car: it also needs to offer state-of-the-art computer navigation and entertainment systems.

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In parallel, it found ways to carry over elements from this expanded cardiology ecosystem to make inroads into new areas of the medical sector like neurology and endocrinology with innovative technology solutions like neurostimulation and implantable drug delivery systems. FedEx’s growth from overnight shipping to orchestrating a range of supply chain and inventory management services, eBay’s extension from online auction house (its original MVE) to virtual shopping mall to e-payment broker (PayPal) to creditor (Bill Me Later), Facebook’s expansion from social network to media platform, and Amazon’s creation of business-to-business service offers alongside its retail operations were all driven by the same fundamental principles of MVE, staged expansion, and ecosystem carryover.

Bulletproof Problem Solving
by Charles Conn and Robert McLean
Published 6 Mar 2019

Charles's team conducted secret shopper pricing analysis and found that Home Depot's prices were 15 to 18% lower for comparable products. How could it possibly operate at such low prices? The ROIC tree was the central framework to guide the analysis. What the team learned was that Home Depot had built a state of the art inventory management system, and had developed a store design that housed inventory on 20‐foot racks on the retail floor (versus Hechinger's 8‐foot racks), therefore doing without backroom storage and labor intensive restocking. Moreover, instead of storing goods mainly in a central company warehouse, it negotiated with suppliers to direct ship to Home Depot stores, or cross‐dock goods (a procedure in which a truck from a supplier is quickly unloaded and the goods go straight to store delivery trucks without being double handled).

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Complication: A new competitor, Home Depot, has emerged with a warehouse superstore model that appears to be growing much faster, driven by substantially lower pricing. Their business model is different, and compensates for lower prices by sourcing economies, lower cost logistics, and higher asset productivity. They will soon have geographic overlap with Hechinger. Resolution: To remain competitive, Hechinger needs to quickly reform its inventory management and logistics systems, and develop lower‐cost sourcing models, to allow lower pricing—or it will face a real threat even in its core markets. As you can see, this is a concise summary of where the problem solving effort sits at a moment in time. It guides the analysis that still has to be done (in this case particularly the answer to the question “What should Hechinger do?”).

Panderer to Power
by Frederick Sheehan
Published 21 Oct 2009

In October 1995, a group of supply managers from various industries visited the Fed to discuss the latest in high-efficiency “just-in-time” inventory management. . . . [One of the] executives described routing goods to drugstores: “They would load up a truck and without having orders send the truck out. The drugstore computer system would call the supplier, which would call the truck on the road and say, ‘Go to suchand-such store and deliver the following items’” . . . To [Edward] Kelley, the retiring Fed governor . . . who referred to himself as “an old inventory manager” . . . this was like “going to Mars.”9 The Greenspan Hypothesis The Fed chairman presented his proposal as a coherent whole at the December 19, 1995, FOMC meeting.

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Morgan Chase) 6, 73, 83, 93, 100, 101, 182, 185, 275 Jackson, Alphonso, 272 Jayhawk Acceptance Corporation, 165 James, Clive, 337 Jenrette, Richard, 33 Johnson, Edward C., II, 1 Johnson, Hugh, 329 Johnson, Jim, 275 Johnson, Lyndon, 27, 29, 39 Jones, Edward N., 278 Jones, Paul Tudor, II, 324 Jordan, Jerry, 170, 171, 175, 176, 193 JP Morgan Chase (see also J.P. Morgan), 274, 346 Juilliard School, 10 Junk bonds, 72, 80–81, 89, 93 Just-in-time inventory management, 159 K Kaufman, Henry, 220–221 Kavesh, Robert, 11, 59 Keating, Charles, 6–7, 85–93, 117 Keating Five scandal (see Lincoln Savings and Loan Association) Kelley, Edward, 199 Kennedy, John, 26 Kennedy, Robert, 320 Kennedy, Ted, 5, 67–68 Keon, Ed, 318 Keynes, John Maynard, 26 Keynesian economics, 26, 39 King, Mervyn, 331 Kissinger, Henry, 56, 69, 70, 74 Kissinger, Nancy, 74 Koch, Ed, 74 KKR (see Kohlberg Kravis Roberts & Co.)

Empirical Market Microstructure: The Institutions, Economics and Econometrics of Securities Trading
by Joel Hasbrouck
Published 4 Jan 2007

These analyses (which generally predate the asymmetric information models) essentially view the securities dealer as being similar in key respects to a dealer in any other commodity. Normally a vendor maintains an inventory to accommodate randomly arriving purchasers. A securities dealer, of course, must also accommodate randomly arriving sellers and in fact must replenish inventory by buying from these sellers. This complicates the inventory management problem. Control relies on order arrival rates that are sensitive to the prices posted by the dealer. The inventory control models predict that the dealer will have a preferred inventory level. Such a preference, though, may also arise from risk aversion. The discussion develops this point, its implications for dealer quotes, and multisecurity extensions.

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A dealer using public quotes would be signaling to the world at large his desire to buy or sell, putting him at a competitive disadvantage. Other liquidity suppliers face a similar sort of dilemma. A customer bidding with a limit order runs the risk that his bid will be matched by others in the market (quote matching) and that his order will be executed after those other bids or (in the worst case) not at all. If inventory management is not effected with publicly posted bid and offer quotes, though, how is it accomplished? There are a number of alternative mechanisms. They may be grouped in three categories: selective, nonpublic quoting; interdealer markets; and market-specific rules that allow dealers to participate in trades without public quoting.

Ansible for DevOps: Server and Configuration Management for Humans
by Jeff Geerling
Published 9 Oct 2015

Using the droplets variable we manually created earlier allows us to set the proper group for a particular droplet. Finally we add inventory variables per-host in add_host by adding the variable name as a key, and the variable value as the key’s value. Simple, but powerful! There are a few different ways you can approach dynamic provisioning and inventory management for your infrastructure, and, especially if you are only targeting one cloud hosting provider, there are ways to avoid using more exotic features of Ansible (e.g. with_indexed_items) and complex if/else conditions. This example is slightly more complex due to the fact that the playbook is being created to be interchangeable with other similar provisioning playbooks.

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But for many organizations, there are needs that stretch basic CLI use too far: The business needs detailed reporting of infrastructure deployments and failures, especially for audit purposes. Team-based infrastructure management requires varying levels of involvement in playbook management, inventory management, and key and password access. A thorough visual overview of the current and historical playbook runs and server health helps identify potential issues before they affect the bottom line. Playbook scheduling can help ensure infrastructure remains in a known state. Ansible Tower checks off these items—and many more—and provides a great mechanism for team-based Ansible usage.

Reinventing Capitalism in the Age of Big Data
by Viktor Mayer-Schönberger and Thomas Ramge
Published 27 Feb 2018

Employee reports and punch cards had to be read and analyzed. Simplified metrics did not capture the entire picture. Thanks to digital computing, by the 1970s it became increasingly possible to consolidate the many different data sources in firms that cover everything from financial accounting and reporting to human resources, manufacturing, inventory management, and sales into a single database. Called enterprise resource planning (ERP), and pioneered by German start-up SAP, these systems gave managers tools to shape the flow of information much more comprehensively than ever before. The big challenge when delegating decision-making is to ensure that the advantages of centralized information flows and decision-making, such as reduced information needs across the organization as well as coherence of decisions, aren’t lost.

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But over time, midsize firms, too, will join the fray. While we may initially see a lot of adoption in the HR field, the application of such a multidimensional market approach is by no means limited to matters of staff allocation. We will see it pop up in other areas, such as marketing, procurement, inventory management, finance, even product development. Once such a market mechanism is in place, its scope may extend outside the firm. Why restrict supply and demand when the mechanism could attract participants from outside the organization as well? Of course there are limits, and some internal markets may never be open to outsiders because of legal restrictions (e.g., to avoid anticompetitive collusion among companies), safety and security concerns, or trade secrets that need to be protected.

Lessons From Private Equity Any Company Can Use
by Orit Gadiesh and Hugh MacArthur
Published 14 Aug 2008

Looking carefully at these three deductions—again, debt service, working capital requirements for sales growth, and capital expenditures—you can quickly see that only one of these can be actively managed in the near term: working capital requirements (debt is relatively fixed, and capital expenditure has both a maintenance and a “growth” component; we’ll address the growth component below). If you need to find more cash on a sustainable basis, you need to drive down your working capital. Going back to our example, if through better inventory management and receivables/payables management we can move our business from a working capital ratio of 30 percent of new sales to 20 percent of new sales, that will save $10 of cash and increase the business’s cash creation from $35 to $45—in other words, a 30 percent increase in cash creation as a result of using our working capital more efficiently.

The Fissured Workplace
by David Weil
Published 17 Feb 2014

In a complex manufacturing system like auto production, this requires high levels of coordination at each step in the process, careful management of capital and labor, attention to quality and factors that affect throughput, and an overhaul of management support systems, from accounting, to inventory management, to compensation. It also requires a different way of handling logistics—the movement of goods—within a manufacturer, between the manufacturer and its suppliers, and between the manufacturer and the end retailer of goods. As lean manufacturing spread to industries beyond the autos and into the retail sector, the importance of logistics as part of competitive strategy rose as well.

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This led to a seemingly endless cat-and-mouse game between the WHD and small-scale contractors, whereby efforts to reduce sweatshop conditions in the garment industry were thwarted by companies constantly going into and out of business, either because of the harsh competitive conditions in the industry or as a means of evading penalties for past violations. The dynamics of the apparel industry changed dramatically given the emergence of lean retailing. Lean retailing relies on information technology to provide retailers with real-time point-of-sale data for purposes of reordering products and inventory management. These practices reduce the need for retailers to stockpile large inventories, thereby reducing their risks of stock-outs, markdowns, and inventory-carrying costs. Apparel companies supplying to lean retailers must operate far more responsively and accept a great deal more consumer demand risk.

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This account is taken from Marc Levinson’s detailed study of the rise and fall of “the Great A&P.” See Levinson (2011). 3. Ibid., 81–84. Levinson quotes a Federal Trade Commission report of 1919 that noted, “The cost of these individual delivery systems … is a large item to be figured into the wholesale prices” (83). 4. The advantages of internalizing inventory management were huge, as shown by “inventory turns,” which is the amount of time required to turn over the inventory held by a retailer. At a time when its principal competitors’ inventory turns were four months (requiring paying interest, committing storage space, and bearing the risk of unsold goods for that amount of time), A&P had reduced its turns to a mere five weeks (ibid., 89). 5.

Industry 4.0: The Industrial Internet of Things
by Alasdair Gilchrist
Published 27 Jun 2016

Leading fashionable retailers that target young fashion-conscious consumers are already investing billions in the IoT—think about mobile phone shops and high street fashion stores. Their adoption of high-tech advertising and providing in-store virtual customer experience provided by the adoption of the IoT has realized the financial returns beyond expectations. The operational and financial benefit that retailers have reaped range from efficient inventory management to real-time customer targeted promotions, and instore entertainment that increase footfall, develops the brand and ultimately increase sales. These pioneers of IoT have identified early that it was necessary to evolve and transform their business practices to conform with the shift in their customers’ lifestyles.

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More often than not, the IIoT is portrayed as deploying high technology, such as augmented reality, RFID customer tracking with personalized advertising, and similar marketing concepts that would not fit easily with most retailers’ current or even future customers. 29 30 Chapter 2 | Industrial Internet Use-Cases The advantages of IoT are not delivered just through enhanced customer experience—many of the benefits come in the back store, in stock control, inventory management, perishable and cold chain management, and for larger operations, digital signage, fleet management, and smart fulfillment centers. As an example, three of the largest supermarkets in the UK reported savings of 50% after the adoption of the IIoT. For some retailers deploying IIoT solutions, it has meant installing a vast range of bewildering technologies, including hardware, sensors, devices, apps, telematics, data, and connectivity to the cloud.

Carjacked: The Culture of the Automobile and Its Effect on Our Lives
by Catherine Lutz and Anne Lutz Fernandez
Published 5 Jan 2010

We tried to shrug off some discomfort: as a member of a profession that has a tenuous reputation for integrity, maybe Pete was just a bit defensive. Pete rummaged through his desk and produced a brochure. After reviewing the eight different options packages available, we chose a more basic, level 3 package. Pete would have to go see what his inventory manager could locate and left us for a few minutes, returning to tell us that we were in great luck! He could get us a level 4 Prius in less than two weeks. Were we interested? Yes, we were, but we needed to know how much he was asking. Pete thought he could get us the car for $25,000. Were we interested?

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Pete explained that there was no state sales tax on hybrids, and we could apply for a federal tax deduction, so the premium over sticker should not concern us. We were committed to buying a hybrid and the price was a lot better than the $28,000 the first Toyota dealer had quoted for the exact same car. When Pete returned, we told him yes. “Great,” he said, “let me just go check with my inventory manager.” We were excited. We were going to get a new car! This wave of euphoria quickly disappeared as Pete returned with bad news. The Prius he had for us was not a level 4 but a level 8, the fully loaded model. It would be nearly $28,000. How could the car suddenly change from a level 4 to a level 8 in the course of twenty minutes?

Confessions of a Microfinance Heretic
by Hugh Sinclair
Published 4 Oct 2012

If a client defaults on a loan, the MFI can easily confiscate the inventory of the client, which is usually put up as collateral for the loan, and sell it rapidly to another person in the same market. The Japanese invented just-in-time inventory management—a principle replicated around the world ever since. Tying up large amounts of capital in inventory was unproductive—far better to have the minimum possible inventory. Microfinance promotes the precise opposite of prudent inventory management. Micro-entrepreneurs by the million obtain loans to buy inventory that sits on shelves in competitive markets gathering dust before sale but accumulating an interest expense in the meantime.

Ghost Road: Beyond the Driverless Car
by Anthony M. Townsend
Published 15 Jun 2020

For decades, just-in-time approaches have sought to reduce stockpiles of goods to the bare minimum needed for the next cycle of production or distribution. AVs will play a major role in the next wave of slimming down stocks. Walmart, for instance, has already trimmed billions of dollars of inventory using automated systems for loading and unloading delivery vehicles and restocking shelves. But a more radical approach to automated inventory management could do away with warehouses altogether. Imagine a fleet of AV freighters synchronized like a microtransit mesh. The inventory that used to be stored in a central depot would instead be spread out among various vehicles. To get a needed item from its current rolling location to your front door would entail a series of transfers, like a passenger riding driverless shuttles across town.

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See artificial intelligence AirCloset, 148 Alexander, Christopher, 101 Alibaba, 11, 115, 118–19, 147 Alstom, 60, 104 Amazon Amazon Day promotion, 132, 219 Amazon Go stores, 183, 220 Amazon’s Web Services division (AWS), 86 Basics brands, 138 fulfillment centers, 123, 132, 136–37, 196n Key, 118, 127 Kiva AV warehouse sleds, 136–37 market capitalization, 118 package lockers, 127, 219, 221 predatory practices, 219, 223 Prime, 118, 119, 132, 219 Prime Fresh grocery-delivery service, 116 product sales in 2018, 118 same-day delivery, 119, 138, 219 separation of humans and AVs, 241–42 shipping costs, 119, 219 Whole Foods acquisition, 219–20 American Automobile Association, 45 American Trucking Associations, 156 American Wonder, 5 America’s Workforce and the Self-Driving Future, 154 Amsterdam, 63, 210, 222 Apple self-driving vehicle project, 8 Archimedes, 169 Arma (Navya), 103–4, 104 artificial intelligence (AI) AI winters, 235 human-machine hybrids, 46, 153 machine learning, 7, 36, 152–53, 235, 238 online experiences and, 81 singletons, 237–38 Singularity predictions, 234–35, 236–38 and task model for computerization of work, 152–54 in urban ushers, 78 use in persuasion, 152 see also deep learning Atlas Shrugged (Rand), 221–22 Audi, 30, 31 auto-manufacturing industry consumer-protection laws and, 25 disruption by driverless revolution, 19 and financial crisis of 2007–2008, 7 new methods of manufacturing, 54 personal transportation services, 11 predicted new-car sales decline, 11 small firms and new methods, 54 vehicular variety increase and, 54–55 automated ground vehicles (AGVs). See conveyors automated vehicles (AVs) accidents and failures, 231, 235–36 ancient fables and legends, xiii automated inventory management, 157–58 “autonomous” vs. “automated” vehicles, 39 benefits from, 9–10, 155, 241 disengagements and, 41–42 early self-steering schemes, 5–6 electrification as symbiotic technology, 54–55 “fifth-generation” (5G) wireless grid and, 42 in-car media and interior design, 30–31 in-car surveillance and driver monitoring, 31–32 and increased importance of driving, 43–45 infrastructure and cellular grid, 40–41, 42–43 modern-day myths about future, xv–xvi predicted growth in numbers, 10, 11–12 promise of, 8–12 terminology and, 45–47 see also specific topics automation airplane “crew resource management,” 29–30 dockless systems and, 65–66, 70–71 effect on pilot training, 45 electrification as symbiotic technology, 54–55 fear of intelligent automobiles, 39, 43, 45 impact on jobs, 149–56 outdated cultural understanding of, 80–81 and scooters, 65–66, 70–71 task model for computerization of work, 150–54, 151, 155 of taxis, predicted by 2030, 10–11 urban concentration and, 186–87 see also automated vehicles autonomists disengagements and, 41–42 inevitability of full autonomy, 39, 95, 96 minimal role of government, 40 overreaches and false arguments of, 40–41, 73, 99 overview, 39–43 platooning and, 70 public transit and, 214–15, 216 self-driving trucks for freight, 122 “autonomous” vs.

Network Security Through Data Analysis: Building Situational Awareness
by Michael S Collins
Published 23 Feb 2014

= current_ip: results[ip] = process_epoch_info(bins) bins = {} if starting_epoch == -1: starting_epoch = time - (time % 86400) # Sets it to midnight of that day bin = (time - starting_epoch) / precision bins[bin] = 1 a = bins.sort() for i in a: print "%15s|%5d|%5d|%8.4f" % (ip, bins[a][0], bins[a][1], 100.0 * (float(bins[a[0]])/float(bins[a[1]]))) The second stage of beacon detection (as usual) is inventory management. An enormous number of legitimate applications, as we saw earlier, transmit data periodically. NTP, routing protocols, and AV tools all dial home on a regular basis for information updates. SSH also tends to show periodic behavior, because administrators run periodic maintenance tasks via the protocol.

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To detect beacons, you identify hosts that communicate consistently over a time window, as done with find_beacons.py. Beacon detection runs into an enormous number of false positives because software updates, AV updates, and even SSH cron jobs have consistent and predictable intervals. Beacon detection consequently depends heavily on inventory management. After receiving an alert, you will have to determine whether a beaconing host has a legitimate justification, which you can do if the beaconing is from a known protocol, is communicating with a legitimate host, or provides other evidence that the traffic is not botnet C&C traffic. Once identified as legitimate, the indicia of the beacon (the address and likely the port used for communication) should be recorded to prevent further false positives.

Building Microservices
by Sam Newman
Published 25 Dec 2014

When modeled as services, these capabilities become the key operations that will be exposed over the wire to other collaborators. Turtles All the Way Down At the start, you will probably identify a number of coarse-grained bounded contexts. But these bounded contexts can in turn contain further bounded contexts. For example, you could decompose the warehouse into capabilities associated with order fulfillment, inventory management, or goods receiving. When considering the boundaries of your microservices, first think in terms of the larger, coarser-grained contexts, and then subdivide along these nested contexts when you’re looking for the benefits of splitting out these seams. I have seen these nested contexts remaining hidden to other, collaborating microservices to great effect.

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The bounded contexts inside the warehouse being popped up into their own top-level contexts In general, there isn’t a hard-and-fast rule as to what approach makes the most sense. However, whether you choose the nested approach over the full separation approach should be based on your organizational structure. If order fulfillment, inventory management, and goods receiving are managed by different teams, they probably deserve their status as top-level microservices. If, on the other hand, all of them are managed by one team, then the nested model makes more sense. This is because of the interplay of organizational structures and software architecture, which we will discuss toward the end of the book in Chapter 10.

Smart Mobs: The Next Social Revolution
by Howard Rheingold
Published 24 Dec 2011

Five billion codes are scanned every day in 140 countries.41 Among the many changes made possible by barcodes was a transformation of manufacturing worldwide from a warehouse system to a “just-in-time” system; as automobiles and other component-based systems (including grocery store inventories) are assembled, barcodes and data networks coordinate the manufacture and shipment of future components in tightly synchronized streams. Wal-Mart achieved dominance largely through its global, instantaneous inventory management system. When you add a barcode scanner or a radio frequency identity tag reader to a handheld device, it becomes easy to link a Web page or other online process to a tag that is physically associated with a place or object. Today, people can point a reader at an object and view relevant content on the screen of a pocket computer or hear spoken information by means of text-to-speech through a cell phone.

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See also Native Americans Industrialization Information Tapestry InfoScope InfoWorld, Ink-jet printers Innamaa, Ilkka Innovation commons See also Commons Insect behavior Institute for Advanced Study (Princeton University) Intel and Bluetooth supercomputers Intelligence: artificial (AI) extraterrestrial humanistic (HI) swarm See also Intelligent (digital) cities Intelligent (digital) cities Interaction Lab Interaction Order International Paper Internet advent of and ARPA cable access to as an innovation commons and Metcalfe's Law, xv T1 connections to T3 connections to Internet Untethered, The (Standage) Interpersonal awareness devices INTV Inventory management systems Ioannidis, John IRC (Internet Relay Chat) Irrigation systems Ishii, Hiroshi ISPs (Internet Service Providers) It's Alive (company) Italy Ito, Mizuko I-WAY experiment Japan: keitai users in ImaHima in i-mode service in NTT in sense of privacy in, versus in America and shared forestry resources Shibuya Crossing in WISnet in Japanese language JEDI (Joint Expeditionary Digital Information) Jefferson, Thomas Jenkins, Henry Jhanji, Neeraj John Paul II (pope) John W.

The Reckoning: Financial Accountability and the Rise and Fall of Nations
by Jacob Soll
Published 28 Apr 2014

Edward III (ruled 1327–1377) stated what other kings in Europe would insist on until the nineteenth century: Kings do not render accounts except to God.20 All these account books and rolls beg the question: Did they at least work well? Surely a good diligent accountant, keeping daily records, should have been able to ascertain a certain level of mastery over accounts. This was the case in cash and inventory management, but even here, it could not be exact. Without Arab numerals and therefore fractions, there was internal error built in the Roman numeral system. No matter how tenacious an account keeper was, the plethora of Xs, Ls, and Is made cumbersome numbers such as DCCCXCIII (893) and left no space for fractions.

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He should learn to audit state financial registers, so as to verify everything from state savings to expenditures and receipts. He should never stop doing this work, warned Colbert, for it is so delicate that it can be left to no one else. In short, Colbert felt the young prince needed to learn the basics of accounting and inventory management in order to be king.24 More than that, Colbert imbued Louis’s government with a merchant’s sense of financial secrecy. In 1661, as the king and his leading minister worked to form their first government, Colbert wrote a memo to Louis on how to organize and manage the Royal Council, mandating that all ministers and members of government take oaths of secrecy and that anyone breaking the oath be expelled from government.

Principles of Corporate Finance
by Richard A. Brealey , Stewart C. Myers and Franklin Allen
Published 15 Feb 2014

To do business, firms need reserves of raw materials, work in process, and finished goods. But these inventories can be expensive to store and they tie up capital. Therefore, inventory management involves a trade-off between the advantages of holding large inventories and the costs. In manufacturing companies, the production manager is best placed to make this judgment, and the financial manager is not usually directly involved in inventory management. So we spend less time on this topic than on the management of other current assets. Our second task is to look at accounts receivable. Companies frequently sell goods on credit, so that it may be weeks or even months before the company is paid.

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Second, there are carrying costs, such as the cost of storage and the opportunity cost of the capital that is invested in inventory. Hongxi can reduce the order costs by placing fewer and larger orders. On the other hand, a larger order size increases the average quantity held in inventory, so that the carrying costs rise. Good inventory management requires a trade-off between these two types of cost. FIGURE 30.5 As the inventory order size is increased, order costs fall and inventory carrying costs rise. Total costs are minimized when the saving in order costs is equal to the increase in carrying costs. BEYOND THE PAGE ● ● ● ● ● Try It!

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The optimal order size (2,043 tons in our example) is termed the economic order quantity, or EOQ.2 Our example was not wholly realistic. For instance, most firms do not use up their inventory of raw material at a constant rate, and they would not wait until stocks had completely run out before they were replenished. But this simple model does capture some essential features of inventory management: • Optimal inventory levels involve a trade-off between carrying costs and order costs. • Carrying costs include the cost of storing goods as well as the cost of capital tied up in inventory. • A firm can manage its inventories by waiting until they reach some minimum level and then replenish them by ordering a predetermined quantity.3 • When carrying costs are high and order costs are low, it makes sense to place more frequent orders and maintain higher levels of inventory

Arriving Today: From Factory to Front Door -- Why Everything Has Changed About How and What We Buy
by Christopher Mims
Published 13 Sep 2021

The system does care which mobile shelving unit items go into, however. That’s why it’s not up to Tyler which items have been delivered to him in which totes, and which bin on which pod he’ll be asked to stuff them in—all of that is decided by algorithms running under the umbrella of Amazon’s warehouse management system, and more broadly, its globe-spanning inventory management system. By asking Tyler to put our USB charger in one bin, allowing him to stick an identical one in another bin of his choosing, and, overall, distributing the dozens of chargers that arrived at this distribution center in a single box across dozens of mobile shelving units, the random stow system maximizes the chances that a mobile shelf with one of these chargers in it is readily accessible when an Amazon customer orders one and it must be extracted from the storage system and delivered to that person.

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Some of this behavior is a natural consequence of the design of the system of which these robots are a part. For example, shelves that are needed frequently tend to stay close to the human stowers and pickers who must access them often. Their actions are orchestrated by the omniscient, hugely powerful warehouse and inventory management systems of Amazon, but to a surprising degree, their movement is self-organized. The amount of time an item resides in an Amazon fulfillment centers varies, and Amazon does not comment on this metric. But in summer 2018, Amazon implemented an index that includes data like how long inventory belonging to a seller on its Marketplace has been in its warehouses.

Hawai'I Becalmed: Economic Lessons of the 1990s
by Christopher Grandy
Published 30 Sep 2002

One could hardly find a popular business The Bubble
13 or economic journal that did not wring its hands over the competitive threat posed by Japan and the apparent failure of U.S. business to respond. Pundits in the United States side lauded everything Japanese, from lifetime employment and tightly-knit interlocking directorships to just-in-time inventory management and total quality management circles.5 Paradoxically, some of these practices would later be cited as the sources of Japanese uncompetitiveness in the 1990s; others were quietly and effectively adopted. For example, lifetime employment and interlocking directorates have both been criticized as sources of problems for Japan’s economy.6 The former is seen as an expense that can no longer be supported, the latter as one reason the financial infrastructure failed to identify troubled firms and to act decisively to remedy the problems.

Building Habitats on the Moon: Engineering Approaches to Lunar Settlements
by Haym Benaroya
Published 12 Jan 2018

Fire-proof/low-outgassing clothes Building material for inflatable structures Efficient food production Advanced understanding of food production/hydroponics Reduced logistics through local food production for spacecraft cabins, planetary habitats Dual-Use Technologies: Power Terrestrial Applications Technology Space/lunar/Mars applications Batteries for: autos – remote operations for DOD, NSF polar programs High-density energy storage Alternate energy storage (flywheels) Reduced logistics for planetary bases High reliability, low-maintenance power systems Spaceship power storage Clean energy from space Beamed power transmission Orbital power to surface base Surface power transmission to remote assets Remote operations for: DOD, NSF polar programs Small nuclear power systems Surface base power Pressurized surface Rover Interplanetary transfer vehicle Remote operations for: DOD, NSF polar programs High efficiency auto engines High efficiency, high reliability low-maintenance heat-to-electric conversion engines Energy conversion for planetary bases: low servicing hours – little or no logistics Table 2.3Partial list of dual-use technologies: Structures and Materials, Science and Science Equipment, and Operations and Maintenance Dual-Use Technologies: Structures and Materials Terrestrial Applications Technology Space/lunar/Mars applications Vehicles Fuel-efficient aircraft Modular construction, homes Composite materials: hard – soft Advanced alloys, high-temperature Cryogenic tanks Habitat enclosures Pressurized Rover enclosures Space transit vehicle structures Aircraft fuel tanks Home insulation Superinsulation Coatings Cryogenic tanks Habitable volumes Large structures, high-rise buildings, bridges Commercial aircraft: improved safety – lower maintenance Smart structures Imbedded sensors/actuators Space transit vehicle structures Planetary habitat enclosures Surface power systems Rover suspensions Dual-use Technologies: Science and Science Equipment Terrestrial Applications Technology Space/lunar/Mars applications Energy resource exploration Environmental monitoring, policing Spectroscopy: gamma ray – laser – other Geo-chem mapping Resource yield estimating Planetary mining operation planning Undersea exploration Hazardous environment assessments and remediation Telescience Remote planetary exploration Environmental monitoring Medicine Image processing: compression technique – storage – transmission – image enhancements Communication of science data Correlation of interferometer data Improved health care Sports medicine – cardiovascular Osteoporosis – immune systems Isolated confined environments/Polar operations Noninvasive health assessments Physiological understanding of humans Instrumentation miniaturization Countermeasures for long-duration and/or micro-g space missions Health management and care Dual-Use Technologies: Operations and Maintenance Terrestrial Applications Technology Space/lunar/Mars applications Military Systems and structures health monitoring Inventory management Task partitioning Reliability & quality assurance in long-term hazardous environments System health management and failure prevention through AI and expert systems, neural nets Systems and structures health monitoring Inventory management Self-repairing technologies Logistics improvement Crawford discussed what it would take to create and sustain a space development program that would last for centuries, eventually leading to interstellar spaceflight capability. ( 22 ) He pointed to the possibility of replacing war by space development as the adventure that humanity requires.

The Invisible Hands: Top Hedge Fund Traders on Bubbles, Crashes, and Real Money
by Steven Drobny
Published 18 Mar 2010

We are playing the current economic bounce, which has come off the back of the broader inventory restocking theme. Our understanding of this theme crystallized during a dinner conversation in the beginning of 2009 with the CEO of one of the largest metals companies in the world. For some time, we have held a very high-level macro view that the move to just-in-time inventory management would at some point be destabilizing for the commodity markets. There is an exceptional book on this called The End of the Line by Barry Lynn, a manufacturing specialist. Its simple premise is that the move to just-in-time inventory and global outsourcing forced all of the volatility of output and debt associated with production onto a much less well-capitalized supply chain.

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Because of the collapse in capital expenditure, the small producer has essentially been taken out of the equation, creating greater concentration with greater pricing pressure. You have China acquiring global reserves and the impact that will have on commodities. You have this whole just-in-time inventory management/supply chain dislocation that is taking place. You have the public risk that is now taking all of the private risk. You have commodity inflation at a lower threshold. And you have the inversion of the demographic pyramid, meaning dependency ratios are going to rise (see box). Dependency Ratio Also referred to as the total dependency ratio, the dependency ratio is a measure showing the number of dependents (aged 0-14 and over the age of 65) to the total population (aged 15-64), which is calculated by Number of dependents ÷ Population (ages 15-64) x 100%.

From Airline Reservations to Sonic the Hedgehog: A History of the Software Industry
by Martin Campbell-Kelly
Published 15 Jan 2003

The new IBM computer was relatively inexpensive, sold in large numbers, and thus created a much broader market for lower-cost software than could ever have been satisfied by software contractors. A software product was a program that could be used without modification by a large number of corporate users. Software products typically automated common business functions, such as payroll or inventory management, or ran an entire medium-size business, such as a manufacturing operation or a savings bank. They were typically priced between $5,000 and $100,000. The more successful ones sold in the hundreds, and a few in the thousands. The arrival of the personal computer in the mid 1970s created an opportunity for mass-market software.

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Type of package Accounting General ledger Accounts receivable/payable Integrated accounting Billing, budgeting, costing Responsibility accounting, asset accounting, and CPA packages Other Packages Median quoted price 46 96 28 24 32 $5,000 $6,000 $8,400 $7,000 $5,000 27 $5,000 Financial Financial analysis Stock transfers and shareholder accounting Credit union and profit-sharing systems 44 10 18 $2,800 $16,000 $6,000 Inventory management, distribution, and warehousing 50 $7,000 Leisure time/ecology 14 $300 Mailing activities 42 $2,000 Marketing 26 $10,000 Mathematics and statistics 36 $3,000 Operations research and management science Mathematical programming Simulation, models, and games Other 34 37 5 $12,500 $9,200 $10,000 Payroll 93 $5,600 Project management and control 50 $6,600 Personnel and pension 26 $10,000 Purchasing and order processing 22 $12,400 Other 17 $9,000 Total number of packages 777 Source: ICP Quarterly, July 1974, as analyzed on p. 64 of International Resource Development Inc., Computer Services and Software Markets. 

Start Small, Stay Small: A Developer's Guide to Launching a Startup
by Rob Walling
Published 15 Jan 2010

It takes a while to rank high in Google for a large quantity of terms – some say 12-18 months (this is known as the Google Sandbox and its existence is an ongoing debate). Even if there is no Google Sandbox, it will take a few months to begin ranking for enough terms to bring in a noticeable stream of traffic. With that said, let’s turn our eyes to a specific example. The Power of Google Let’s take the example of a theoretical application: an inventory management system. It’s a good example because it could conceivably sell for $200 at a conversion rate of 0.5%, so it fits with the assumptions we’ve made thus far. At this point, we’re looking for 500 visitors per month from organic traffic. Let’s look at how we might determine if this is possible.

The Dhandho Investor: The Low-Risk Value Method to High Returns
by Mohnish Pabrai
Published 17 May 2009

He moved his family to Southern California and his brother lent some financial support as they got settled. After starting at Cherokee, he worked full-time and put in all the overtime the company would allow. Cherokee recognized some of his accounting skills and put him in the stockroom helping out with inventory management. The pay was a little over minimum wage. His remaining two brothers and one sister (and all their families) joined him in a few months. They all lived together in a small apartment and in short order nearly all the adults had assembly linetype jobs at Cherokee. One brother was single. With seven adults, the paychecks began to flow in and Manilal and all his siblings started saving in earnest.

The Art of Scalability: Scalable Web Architecture, Processes, and Organizations for the Modern Enterprise
by Martin L. Abbott and Michael T. Fisher
Published 1 Dec 2009

Failing to specialize and focus your staff will result in too many engineers having too little information on the entire system to be effective. If you run a commerce site, you might have code, objects, methods, modules, servers, and databases focused on checkout, finding, comparing, browsing, shipping, inventory management, and so on. By dedicating teams to these areas, each team will become an expert on a codebase that is itself complex, challenging, and growing. The resulting specialization will allow for faster new feature development and a faster time to resolve known or current incidents and problems. All of this increase in speed to delivery may result in a faster time to market for bug fixes, incident resolution, and new feature development.

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As such, they are going to need to rely on all three axes of the AKF Application Scale Cube. The architects decide that it makes most sense to split the application primarily by the functions of the site. Most of the major functions that don’t directly rely on customer information will get a swim lane of functionality (see Chapter 21). Browsing, searching, catalog upload, inventory management, and so on and every other verb that can be performed without needing to know specific information about a particular customer becomes a branch of functionality within the site and its own code base. These splits allow these services to grow with transaction volume regardless of customer growth as the number of customers isn’t important when delivering the results of a search, or a catalog upload, and so on.

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Ecommerce Implementation The AllScale data architects ultimately decide that the data architecture is going to be impacted along three dimensions: transaction growth upon the databases, decisions made in Chapter 23 to scale the application, and growth in customers and products. As such, they are going to need to rely on all three axes of our AKF Application Scale Cube. In Chapter 23, the team decided to split functionality of the site to allow for growth and complexity in the application. You may recall that browsing, searching, catalog upload, inventory management, and so on, and every other verb that can be performed without needing to know specific information about a particular customer, became a branch of functionality within the site and its own code base. Applying the principles of Chapter 21, the team decides to make these swim lanes; each swim lane needs to have data relevant to the needs of the application.

One Click: Jeff Bezos and the Rise of Amazon.com
by Richard L. Brandt
Published 27 Oct 2011

Further, the offering began to look a lot like the phenomenon now known as cloud computing—tapping into a program sitting on a Web server somewhere rather than one sitting on your own desktop. Another company using the service, for example, Monsoon of Portland, Oregon, offered software that companies could use to tap into Amazon’s software to simplify their own inventory management. “Web 1.0 was making the Internet for people; Web 2.0 is making the Internet better for computers,” Bezos predicted in a speech at the Web 2.0 conference in San Francisco in 2004. Amazon became known as one of the most innovative companies in cloud computing. From its initial start in 2002, Amazon Web Services offerings just kept expanding.

Game Over Press Start to Continue
by David Sheff and Andy Eddy
Published 1 Jan 1993

“Back in the Colgate days, it used to take two months to get a report after the fact to find out the mistakes you made—which you were compounding and which were leading you down the wrong road,” Main says. “We were getting it daily.” Japanese companies in the automobile industry used efficient just-in-time inventory management systems. Essentially this meant that companies bought parts they needed only when they needed them. The merchandising feedback loop allowed Nintendo to instigate a kind of just-in-time inventory policy so that it ordered only what it needed as it needed it from NCL. Likewise, NCL could thus avoid over- or underproduction.

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Even the kids whose parents held out still managed to get games; in 1989, in a survey of what kids in Sandwich, Illinois, bought with their allowances and other money they earned, the near unanimous choice was Nintendo games. The editor of one toy-industry journal noted that “Nintendo has become a name like Disney or McDonald’s. They’ve done it by doling out games like Godiva chocolates.” In 1988, Fortune observed that “so far the strategy looks like a winner.” “Inventory management” is what Peter Main called it. The Atari wave had floundered in large part because of a flooded market. Main made certain that scarcity whetted the public’s appetite and sustained demand as Coleco had done in 1984, when there was a shortage of Cabbage Patch Kids. By design, Nintendo did not fill all of the retailers’ orders, and it kept half or more of its library of games inactive.

The Content Trap: A Strategist's Guide to Digital Change
by Bharat Anand
Published 17 Oct 2016

The recommendation engine, also thought of as a means of increasing customer satisfaction, doubled as an inventory management tool: It let the company recommend not only movies a customer might like, but also those that were in stock! Netflix integrated its sorting machines with the U.S. Postal Service to make deliveries more efficient. It even hired a former postmaster general to guide its operations. And its distributed warehouse system allowed it to secure DVD titles at a relatively low cost per user, since it minimized inventory and maximized turns. The cumulative effect of these choices was impressive: By 2007 Netflix’s inventory management costs were one-third those of Blockbuster.

After Steve: How Apple Became a Trillion-Dollar Company and Lost Its Soul
by Tripp Mickle
Published 2 May 2022

The Compaq job put him in charge of inventory at a company whose sales had surged from $3 billion a year in 1991 to nearly $34 billion by 1997, the year he joined. It was the type of job that he’d been working toward his entire career. When Cook arrived, Compaq was in the throes of addressing an inventory headache. The ratio of warehouse-to-manufacturing space was two to one. To keep up with its swelling orders, the company needed to improve its inventory management, so it would require less floor space. Cook worked to make inventory purchases match demand by scheduling deliveries an hour before a manufacturing shift began. The arrangement meant that Compaq held inventory for only two hours each day, the small window right before each of its twelve-hour manufacturing shifts.

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He’s shown here discussing it at a Vanity Fair event in 2014. Kimberly White/Getty Images for Vanity Fair Tim Cook (left), shown here with Steve Jobs (center) and Apple chief marketer Phil Schiller (right), joined Apple in 1998 as Senior Vice President for Worldwide Operations, revolutionizing their inventory management and helping them improve profitability. David Paul Morris/Getty Images Jony Ive (left) and Steve Jobs (right) dreamed up many of Apple’s product designs together, including the 2001 iMac G4, which was inspired by a walk among the flowers in Jobs’s backyard in Palo Alto. Jobs told biographer Walter Isaacson that Ive was his “spiritual partner.”

Keeping Up With the Quants: Your Guide to Understanding and Using Analytics
by Thomas H. Davenport and Jinho Kim
Published 10 Jun 2013

An end-cap display is the most effective placement of our product in a retail store for lifting weekly sales. Our customers can be grouped into four distinct segments with regard to the products they buy. Our ability to raise prices on a class of consumer staple products without hurting demand is significantly lower during economic recessions. Our business units that have centralized inventory management facilities tend to maintain lower average days of inventory for their production processes. * * * There are thirty-seven numbers in a French/European roulette wheel: 1–36 and 0. When a wheel is spun once, the theoretical probability that each number will come out is equal to 1/37.

The Gig Economy: A Critical Introduction
by Jamie Woodcock and Mark Graham
Published 17 Jan 2020

Transport is an area that is the focus of substantial investment in automation technologies, and many of the sorts of jobs on microwork platforms have already been automated by some companies. With delivery work, some parts of the labour process have already been automated, through the use of GPS-assisted route planning and barcodes or radio-frequency identification (RFID) tagging for inventory management. The second is that in all of these cases, workers are contributing to datasets being used to train artificial replacements. The data generated by drivers contributes to the training sets for self-driving cars, while microwork allows for a much wider range of training data. Often workers will not be aware of the role they are playing, as the tasks are fractured and stripped of their meaning.

Learning Ansible 2 - Second Edition
by Fabio Alessandro Locati
Published 21 Nov 2016

The biggest features of Ansible Tower are as follows: • LDAP/AD integration: You can import (and give privileges to) users based on the result of LDAP/AD queries that Ansible Tower performs on your LDAP/AD server • Role-based access control: Limit the users to only run the playbooks they are authorized to run and/or target only a limited amount of hosts • REST API: All Ansible Tower capabilities are exposed via a REST API • Job scheduling: Ansible Tower allows us to schedule jobs (playbook execution) • Graphical inventory management: Ansible Tower manages the inventory in a more dynamic way than Ansible • Dashboard: Ansible Tower allows us to see the situation of all current and previous job executions • Logging: Ansible Tower logs all the results of every job execution to be able to go back and check if needed Although Red Hat has promised to make Ansible Tower open source soon, at the moment, it is not freely available and you need to pay depending on the number of nodes you want to manage.

Corporate Finance: Theory and Practice
by Pierre Vernimmen , Pascal Quiry , Maurizio Dallocchio , Yann le Fur and Antonio Salvi
Published 16 Oct 2017

Section 43.2 Corporate governance and financial theories Section 43.3 Value and corporate governance Chapter 44: Taking control of a company Section 44.1 The rise of mergers and acquisitions Section 44.2 Choosing a negotiating strategy Section 44.3 Taking over a listed company Chapter 45: Mergers and demergers Section 45.1 All-share deals Section 45.2 The mechanics of all-share transactions Section 45.3 Demergers and split-offs Chapter 46: Leveraged buyouts (LBOs) Section 46.1 LBO structures Section 46.2 The players Section 46.3 LBOs and financial theory Section 46.4 The LBO market: following the crisis, a gradual bounce-back Chapter 47: Bankruptcy and restructuring Section 47.1 Causes of bankruptcy Section 47.2 The different bankruptcy procedures Section 47.3 Bankruptcy and financial theory Section 47.4 Restructuring plans Part Two: Managing working capital, cash flows, financial risks and real estate Chapter 48: Managing working capital Section 48.1 A bit of common sense Section 48.2 Managing receivables Section 48.3 Managing trade payables Section 48.4 Inventory management Section 48.5 Conclusion Chapter 49: Cash management Section 49.1 The basics Section 49.2 Cash management Section 49.3 Cash management within a group Section 49.4 Investing cash balances Section 49.5 The changing role of the treasurer Chapter 50: Managing financial risks Section 50.1 Introduction to risk management Section 50.2 Measuring financial risks Section 50.3 Principles of financial risk management Section 50.4 Organised markets – OTC markets Chapter 51: Managing operational real estate Section 51.1 Methods for financing real estate Section 51.2 Criteria for choosing real-estate financing Section 51.3 Value creation and investor perception Section 51.4 An ideal way of organising real estate?

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Indeed, successful expansion often depends on the following two conditions: ensuring that the growth in working capital tracks the growth in sales rather than zooming ahead of it; creating a corporate culture that strives to contain working capital. If working capital grows unchecked, sooner or later it will lead to serious financial difficulties and compromise the company’s independence. Today, companies faced with slower growth in business manage working capital strictly through just-in-time inventory management, greater use of outsourcing, reorganisation of internal payment circuits, financial incentives for salespeople linked to customers’ payments, etc. (as we will see in Chapter 48). 2. Recession By analysing the working capital of a company facing a sudden drop in its sales, we can see that it reacts in stages.

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In the worst of cases, new orders will be triggered as the stocks in the system could appear to be abnormally low!; finally, disputes should be dealt with quickly as they will not result in any extension of the contractual payment period. Suppliers should not be paid late or in advance (except to get a discount), they should be paid on time. Section 48.4 Inventory management According to Walbert and Cabelli, the ability of a company to manage its inventories well is dependent on several parameters and on how well the company manages these: its ability to correctly forecast the level of activity in advance, which is highly dependent on the sector; its ability to carry out cross-analyses between product families and customer families in order to be able to work out suitable supplies and storage policies; its ability to reduce its supply periods; its ability to transform its stocks rapidly from raw materials into finished products, and then to sell them (called optimisation of the production process); its ability to monitor stock levels; its ability to obtain a service rate10 high enough to avoid stockouts.

97 Things Every Programmer Should Know
by Kevlin Henney
Published 5 Feb 2010

They seem to think you operate on a different plane, that solutions appear to you without analysis based on evidence. They think you are a guru. We expect such questions from those unfamiliar with software; to them, systems can seem almost magical. What worries me is seeing this in the software community. Similar questions arise in program design, such as "I'm building inventory management. Should I use optimistic locking?" Ironically, people asking the question are often better equipped to answer it than the question's recipient. The questioners presumably know the context, know the requirements, and can read about the advantages and disadvantages of different strategies. Yet they expect you to give an intelligent answer without context.

The Lights in the Tunnel
by Martin Ford
Published 28 May 2011

After all, technology is not just physical machines; it is also techniques, processes and distributed knowledge. The reality, however, is that the historical distinction between machines and intellectual capital is blurring. It is now very difficult to separate innovative processes from the advancing information technology that nearly always enables and underlies them. Improved inventory management systems and database marketing are examples of innovative techniques, but they rely heavily on computers. In fact, we can conceivably think of nearly any process or technique as “software”—and, therefore, part of a machine. If you still have trouble accepting this scenario, you might try asking yourself a couple of questions: (1) Is it possible for a machine to keep getting better forever without eventually becoming autonomous?

Side Hustle: From Idea to Income in 27 Days
by Chris Guillebeau
Published 18 Sep 2017

You can add a button or link to your website to accept funds through PayPal, or you can bill customers directly through the system. SHOPIFY. If you sell products with a fixed quantity (as opposed to a service or a product with unlimited quantity, like an e-book or app), the benefits of this system are the easy-to-use shopping cart and inventory management tool. Additionally, you can create a basic website right from the interface. Hundreds of thousands of people use Shopify, and the service focuses on serving individual sellers instead of big businesses. To get a free trial and see if it works for you, visit Shopify.com/​sidehustle. STRIPE.

Big Bucks: The Explosion of the Art Market in the 21st Century
by Georgina Adam
Published 14 Jun 2014

The top galleries are, today, very different from the operations of the twentieth century. While the personality of the dealer remains essential, they are also highly professional enterprises with forceful press officers – and most also hire outside public relations companies. They use state-of-the-art technology for invoicing, inventory management and so on. Monitors can track who is in the gallery, what works of art visitors look at first, which they look at longest. And staff behind the reception desks have mug-shots of leading collectors, artists, even critics, so that if one comes in, they can alert those higher up. A director will shortly amble by – quite by coincidence of course.

Human + Machine: Reimagining Work in the Age of AI
by Paul R. Daugherty and H. James Wilson
Published 15 Jan 2018

See Watson (IBM) “if-then” rules, 25 Illumeo, 142 image recognition, 66 incubators, 162 industries, redefining, 56–58 Inertia Switch, 23 inference systems, 64 information analysis, 10 information technology (IT) cybersecurity and, 56–58, 59 in process automation, 5 Init.ai, 121 innovation, 152 generative design and, 135–137 observation and, 69–72 See also experimentation; research and development (R&D) Institute for the Future, 187 institutional review boards (IRBs), 78 inSTREAM, 47–48 Intel AI Day, 188 intelligence, extended and embodied, 206 intelligent agents, 65 IntelligentX Brewing Company, 76 interaction, 107, 139 jobs with, 143–146 See also augmentation; missing middle interaction agents, 143–146 interaction modelers, 120 internet of things (IoT), 34, 36, 37 interrogation, intelligent, 12, 185, 193–195 intuition, 191–193 inventory management, 30–33 iPhone, 176 IPSoft, 55–56, 139, 164, 201 iRobot, 24 IT security, 56–58, 59 Järborg, Rasmus, 55 job creation, 11, 113–115, 208–211 in data supply chains, 179 education and training for, 132–133 ethics compliance and, 79 explainers, 122–126 in manufacturing, 20 in marketing and sales, 100–101 in sustaining, 126–132 in training, 100, 114–122 See also fusion skills job loss, 19, 20, 209 job satisfaction, 46–47 job searches, 198–199 John Radcliffe Hospital, 197 Johnson & Johnson, 82 judgment integration, 12, 191–193 Kaiser Permanente, 188 Kaplan, Jerry, 60 Kelton, Fraser, 97 Keshavan, Meghana, 82 Kik, 91, 97 Kindred AI, 200 Kiva Robots, 31 knowledge representation, 63–64 Koko, 97, 117–118 Kowalski, Jeff, 137 Kraft Phone Assistant, 91 Lambda Chair, 136–137 Lange, Danny, 43 Las Vegas Sands Corp., 76 Laws of Robotics, 128–129 leadership, 14–15, 153–181, 213 blended culture and, 166–174 data supply chains and, 174–179 in enterprise processes, 58–59 in manufacturing, 38 in marketing and sales, 100 in normalizing AI, 190–191 in R&D, 83 in reimagining processes, 154, 180–181 learning deep reinforcement, 21–22 distributed, 22 reinforcement, 62 in robotic arms, 24–26 semi-supervised, 62 sensors and, 24–26 supervised, 60 unsupervised, 61–62 See also machine-learning technologies Leefeldt, Ed, 99 Lee Hecht Harrison, 199 legal issues.

The People's Republic of Walmart: How the World's Biggest Corporations Are Laying the Foundation for Socialism
by Leigh Phillips and Michal Rozworski
Published 5 Mar 2019

According to Supply Chain Digest, that business-management periodical more engrossing than a Vice exposé on the furry-fetish web-porn habits of the leadership of ISIS, Walmart stocks products from more than seventy nations, operating some 11,000 stores in twenty-seven countries. TradeGecko, an inventory-management software firm, describes the Walmart system as “one of history’s greatest logistical and operational triumphs.” They’re not wrong. As a planned economy, it’s beating the Soviet Union at its height before stagnation set in. Yet if Mises and friends were right, then Walmart should not exist.

The Greatest Capitalist Who Ever Lived: Tom Watson Jr. And the Epic Story of How IBM Created the Digital Age
by Ralph Watson McElvenny and Marc Wortman
Published 14 Oct 2023

IBM’s computers and magnetic stripe data storage technology would provide the backbone for the credit card industry; networked computer telecommunications and time-sharing across enterprises would enable simultaneous operations allowing remote input and output from multiple terminals and eventually distributed sites, offices, and finally desktop workstations. Other inventions tied to IBM would transform supply-chain, wholesale, retail, and delivery businesses of all types, through optical scanners and barcodes that provided the basis for retail universal product code (UPC) scanning for real-time inventory management and tracking. The arrival of the relational database would allow queries, combination, and retrieval of stored data sets for business transactions, insights into operations, and identification of opportunities, from sales reports to bank transfers. Early advances in machine learning and artificial intelligence, too, would grow out of IBM relational database developments.

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IBM computer scientists also invented magnetic-stripe data-storage technology, enabling the credit card industry; networked computing and time-sharing across enterprises, which was seminal to intercontinental strategic defense and to airline reservation systems; and optical scanners, making barcodes practical for inventory management and retail UPC scanning. IBM work on relational database search and retrieval tools led to large-scale enterprise database-management systems and provided the original basis for machine learning/artificial intelligence, or AI, and many other technologies that helped make computers an integral part of all aspects of life.

How PowerPoint Makes You Stupid
by Franck Frommer
Published 6 Oct 2010

What was unknown at the time was that this invention would strike a severe blow against the “large systems” computing that had been established in companies since the 1960s: The first service businesses to become computerized were banks and insurance companies; in other sectors, the first uses were in accounting, payroll, and inventory management. This changed the physical conditions of work: in the 1960s, employees spent part of their time perforating cards and going over lists; then, in the 1970s and 1980s, terminals were installed, replaced by networked micro-computers in the 1990s. At each stage, the ergonomics were modified as well as the possibilities offered to the user.15 The advent of microcomputing in business had a considerable influence on the organization of work, particularly on the omnipotence of information systems.

Where Does It Hurt?: An Entrepreneur's Guide to Fixing Health Care
by Jonathan Bush and Stephen Baker
Published 14 May 2014

I think this disruption has to come from outside—and a good dose of it from fellow MDP members. But this doesn’t mean the entrepreneurs should start with hospitals. Sure, a lot of them might look at the inefficiencies in hospitals and see opportunities. No doubt there are jobs, maybe pharmacy or inventory management, that they could handle much better. All that’s needed, they might think, is a thirty-minute session to demo the technology for a hospital administrator or two. And then, just imagine the upside. If entrepreneurs can sell their apps to Partners, or to Mayo, they’ll have a breakthrough contract, legitimacy, a brand.

Swimming With Sharks: My Journey into the World of the Bankers
by Joris Luyendijk
Published 14 Sep 2015

Not only would this mean that we can no longer withdraw our money from banks but also that trade finance stops. As Cooper puts it, ‘This financial crisis came perilously close to causing a systemic failure of the global financial system. Had this occurred, global trade would have ceased to function within a very short period of time. Remember that this is the age of just-in-time inventory management,’ Cooper adds, meaning supermarkets have very small stocks. With impeccable understatement, Cooper concludes: ‘It is sobering to contemplate the consequences of interrupting food supplies to the world’s major cities for even a few days.’ These were the dominos that had come so close to falling down in 2008, and I had just witnessed first-hand what could be the next tile in that line.

The Captured Economy: How the Powerful Enrich Themselves, Slow Down Growth, and Increase Inequality
by Brink Lindsey
Published 12 Oct 2017

To begin with, there is no shortage of innovation in fields where patenting hasn’t been an option. Consider, for instance, all the organizational breakthroughs that have helped to power productivity growth since industrialization, including the multidivisional corporation, the R&D department, the department store, the chain store, franchising, statistical process control, just-in-time inventory management, and on and on. All these ideas were quickly and widely imitated, but that was no bar to their original introduction. Even in areas eligible for patent protection, many firms don’t seek patents and flourish all the same. The importance of open-source software to the success of the Internet is a spectacular case in point.

Subscribed: Why the Subscription Model Will Be Your Company's Future - and What to Do About It
by Tien Tzuo and Gabe Weisert
Published 4 Jun 2018

Walmart has 5,000 stores, more than 1.5 million employees, and serves more than 140 million shoppers a week. Nearly every American spent money at a Walmart last year. Those are pretty amazing statistics. This is a company with decades of institutional experience with supply chains, transport logistics, inventory management. It knows how to buy and sell products. Most of its customers shop for groceries and basics—very simple, repeat purchases. But what was the last thing you bought at Walmart? They certainly couldn’t tell you. To Walmart, you’re basically just a vehicle for dispensing inventory. Once you pass the cash register, you vanish off the map.

Total Recall: How the E-Memory Revolution Will Change Everything
by Gordon Bell and Jim Gemmell
Published 15 Feb 2009

See also biometric sensors improvised explosive devices (IEDs) In Search of Memory: The Emergence of a New Scientific Mind (Kandel) indexing inductive charging industrial revolution Infinite Memory Multifunction Machine (IM3) Information Age inheritance instant messaging and cloud computing and cyber twins and note taking and smartphones and total data collection institutional memory instruction manuals insurance insurgency Intel Intellectual Ventures interfaces International Technology Roadmap for Semiconductors Internet. See also World Wide Web and cloud computing and data backup services and gossip and higher learning and implementation of Total Recall and information availability and the Millennial Generation and social values and unified communications inventory management IOgear iPhone Iraq War iTunes J Jaimes, Alexandro Jim Gray Endowed Chair in Computer Systems Joe Bill Jones, William JPEG files. See also pictures and photographs K Kaiser Permanente Kandel, Eric keywords Kindle knowledge mining L La Femme Nikita (television) language, development of language acquisition laptops.

Makers
by Chris Anderson
Published 1 Oct 2012

Somebody has to do the manufacturing, handle the inventory, get the liability insurance, and run the customer support, and that takes money, a legal structure, and real day-to-day responsibilities. Thus, a company. So, in the new manufacturing model, you need a new kind of manufacturing company, too. At its core, it has to incorporate all the skills and learning of traditional manufacturing companies—tight quality control, efficient inventory management, and supply-chain management—so that it can compete with them on basic price and quality. But it also needs to incorporate many of the skills of Web companies in creating and harnessing a community around its products that allow it to design new goods faster, better, cheaper. In short, it must be like the best hardware companies and the best software companies.

Buy Then Build: How Acquisition Entrepreneurs Outsmart the Startup Game
by Walker Deibel
Published 19 Oct 2018

The company was selling a few million in revenue and had a handful of noteworthy, highly-respected, and well-known clients. 4 Through our analysis—although print management and centralized “brand control” was valuable to its customers—we decided that the real core competency of the business was in its inventory management and fulfillment capabilities, which provides its customers the benefits of lean supply chain management practices. It was clear that the product lines could be easily expanded. Indeed, one of the biggest clients came to the seller and asked if he could put other products important to their supply chain into the online ordering system.

Principles of Web API Design: Delivering Value with APIs and Microservices
by James Higginbotham
Published 20 Dec 2021

Teams will see the various challenges involved with designing APIs that are meant to support different audiences and support operations, commerce, and partner integration. It will also help teams explore the challenges involved with applying design techniques to existing APIs that already exist. JSON’s Bookstore must design a series of APIs that will support online commerce, order fulfillment, inventory management, and catalog management. The company will also need to support integration with partners and customers. Along the way, the API surface area will increase, requiring JSON’s Bookstore to find ways to manage and govern the APIs in a scalable way that doesn’t slow down its development velocity.

The Complacent Class: The Self-Defeating Quest for the American Dream
by Tyler Cowen
Published 27 Feb 2017

As productivity researchers John Fernald and Bing Wang put it: “Three out of the last four decades have seen business-sector productivity growth near 1½%.”18 Overall, the history of this variable suggests the following story: America had a productivity heyday from the early twentieth century through about 1973. But then American innovativeness slowed sharply. The early years of applying IT brought a major rebound, but that dwindled as some of the low-hanging fruit from computer use, such as basic inventory management practices and email, was exhausted. Since the early 2000s, America has settled back into what is essentially a low-innovation mode of existence, with the exception of a few areas, such as social media. And as you can see from the earlier chapters, the slowdown story doesn’t rely on just a single productivity number; rather, it is consistent with a broad array of data about many social and economic variables, many of them easier to measure than business productivity.

Extreme Teams: Why Pixar, Netflix, AirBnB, and Other Cutting-Edge Companies Succeed Where Most Fail
by Robert Bruce Shaw , James Foster and Brilliance Audio
Published 14 Oct 2017

He is an environmentalist who built a $750 million company.4 His disregard for common business practices has resulted in some missteps along with way—including a near-death experience for the company several decades ago.5 Chouinard admits that Patagonia made some classic blunders. The firm at one time had an unwieldy organizational structure, poor inventory management processes, and little or no training for its new managers. The firm also suffered, early in its history, with significant turnover at the senior levels—people, in Chouinard’s view, who didn’t fit the firm’s culture. Some of those who departed had a different view—suggesting that Chouinard was a difficult and divisive boss.

The Locavore's Dilemma
by Pierre Desrochers and Hiroko Shimizu
Published 29 May 2012

In the end, why are modern agricultural producers willing to purchase costly synthetic inputs, hormonal growth promoters, antibiotics, and genetically modified seeds when the methods agri-intellectuals prefer are either completely free (such as giving up on the use of these inputs and on equipment such as poultry housing) or seemingly much cheaper (such as feeding cattle entirely on pastureland and saving one’s seeds instead of relying on those marketed by specialized producers)? On the retail side, perhaps supermarkets and large chain stores displaced farmers’ markets because of their more convenient hours, better parking conditions, greater mastery of logistics and inventory management, higher quality products, lower prices, and superior record in terms of food safety. On the latter topic, couldn’t it be the case that the risk that large processing plants will spread pathogens over long distances is mitigated by the fact that they have better technologies to detect, control, and track such problems in the first place?

Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies
by Reid Hoffman and Chris Yeh
Published 14 Apr 2018

Despite—or perhaps because of—the growing dominance of bits, the power of software has also made it easier to scale up atom-based businesses as well. Amazon’s retail business is heavily based in atoms—just think of all those Amazon shipping boxes piled up in your recycling bin! Amazon originally outsourced its logistics to Ingram Book Company, but its heavy investment in inventory management systems and warehouses as it grew turned infrastructure limitations from a growth limiter to a growth factor. On the retail side, merchants pay Amazon to manage their inventories and logistics for them, while the massive computer systems that Amazon built to operate its retail business gave it the capabilities to launch its AWS business (which is a high-margin, bits-based business!).

The Socialist Manifesto: The Case for Radical Politics in an Era of Extreme Inequality
by Bhaskar Sunkara
Published 1 Feb 2019

It builds a new factory, purchasing top of the line equipment. The company hopes it can win an advantage over its two main rivals, Saab and Volvo, by maintaining a smaller workforce and capitalizing on existing brand recognition among car enthusiasts. Not one for physical labor, you apply for an inventory management position. You don’t earn much more than the assembly line workers, who are covered in the same industry-wide bargaining agreement. But you make 30 euro an hour, have plenty of vacation, and no longer need to listen to satanic mixtapes. It’s a good deal. Your first year, the firm isn’t profitable, but it produces a well-regarded Volvo S60 competitor, and there’s hope that the company’s market share will grow.

Busy
by Tony Crabbe
Published 7 Jul 2015

It was successful because of its values: it valued deep expertise and a passion for science. Chemistry was the heart and soul of the business, delivering innovation that, in turn, brought profits. In moving to a more directly profit-centric model, the business lost its vitality. The chemists weren’t fired up by spreadsheets, saving money and inventory management. The last ten years for ICI were spent scrambling for efficiencies and productivities as it increasingly relinquished its unique place in the market. This story should stand as a salutary reminder of the perils of trading the heart and soul of a business for a balance sheet. It should also set off warning bells for you and me.

Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith
by Sam Newman
Published 14 Nov 2019

It’s also very useful when the monolith is in effect a black-box system—such as third-party software or a SaaS service. Occasionally, you can extract an entire end-to-end slice of functionality in one piece, as we see in Figure 3-2. This simplifies the extraction greatly, aside from concerns around data, which we’ll look at later in this book. Figure 3-2. Straightforward end-to-end abstraction of Inventory Management functionality In order to perform a clean end-to-end extraction like this, you might be inclined to extract larger groups of functionality to simplify this process. This can result in a tricky balancing act—by extracting larger slices of functionality, you are taking on more work, but may simplify some of your integration challenges.

Hands-On RESTful API Design Patterns and Best Practices
by Harihara Subramanian
Published 31 Jan 2019

That is, different business capabilities are implemented through separate microservices running on different processes. For an e-commerce application, we can have microservices for various modules, such as the shopping cart, customer analytics, the payment gateway, warehousing, shipping, replenishment, inventory management, and email notifications. Web-scale applications are embracing the MSA in order to be business-friendly. For applications with frequently varying loads (where the number of users changes quickly and there can be sudden spikes in the number of messages with different data sizes), there is an insistence for mechanisms that innately support dynamic, horizontal, and real-time scalability.

The Pyramid Principle: Logic in Writing and Thinking
by Barbara Minto
Published 2 Jan 2010

In addition, because the central warehouse was frequently out of stock of some items, the outlying warehouses also ordered direct from suppliers, further increasing inventory cost. r--Ket; 1 lssrtes Based on our discussion, sevt•ral issues emerged that should be addressed since the answers vvill i1ffect improvement opportunities and, possibly~ future business strategy These issues are preliminary only, cmd we \Vould expt~ct others to emerge. ·1. Is the present inventory management system suitable for all elements of l -- - the business? VVe understand that a cmnputerized "IMPACT" type system is in use. \Ve are familiar vvith systems of this type, and find them quite useful in nonmanuhcturing, stocking businesses in which thousands of relatively stable stockkeeping units are processed.

What Would Google Do?
by Jeff Jarvis
Published 15 Feb 2009

Peter Osnos, another publishing visionary on a mission to save the business, founded the Caravan Project to enable publishers to sell books in any form: in their traditional format, via print-on-demand, digitally in full or by chapter, and in audio. “When a reader asks for a book, the seller’s answer should always be, ‘how do you want it?’” he wrote at The Century Foundation. Osnos told me that the fundamental problems for publishing are availability and inventory management. If he can drive 20 percent of book selling to on-demand and digital, he believes he will save so much in printing unsold copies that he will be able to afford the marketing needed to make the business model work. He read a quote from The New York Times on the day that Google introduced its new Chrome browser arguing that Google needed to control its own destiny.

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism
by Arun Sundararajan
Published 12 May 2016

Walmart claimed that these former employees had leaked proprietary information about Walmart’s famed supply chain management systems. The suit was settled in 1999, but it underscored the fact that Amazon wasn’t merely investing in product variety or search and discovery innovations like user reviews and recommendations. They were making massive investments into inventing an entirely new infrastructure for inventory management, warehousing, and delivery, one that was optimized for a retail world in which goods had to be moved not in bulk to outlets or stores, but one-by-one to individual consumers. Amazon’s current dominance of online retailing in the United States owes much to these early investments, and to the capabilities it has built to move physical goods faster and cheaper than any of its competitors.

Scarcity: The True Cost of Not Having Enough
by Sendhil Mullainathan
Published 3 Sep 2014

So Schoar procured a standard financial literacy training module, of the kind typically given to microentrepreneurs worldwide. Her reaction upon seeing the material: Wow, how tedious! (And she’s a finance professor at MIT.) The course was several weeks long and focused on traditional accounting techniques, teaching daily recordkeeping of cash and expenses, inventory management, accounts receivable and payable, and calculating profits and investment. In a world of unlimited bandwidth, all this would be worth knowing. But in the real world, Schoar believed that she could do better for her clients. She gathered together a group of the best local entrepreneurs to look at how they managed their finances.

No Ordinary Disruption: The Four Global Forces Breaking All the Trends
by Richard Dobbs and James Manyika
Published 12 May 2015

Free Mobile signed up more than 2.6 million new subscribers in less than three months in 2012 and captured 13 percent market share in one year with no above-the-line budget.57 Luxury retailer Burberry is synonymous with best-in-class multichannel customer experience; its flagship store at 121 Regent Street in London boasts the world’s tallest retail screen, real-life digital feeds, and RFID chips that are sewn into Burberry products. These tiny chips trigger bespoke content in front of RFID-enabled mirrors.58 Nordstrom, the luxury department store, first exploited the marginal cost advantages of digital for internal purposes, to develop shipping and inventory-management facilities. The company then turned its digital investments outward, building a strong e-commerce site, mobile-shopping apps, kiosks, and capabilities for managing customer relationships across channels. Find New Ways to Monetize Consumer Surplus There’s an interesting and perhaps counterintuitive implication to the rise of big data and increasingly cheap digital business tools.

How Music Got Free: The End of an Industry, the Turn of the Century, and the Patient Zero of Piracy
by Stephen Witt
Published 15 Jun 2015

For years, Glover had stood and watched as thousands of perfectly good compact discs were destroyed in the gears of the machine. And, over time, he came to realize that he was staring into a black hole in the Universal security regime. The grinder was efficient, but it was far too simple. The machine had no memory and generated no records. It existed outside of the plant’s digital inventory management process. If you were instructed to destroy 24 overstock discs and only 23 actually made it into the feed slot, no one in accounting would ever know. So what Glover could do was take off his surgical glove while holding an overstock disc on his way from the conveyor belt to the grinder.

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
by Erik Brynjolfsson and Andrew McAfee
Published 20 Jan 2014

One way to think of the value created is to imagine that the new product always existed, but only at such a high price that no one could buy it. Making it available is like lowering the price to a more reasonable level. There have even been substantial increases in the number of stock keeping units (SKUs) in most physical stores as computerized inventory management systems, supply chains, and manufacturing have become more efficient and flexible. For the overall economy, the official GDP numbers miss the value of new goods and services added to the tune of about 0.4 percent of additional growth each year, according to economist Robert Gordon.* Remember that productivity growth has been in the neighborhood of 2 percent per year for most of the past century, so contribution of new goods is not a trivial portion.

The Wealth of Humans: Work, Power, and Status in the Twenty-First Century
by Ryan Avent
Published 20 Sep 2016

They ordered the parts they needed to do the manufacturing in bulk and carried large inventories. And then they shipped the cars off to dealers to sit on lots for purchase. In the 1980s, this system began to change. Upstart manufacturers such as Toyota adopted lean production techniques, which emphasized close cooperation across all the firms on the supply chain and careful inventory management, as well as constant improvement to both the car designs and the production processes. As electronics shrank and grew more powerful, the operation of the car itself became far more sophisticated; information processing once done within the driver’s head was instead handled by on-board computers; variation and personalization took on increasing importance.

The Connected Company
by Dave Gray and Thomas Vander Wal
Published 2 Dec 2014

This means that when it’s time to scale up a particular service, a pod that has, for example, seven people, can reproduce itself by dividing into two pods, each of which can bring on new members with minimal growing pains. What Kinds of Companies have been Successful with a Podular Approach? Xerox, Procter and Gamble, AT&T, and many other companies have credited self-directed teams with having a marked impact on their operations, including improvements in customer service, manufacturing, inventory management, and other productivity gains. Let’s look at three highly effective podular systems: one old-school company, one new-school company, and one old-school industry that’s reinventing itself. 3M is Podular Although they are known for innovation, 3M was incorporated in 1902, making it more than a hundred years old.

Equal Is Unfair: America's Misguided Fight Against Income Inequality
by Don Watkins and Yaron Brook
Published 28 Mar 2016

(And, as she also shows, many of those who didn’t escape poverty were held back by their own choices.)39 One of the worst things we can do for people who want to advance out of low-paying jobs, Newman points out, is to demean those jobs as mindless or degrading. As she writes in her book No Shame in My Game, even though many low-paying workers employ talents similar to those used by their white-collar counterparts—“memory skills, inventory management, the ability to work with a diverse crowd of employees, and versatility in covering for fellow workers when the demand increases” among many other skills—such workers are “limited by the popular impression that the jobs they hold now are devoid of value.” Newman is particularly disturbed by the fact that “when journalists want to call upon an image that connotes a deadening, routinized, almost ‘skill-free’ job, they routinely invoke the fast-food burger flipper as the iconic example.

The End of College: Creating the Future of Learning and the University of Everywhere
by Kevin Carey
Published 3 Mar 2015

It happened because state laws mandate that you can’t teach in a public school without a bachelor’s degree, and union contracts say you can’t make the maximum possible salary without a master’s degree. Employers were also faced with another version of a familiar problem: how to sort through a lot of information with limited resources and limited time. Brassiere inventory management is a snap compared to figuring out human beings. As information technology destroyed jobs that involved simple and repetitive tasks, like painting car parts or shelving paper files, and globalization moved other low-skill jobs overseas, the American jobs that remained fell into several large categories.

The End of Accounting and the Path Forward for Investors and Managers (Wiley Finance)
by Feng Gu
Published 26 Jun 2016

In particular, economists recorded a shift in the mid-1980s toward stabilization of economic activity: It has been estimated that, since 1984, the variance (a statistical measure of volatility) of GDP growth has declined by an astounding 50 percent. The search for a full understanding of this phenomenon goes on, but stabilizing factors like improved inventory management by companies, better control of firms’ operations brought about by information technology, smarter government interventions in crises, and the increased use by companies of stabilizing (risk hedging) financial innovations are among the volatility-reducing factors already identified. And what about the substantial business disruptions caused by the 2007−2008 crisis, you ask?

The Investopedia Guide to Wall Speak: The Terms You Need to Know to Talk Like Cramer, Think Like Soros, and Buy Like Buffett
by Jack (edited By) Guinan
Published 27 Jul 2009

Investopedia explains Inventory Possessing a high amount of inventory for long periods is not usually good for a business because it carries inventory storage, obsolescence, and spoilage costs. However, possessing too little inventory is not good either, because the business runs the risk of not filling customers’ orders and losing potential sales and thus market share as well. Inventory management techniques such as a just-in-time inventory system can help minimize inventory costs because goods are created or received as inventory only when needed. Related Terms: • Accounts Payable—AP • Cash Conversion Cycle—CCC • Inventory Turnover • Accounts Receivable—AR • First In, First Out—FIFO Inventory Turnover What Does Inventory Turnover Mean?

Blood, Sweat, and Pixels: The Triumphant, Turbulent Stories Behind How Video Games Are Made
by Jason Schreier
Published 4 Sep 2017

Toward the middle of 2013, the Eternity team finished the vertical slice and shifted from preproduction to production, the phase in which they would build the bulk of the game. The artists had grown familiar with the tools and pipelines; Josh Sawyer and the other designers had laid out systems like spellcasting and crafting; and the programmers had finished up fundamental features like movement, combat, and inventory management. The level designers had built outlines and sketches for most of the areas. But the game was still very much behind schedule. The biggest problem was Project Eternity’s story, which was coming together far more slowly than anyone on the team had expected. Sawyer and Brennecke had entrusted the main narrative to Eric Fenstermaker, a writer who had been at Obsidian since 2005.

Netflixed: The Epic Battle for America's Eyeballs
by Gina Keating
Published 10 Oct 2012

They had initially hesitated to leave two steady jobs to work at the same start-up, but the chance to work together, and with Meyer, was too tempting. Besides, they were still in their twenties—the youngest team members—and like most programmers in Silicon Valley in those days, they were always fielding calls from employment recruiters. The push-pull of turning the marketing department’s concepts for the user interface, inventory management, shipping, and even the credit card application into intuitive and consumer-friendly software was so satisfying that the grueling hours of coding seemed like play. Marketing and technology waltzed together in a harmony that the young technologists had never before experienced. Meyer insisted on customizing Oracle programs to one day handle search and fulfillment operations for up to ten million users.

The Man Who Broke Capitalism: How Jack Welch Gutted the Heartland and Crushed the Soul of Corporate America—and How to Undo His Legacy
by David Gelles
Published 30 May 2022

Hoping to improve efficiency, he reduced the amount of inventory Home Depot held. Before long, customers were frustrated that items were out of stock and employees were embarrassed that their company wasn’t coming through. Nardelli also transformed what had been a convivial culture into a Darwinian one. Inventory management tools were in, while a homespun approach to customer service was out. And when Nardelli tried to strongarm suppliers into giving him better deals, as he had done successfully at GE, it backfired. Some key suppliers didn’t cave, and their products were removed from Home Depot shelves. “I don’t know what the hell happened to Bob,” Langone said.

Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success
by Sean Ellis and Morgan Brown
Published 24 Apr 2017

GOOGLE ANALYTICS DASHBOARD The metrics that appear in Google’s default dashboards aren’t necessarily the most important for your growth. The equations above may seem overly simplistic. Clearly many more factors go into making a business work, such as R&D investment, cost of materials, shipping expenses, inventory management, and more. But the stark simplicity of the growth equation is the point. The sheer volume of data that is now available about customer behavior, even using the most basic analytics program, is daunting, with screen after screen of extraordinary detail. Google Analytics, for example, provides hundreds of charts and data points, which, while robust, can create confusion if it isn’t used in service of tracking the most important metrics specifically for your growth.

Early Retirement Extreme
by Jacob Lund Fisker
Published 30 Sep 2010

Given the limitations of human intelligence and lifespan, specialization is the only way to rapidly produce sophisticated products. In that sense, the complex skills of building a car have been transferred from the master craftsman up to the factory system, which has gotten very complex, with computer-controlled assembly lines and inventory management. Conversely, the system tries to divide labor into as narrow specializations as possible to cut costs. Using again the example of manufacturing a car, specialization can be narrowed to the point of replacing people with robots that weld a single piece of metal. The cost of specialization It's obviously more expensive, both in time and money, for Person A and Person B to gain the required amount of knowledge in both fields X and Y than it is if A were to concentrate on X while B concentrated on Y.

When Gravity Fails
by George Alec Effinger
Published 1 Jan 1987

I went to Laila because even though I wasn’t wired, she let me “borrow” any moddy or daddy she had in stock, by plugging it into herself. If I needed to do a little research, I went to Laila and hoped that she didn’t distort what I had to learn in any lethal way. This afternoon she was being herself, with only a bookkeeping add-on and an inventory-management add-on plugged in. It was that time of the year again; how the months fly when you take a lot of drugs. “Laila,” I said. She was so much like the old hag in Snow White that you couldn’t think of more to say to her. Laila was one person with whom you didn’t make small talk, whatever you wanted from her.

Better, Stronger, Faster: The Myth of American Decline . . . And the Rise of a New Economy
by Daniel Gross
Published 7 May 2012

A Thread Social Poppy Sweetheart dress, retail $365, rents for $50 (perfect for that spring tea). Accessorize with Crislu Crystal Tear earrings (retail $96, rent for $20). Like so many other online businesses, it has tapped into the highly developed and integrated logistics, customer service, shipping, inventory management, and payments systems that serve as a competitive advantage for all U.S. companies. In business for less than two years, Rent the Runway has raised $31 million in venture capital, has attracted 1 million customers, and is turning a profit. All these models involve more sharing than American consumers are typically accustomed to.

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines
by Thomas H. Davenport and Julia Kirby
Published 23 May 2016

On top of their basic wage, they cost their employers a third again more in payroll taxes, paid time off, health insurance, 401(k) contributions, and other perks. Think that’s all? Ask any facilities manager. Humans need ergonomic workspaces, heat, and light. Plumbing. All this is expensive, but it gets uglier. Ask any corporate counsel if humans like to bring lawsuits. Ask any security officer if embezzlement happens. Ask any inventory managers if they know about shrinkage. Ask any human resource executive what percentage of employees are engaged in their work (the average is 13 percent in the U.S.). But the trouble with human workers is a bigger deal than even that. As we’ll discuss in Chapter 2, technologies get smarter and cheaper all the time, but humans as a group don’t.

Sam Walton: Made in America
by Sam Walton and John Huey
Published 1 Jan 1992

Fortunately, he hired Don Soderquist from Ben Franklin around that time, and Don came in as a big supporter of what we were trying to do. He believed in mechanized distribution all the way, and he eventually took over distribution from me in 1980. He went on to do a great job expanding it, helping introduce a lot of innovation, including a badly needed new inventory management system. "Fortunately, we turned Searcy around and made it work because it saved our neck after we took on all those Kuhn's stores. We had to figure out how to supply them, and our arrangement with a third-party distributor turned into a nightmare. So we built an addition at Searcy to service them, and it solved the problem.

The Launch Pad: Inside Y Combinator, Silicon Valley's Most Exclusive School for Startups
by Randall Stross
Published 4 Sep 2013

Then Patrick’s younger brother John, who still had two years of high school to finish, also joined Auctomatic, quickly learning how to code on the job. Y Combinator’s motto was “Make Something People Want,” and the four Auctomatic cofounders did so. EBay’s power sellers were quite taken with Auctomatic’s inventory management tool, which was free. It supported eBay’s international sites that seemed obscure to Auctomatic’s large competitors and found greatest acceptance among eBay sellers who were outside of the United States.17 As it added users, Auctomatic caught the attention of prospective acquirers. Less than a year after completing YC, Auctomatic, then consisting of five people who lived in a two-bedroom apartment to save on rent, was presented with an acquisition offer by a Canadian company, Live Current Media, based in Vancouver.

WEconomy: You Can Find Meaning, Make a Living, and Change the World
by Craig Kielburger , Holly Branson , Marc Kielburger , Sir Richard Branson and Sheryl Sandberg
Published 7 Mar 2018

Over the next several months, teams from our three organizations put their heads together to come up with a campaign that would infuse Unilever products, sold at Walgreens, with a social value proposition that included Track Your Impact. The campaign would involve three of Unilever's flagship products: its TRESemmé, Suave, and Caress brands of shampoos and body washes. Andrea Farris, VP of Inventory Management and Supply Chain at Walgreens, reflected on the process: “Those brands aligned with the goal we were trying to achieve: while you're taking care of yourself with these products, you can also do good.” It was a natural progression to choose clean water as the social impact these products would deliver, since personal care products are often used with and linked to water.

When Gravity Fails
by George Alec Effinger
Published 1 Apr 2014

I went to Laila because even though I wasn’t wired, she let me “borrow” any moddy or daddy she had in stock, by plugging it into herself. If I needed to do a little research, I went to Laila and hoped that she didn’t distort what I had to learn in any lethal way. This afternoon she was being herself, with only a bookkeeping add-on and an inventory-management add-on plugged in. It was that time of the year again; how the months fly when you take a lot of drugs. “Laila,” I said. She was so much like the old hag in Snow White that you couldn’t think of more to say to her. Laila was one person with whom you didn’t make small talk, whatever you wanted from her.

Amazon: How the World’s Most Relentless Retailer Will Continue to Revolutionize Commerce
by Natalie Berg and Miya Knights
Published 28 Jan 2019

According to global consulting firm AlixPartners, these include: shipping and handling charges: free and/or fast shipping and packaging costs; costs associated with increased returns and restocking, reverse logistics, and lost margin on SKUs returned to a channel that was not intended to sell it; corporate headcount growth to support e-commerce divisions (including merchandising, planning, marketing, content creation, web development and IT, to name a few); balancing additional online marketing expenses with traditional expenses; incremental distribution and warehousing costs associated with piece picking; deleveraged store base and diluted store labour; incremental labour and technology expenses associated with omnichannel capabilities (ship from store, buy online, pick up in store, order from store, etc). complications associated with inventory management – deciding to share or not to share online and stores’ inventory and the costs associated with either decision.24 How do these costs stack up against those incurred by a bricks and mortar retailer? Take clothing, for example. According to AlixPartners, a typical $100 clothing purchase made by a shopper in a bricks and mortar outlet comes with a cost of goods sold of about $40.

Practical Doomsday: A User's Guide to the End of the World
by Michal Zalewski
Published 11 Jan 2022

Sloppy home canning is sometimes implicated in deadly botulism cases, but the condition is far less common than believed. Fewer than 20 food-borne cases are reported in the United States in a typical year.5 Low-moisture, shelf-stable foods that are stored properly are very unlikely to cause issues, and as with bottled water, the dates printed on the packaging exist more for inventory management and quality assurance purposes than as a sign of mortal peril awaiting those foolish enough to take a bite a few days too late. Old crackers might still taste stale, of course, but that’s caused by the oxidation of fats in contact with ambient air, as well as the loss of volatile substances that account for the flavor of freshly baked goods.

The Stolen Year
by Anya Kamenetz
Published 23 Aug 2022

I also did the grocery shopping and meal planning and most of the cooking. My husband picked up relaxing, fully optional household tasks during the pandemic, perfecting his sourdough bread and kombucha. I got dinner on the table night after night, subscribed to several new grocery delivery services, and sweated over inventory management of our new stockpiles of marinara sauce and dried beans. Once I had a full-on breakdown because we were out of dark green vegetables and running to the grocery store for a single item seemed at the time like an out-of-bounds risk. MOMS WORRIED MORE ABOUT COVID ITSELF As my kale freak-out illustrates, the fact that this was a public health crisis hit moms especially hard.

Cheap: The High Cost of Discount Culture
by Ellen Ruppel Shell
Published 2 Jul 2009

“Old Man,” high/low pricing Hitchcock, Alfred H & M home construction Home Depot Home Shopping Network Homo economicus economic model hotel industry Hounshell, David Household Registration Law (China) Hu Jindou Hull, Brent Humphrey-Hawkins Act Humpty Dumpty hyperbolic time discounting IKEA advertising by alliances with not-for-profits bookcase catalog designing to price de-skilling of labor flat packing forestry industry and number and location of stores suppliers to illusion of objectivity imports Chinese (See China) Japanese and Asian, in 1960s, markdowns of shrimp income declines in real income, early 2000s, post-World War II boom years income taxes, under Eisenhower and Kennedy India inelastic goods and services inflation of 1970s, CPI, in 2007-2008, Feds targeting of employment to fight during World War II, Ingka Holding innovation In Search of Excellence (Peters) instant rebates insula interchangeable parts International Herald Tribune inventory management iPhone iPod Ireland Irish potato famine “Is This the Worlds Cheapest Dress . . .” (Wilson) J. C. Penney Japanese imports John Wanamaker & Co. Jones, Lee Jonze, Spike Jordan, Julie Journal of Economic Behavior and Organization Journal of the Academy of Marketing Science just-in-time distribution K.

European Founders at Work
by Pedro Gairifo Santos
Published 7 Nov 2011

The interesting thing about what they were doing, they'd spent a lot of time and energy actually building software to automate the picking of the DVD on the back-end logistic side of things. Obviously, what was interesting and challenging about a business like this was it wasn't just the front end of a web site. You have to think about all of the back-end systems in terms of purchasing, inventory management, logistics, customer care, CRM, etc. I looked at all of this stuff. Originally my view on the market was, “Why don't we find a team to back?” This was my father and I, because we had been doing seed investing together for a couple of years through something called The Accelerator Group, TAG.

The Docks
by Bill Sharpsteen
Published 5 Jan 2011

How can he get people to experiment a little more and pick up a bottle of shiraz? Plus, the vineyards may have their own ideas, pushing one varietal over another because the vintage is a good one or they have surplus stock. More important, decisions about what wine to order and how much aren’t entirely a function of pre-orders or even an inventory management system that determines what to buy based on previous sales or demand, as if wine were soap or dish towels. It’s all about public taste and what the wine drinkers believe will make for a good glass. For Wilkinson, selling focuses on educating wine drinkers more than anything else. Although the United States imports about five times as much wine as it exports, making it the world’s third largest wine importer, it is nevertheless true that about two out of every three wine bottles sold in the United States come from California.

The Mathematics of Banking and Finance
by Dennis W. Cox and Michael A. A. Cox
Published 30 Apr 2006

r Demand is uniform over time. r The lead-time for new deliveries is zero. r Inventory is replenished when stock level is exactly zero. r The entire order is received in one delivery. r All costs are fixed over time. r There is always sufficient storage space for the deliveries. Clearly efficient inventory management will both save money and reduce the capital that is tied up by the business within inventory values. In practice, computer software is normally used to produce the graphs. However, the economic order quantity model is only a simple model and should always be used with care since in practice the assumptions are likely to be rather brave.

The Elusive Quest for Growth: Economists' Adventures and Misadventures in the Tropics
by William R. Easterly
Published 1 Aug 2002

. ~ And it’s not just high tech that has made such spectacular leaps. Wheat yields doubled between 1970 and 1994; corn and rice yields also soared, by 70 and 50 percent, respectively. Asian cereal yields have done even better, tripling over the past four decade^.^ Industry has become more efficient. New technologies like just-intime inventory management and numerically controlled machines have emerged. Health advances have been spectacular. To take one example, the treatment of mental illnesses like schizophrenia and depression has leaped with the discovery of new drugs like Risperdal and Prozac, bringing relief to millions of sufferers. The list could go on and on.

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems
by Irene Aldridge
Published 1 Dec 2009

For example, the dealers may provide lower spreads on large block orders in an effort to gather information and use it in their own proprietary trades. Mende, Menkhoff, and Osler (2006), however, emphasize that the majority of price variations in response to customer orders occurs through dealer inventory management. When the dealer transacts with an informed customer, the dealer immediately needs to diversify the risk of ending up on the adverse side of the transaction. For example, if a dealer receives a buy order from an informed customer, there is a high probability that the market price is about to rise; still, the dealer has just sold his inventory to the customer.

A Pelican Introduction Economics: A User's Guide
by Ha-Joon Chang
Published 26 May 2014

Fast food restaurants, such as McDonald’s, use ‘factory’ techniques, turning cooking into an assembly job. Some even deliver food on a conveyor belt, as in kaiten-zushi restaurants (for people living in Britain, that’s Yo! Sushi). Large retail chains – be they supermarkets, clothes shop chains or online retailers – apply modern inventory management techniques developed in the manufacturing sector. Even in the agricultural sector, productivity has been raised in some countries, such as the Netherlands (which is the third-largest exporter of agriculture in the world, after the US and France), through the application of manufacturing-style organizational knowledge, such as computer-controlled feeding.

Zero to Sold: How to Start, Run, and Sell a Bootstrapped Business
by Arvid Kahl
Published 24 Jun 2020

If the workflow requires interactions with cloud services, you will find that most of them provide easily used and well-documented APIs. Input Integrations Find out the shape of your customers’ data at the outset of their problem. Let's say your audience is plumbers who need help requisitioning new inventory of their pipefitting supplies. Do they already have an inventory management system that has an API? Are they maybe using an Excel sheet or a Google spreadsheet? Do they have such a system at all, or do they "go and check" regularly? Whatever it is, you will need to allow your customers to use the system they already have in place. Forcing them to adopt another system just because your product only works with that is a surefire way to build a tool that your prospective customers won't even try.

That Will Never Work: The Birth of Netflix and the Amazing Life of an Idea
by Marc Randolph
Published 16 Sep 2019

I’d been so confident about it that I’d run pre-movie advertisements—HELP WANTED—in the Scotts Valley movie theater. But I’d made a deep miscalculation. I had assumed that we would need a lot of “front-end” engineers—people with the skills to build web pages designed for e-commerce. But it turns out that what we really need is help with “back-end” problems—processes having to do with order processing, inventory management, analytics, and financial transactions. And if you want engineers for that kind of work, no amount of pre-movie advertising in Scotts Valley will do the trick. Most of the good back-end engineers live near San Francisco, and despite Eric’s reputation (and my powers of persuasion), it is virtually impossible to convince someone to drive 75 miles each way to work.

Superminds: The Surprising Power of People and Computers Thinking Together
by Thomas W. Malone
Published 14 May 2018

Then companies led by men with names like Daimler, Benz, Ford, and Chrysler continued to refine automobiles, adding and improving new technologies for functions like steering and braking.2 By the early 20th century, there were hundreds of small automobile companies, each of which produced only a few handmade cars.3 In the same period, Ford Motor Company developed the assembly line and used it to produce the Model T in very large quantities.4 Soon other car companies adopted these mass-production techniques and pioneered even more organizational innovations themselves. For instance, General Motors pioneered multidivisional hierarchies, and Toyota pioneered just-in-time inventory management. The auto industry also adapted to many kinds of changes in its environment. When the world was at war, automakers produced vehicles for armies. When the world was at peace, they produced more cars for civilians. When gasoline prices rose in the late 1970s, the industry produced more fuel-efficient vehicles.

The Great Reversal: How America Gave Up on Free Markets
by Thomas Philippon
Published 29 Oct 2019

Through its vendor-managed inventory system, manufacturers are responsible for managing their own inventory in Walmart warehouses. Vendors can directly monitor the inventory of their goods in Walmart stores and send additional items when the stocks are low in a particular store. This technology lowers the cost of inventory management, and the efficiency gains are passed on to consumers in the form of lower prices. Economists Ali Hortaçsu and Chad Syverson argue in a 2015 paper that superstores and e-commerce have increased productivity in the retail industry. The growth of Walmart provides us with an example of efficient concentration.

How I Built This: The Unexpected Paths to Success From the World's Most Inspiring Entrepreneurs
by Guy Raz
Published 14 Sep 2020

Those first couple years, they did most everything themselves: perfecting their formula, guiding the design and manufacture of the bottles, printing Eric’s personal cell phone number on the bottle as the customer service number,* doing in-store demos to get customers (Eric even wore a lab coat), pitching investors like the Sand Hill Road firms, calling on retail accounts like Mollie Stone’s Markets. They even handled inventory management. Every day, as they expanded into more Mollie Stone’s and then into additional boutique groceries, Adam and Eric would take turns driving around to each store to check inventory levels and restock the shelves as necessary. They called it their paper route. And the subsequent costs attendant to all these tasks, if money from friends and family wouldn’t cover it, Adam and Eric would just put on their credit cards.

Why Startups Fail: A New Roadmap for Entrepreneurial Success
by Tom Eisenmann
Published 29 Mar 2021

Finally, they can invest more time and effort into acquiring some specific industry knowledge themselves, while being aware that mastery can take years. It would certainly take that long for Quincy’s founders to master the process of designing and manufacturing apparel. But if they’d spent more time researching the challenges of garment manufacturing and inventory management before launching, they might at least have learned enough to target their recruiting efforts more precisely. In her postmortem analysis, Nelson speculated that perhaps she and Wallace had left their consulting jobs prematurely. In retrospect, she realized that they should have continued to evaluate their concept while still employed full-time.

Understanding Sponsored Search: Core Elements of Keyword Advertising
by Jim Jansen
Published 25 Jul 2011

Yield: the percentage of clicks versus impressions on an ad within a specific page. Also called ad click rate (Source: IAB) (see Chapter 6 BAM!). Yield management: yield and revenue management is the process of understanding, anticipating, and influencing advertiser and consumer behavior to maximize profits through better selling, pricing, packaging, and inventory management while delivering value to advertisers and site users (Source: IAB) (see Chapter 6 BAM!). Zipf’s principle of least effort: an information-seeking client will tend to use the most convenient search method (see Chapter 3 keywords). 272 Glossary References [1] Johnson, S. 1755. “Johnson, Preface to the Dictionary.”

Database Design and Relational Theory
by C.J. Date
Published 19 Apr 2012

The consequences of permitting more than one primary key ... for a single base relvar [would be] disastrous. (I’ve taken the liberty of replacing the term relation by the term relvar twice in this extract.) And he goes on to give an example involving employees with “several distinct responsibilities”—project management, department management, inventory management, etc.—and then he says: Comparing for equality of identifiers ... is intended to establish that one and the same employee is involved ... This objective is dealt a severe blow if the types of identifiers used for employees can be different depending on which pair of employee-identifying [attributes] is selected for the comparison.

The Everything Store: Jeff Bezos and the Age of Amazon
by Brad Stone
Published 14 Oct 2013

Bezos built the first two desks out of sixty-dollar blond-wood doors from Home Depot, an endeavor that later carried almost biblical significance at Amazon, like Noah building the ark. In late September, Bezos drove down to Portland, Oregon, to take a four-day course on bookselling sponsored by the American Booksellers Association, a trade organization for independent bookstores. The seminar covered such topics as “Selecting Opening Inventory” and “Inventory Management.”1 At the same time, Kaphan started looking for computers and databases and learning how to code a website—in those days, everything on the Internet had to be custom built. It was all done on a threadbare budget. At first Bezos backed the company himself with $10,000 in cash, and over the next sixteen months, he would finance the startup with an additional $84,000 in interest-free loans, according to public documents.

The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory
by Kariappa Bheemaiah
Published 26 Feb 2017

Today, the movement of goods across borders is carried out through supply chain management and trade finance. Supply chain deals with the processes that document the flow of goods from producer to consumer. It encompasses a wide range of procedures and structures that govern manufacturing, inventory management, and quality control. This involves a number of intermediaries and the transactions between them have to be documented to ensure the integrity of the trade process. The key word to remember is documentation. Today’s trade transaction and associated processes involves the transfers of records such as purchase orders, invoices, bills of lading, customs documentation, certificates of authenticity, etc.

The Secret Life of Groceries: The Dark Miracle of the American Supermarket
by Benjamin Lorr
Published 14 Jun 2020

See also audits insurance, 183 health insurance, 183, 270 truck drivers and, 88–89, 90, 91 integrity, vendors of, 189–92 International Food Congress, “American Way exhibit,” 34 International Labour Organization, 248–49 international market, 148 Interstate Commerce Commission, 96 inventory, managing, 178 investment per employee, 49 IOM, 313–14n Jack in the Box, E. coli outbreak at, 190, 191 JANA Partners, 259 Japan, automobile industry in, 174–77, 178 Jarrell, Randall, 75 J.B. Hunt, 100, 101, 295n job security, Whole Foods and, 183 Johnson, Gary, 46–47n10 journalism, 151, 249–54, 253–54, 268, 270–71, 313–14n.

Portfolio Design: A Modern Approach to Asset Allocation
by R. Marston
Published 29 Mar 2011

We know that (a) bonds are supreme during market downturns and (b) stocks are supreme in upturns. So all we have to do is shift portfolios to bonds in time for recessions (or perhaps prior to the start of the recessions). Then we have to shift portfolios back to stocks just in time. It’s plausible that Japanese automakers can run their production lines successfully with “just-in-time” inventory management. But it may be a trifle more difficult for investors to do the same. So what should investors do in a downturn? The answer is that they should sit tight. David Swensen of the Yale endowment perhaps said it most clearly. When asked in January 2009 whether poor investment performance in 2008 would induce him to tinker with his asset allocation, he replied “I don’t think it makes sense . . . to structure a portfolio to perform well in a period of financial crisis.

Machine, Platform, Crowd: Harnessing Our Digital Future
by Andrew McAfee and Erik Brynjolfsson
Published 26 Jun 2017

Rent the Runway thus practices a type of revenue management that differs from ClassPass’s approach—one aimed at preserving the value of durable inventory as long as possible by presenting it to the people around the country with the highest willingness to pay, as determined by the company’s algorithms. By the spring of 2016, Rent the Runway felt confident enough in its revenue and inventory management expertise to launch its own version of an unlimited service, one that treated articles of clothing much the way Netflix treated physical DVDs. For a flat $139 per month, a Rent the Runway member could keep three items with her at all times. As soon as she returned one, the next one on her wish list would be sent to her.

Dreaming in Code: Two Dozen Programmers, Three Years, 4,732 Bugs, and One Quest for Transcendent Software
by Scott Rosenberg
Published 2 Jan 2006

The inflammatory title of Carr’s article raised predictable hackles, but his argument made eminent sense as long as you viewed IT as a fixed set of functions and capabilities. IT “doesn’t matter” as long as you know in advance that the things you expect software to accomplish for a business—accounting, workflow automation, inventory management, you name it—are not going to change and that your competition is using software to accomplish the same set of things. But of all the capital goods in which businesses invest large sums, software is uniquely mutable. The gigantic software packages for “customer relationship management” and “enterprise resource planning” that occupy the lives of the CTOs and CIOs of big corporations may be cumbersome and expensive.

Cocaine Nation: How the White Trade Took Over the World
by Thomas Feiling
Published 20 Jul 2010

Even the local DEA office in Detroit admitted that ‘kids in the ghetto who couldn’t get jobs or couldn’t get to jobs because they didn’t have transportation out to the suburbs could rock up cocaine and sell it on any street corner’.26 On the one hand, the Chambers brothers were the lead characters in an archetypal American story of entrepreneurial success. They had identified a niche market, studied and overcome barriers to entry, bought wholesale, tracked inventory, managed cash flow, analysed risk and expanded aggressively until they cornered the market. Plenty of those involved in the upper echelons of the cocaine business, such as Lance in South Jamaica, Queens, craved the respect granted to their counterparts in the legal economy and regarded themselves as successful businessmen whose stock-in-trade happened to be illegal.

Trading at the Speed of Light: How Ultrafast Algorithms Are Transforming Financial Markets
by Donald MacKenzie
Published 24 May 2021

So if you wanted to take, you had to create some cockamamie series of events that would cause you to say that the price is worth five cents more [than the current market price], which will cause the strategy to maybe take, you hoped. (Interviewee AF) Even if the valuation formula input by a trader caused the firm’s system to take, its inventory-management function would often lead it to eliminate the resultant trading position too quickly, before it became profitable: [I]f you’re trying to do something different than the system was conceived and built [for] in the first place, you spend an awful lot of time and energy trying to stop it from doing what it wants to do.

When Einstein Walked With Gödel: Excursions to the Edge of Thought
by Jim Holt
Published 14 May 2018

“If a government minister asked me that question,” Harris replies, “I could claim that mathematicians, like other academics, are needed in the universities to teach a specific population of students the skills needed for the development of a technological society and to keep a somewhat broader population of students occupied with courses that serve to crush the dreams of superfluous applicants to particularly desirable professions (as freshman calculus used to be a formal requirement to enter medical school in the United States).” Although physicians don’t really need calculus, Harris at least concedes that engineers, economists, and inventory managers couldn’t get by without a fair amount of math, even if it is trivial math by his lights. Finally, there is the presumed value of mathematical truth. Since the ancient Greeks, mathematics has been taken as a paradigm of knowledge: certain, timeless, necessary. But knowledge of what? Do the truths discovered by mathematics describe an eternal and otherworldly realm of objects—perfect circles and so forth—that exist quite independently of the mathematicians who contemplate them?

The Rise and Fall of American Growth: The U.S. Standard of Living Since the Civil War (The Princeton Economic History of the Western World)
by Robert J. Gordon
Published 12 Jan 2016

A part of the great transition that was achieved in the 1980s and 1990s was the catalog revolution. Even before the web became pervasive in the late 1990s, libraries had already converted from wooden boxes of paper card catalogs to electronic catalogs that doubled not only as search tools but as inventory managers, indicating for every search result whether the book or periodical was on the shelf. The parts departments at automobile dealers made a transition at the same time to electronic catalogs from enormous binders into which multiple replacement pages had to be inserted every day. Hardware stores, book stores, garden nurseries, and, indeed, any retail store selling a large number of varieties of products shifted to electronic catalogs over proprietary computer networks even before the web allowed direct consumer contact with each merchant’s catalog.

…

In the early years of credit cards in the 1970s and 1980s, checkout clerks had to make voice phone calls for authorization, then there was a transition to terminals that would dial the authorization phone number, and now the authorization arrives within a few seconds. The big-box retailers brought with them many other aspects of the productivity revolution. Walmart and others transformed supply chains, wholesale distribution, inventory management, pricing, and product selection, but that productivity-enhancing shift away from traditional small-scale retailing is largely over. The retail productivity revolution is high on the list of the many accomplishments of IR #3 that are largely completed and will be difficult to surpass in the next several decades.

The Personal MBA: A World-Class Business Education in a Single Volume
by Josh Kaufman
Published 2 Feb 2011

—MICHAEL LEBOEUF, BUSINESS PROFESSOR AND AUTHOR OF HOW TO WIN CUSTOMERS AND KEEP THEM FOR LIFE Every successful business actually delivers what it promises to its customers. There’s a term for a person who takes other people’s money without delivering equivalent value: “scam artist.” Value Delivery involves everything necessary to ensure that every paying customer is a happy customer: order processing, inventory management, delivery/fulfillment, troubleshooting, customer support, etc. Without Value Delivery, you don’t have a business. The best businesses in the world deliver the value they’ve promised to their customers in a way that surpasses the customers’ expectations. Customers like to get the benefits of their purchases quickly, reliably, and consistently.

Endurance: A Year in Space, a Lifetime of Discovery
by Scott Kelly and Margaret Lazarus Dean
Published 14 Aug 2017

It’s close to impossible to find anything even with the lights on, and out of courtesy Kjell has left them off. “To tell you the truth, I’m looking for more puke bags,” Kjell says. “I’m out.” “There’s got to be some more here somewhere,” I say. I look in the few places that seem most likely, then search in the computer inventory management system. I ask Houston where I should be looking. After a minute, they say we don’t have a stash of puke bags on board. We don’t include them among supplies sent up to the station because the Russians used to bring them on the Soyuz. “We’ll improvise something,” I assure Kjell. As with everything else up here, vomit has a tendency to go everywhere, so there has to be a way for the bag to absorb it and hold it in place.

Inside the House of Money: Top Hedge Fund Traders on Profiting in a Global Market
by Steven Drobny
Published 31 Mar 2006

As a consultant, you tend to roll in, offer your advice, and leave. I actually wanted to implement some ideas and see if there was any value. So I took the job and was there for about two years helping to change shop floor operations.While there, I also studied and took the exams for Certification in Production Inventory Management, which is the manufacturing equivalent of the CFA (Chartered Financial Analyst) or CPA (Certified Public Accountant) exams. It was a great experience dealing with a private, traditional, old company and managing people much older than me in that sort of environment. It was also interesting to me that the company realized the purchase price of something but not the cost.

Lean Analytics: Use Data to Build a Better Startup Faster
by Alistair Croll and Benjamin Yoskovitz
Published 1 Mar 2013

These efficiencies turn into a competitive advantage, because they let you sell to consumers who are more interested in faster, better-quality service than the cheapest price. Stock Availability “When items are out of stock, sales go down,” says Jason Billingsley. “Of course that’s obvious, but few e-commerce vendors do anything about it.” Improving your inventory management can make a big difference to your bottom line. Jason recommends lowering out-of-stock items on product list or category pages, effectively hiding them from consumers. You can also hide these items from searches, or again, make sure they appear lower in the search results. It’s also interesting to analyze inventory versus sales.

The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order
by Paul Vigna and Michael J. Casey
Published 27 Jan 2015

The Arkansas-based retailer famously developed a sophisticated network with which to tie all of its suppliers worldwide into a single, integrated database for managing the goods and services flowing in and out of Walmart’s warehouses. Along with big improvements in shipping logistics, this allowed the company to optimize its just-in-time inventory management, which drastically cut its costs. Walmart parlayed those cost savings into the cheapest prices anywhere in the United States, which turned it into the iconic and, to some, infamous behemoth that now dominates American suburbia. Just as important, its high-tech network had a feedback effect on suppliers, contributing to the concentration of manufacturing in hubs such as China’s Pearl River Delta.

The Future of Ideas: The Fate of the Commons in a Connected World
by Lawrence Lessig
Published 14 Jul 2001

See also “Online Entertainment: Coming Soon to a Digital Device Near You: Hearing Before the Senate Comm. on the Judiciary,” 107th Cong. (2001) (statement of Hilary Rosen, president and CEO, Recording Industry Association of America), available at http://judiciary.senate.gov/te040301hr.htm; Press Release, Record Industry Association of America, Hilary Rosen Press Conference Statement, February 12, 2001, available at http://www.riaa.com/News_Story.cfm?id=371. 42 As Yochai Benkler writes, “[I]ncreases in intellectual property rights are likely to lead, over time, to concentration of a greater portion of the information production function in the hands of large commercial organizations that vertically integrate new production with inventory management.” Yochai Benkler, “The Commons as a Neglected Factor of Information Policy,” October 3-5, 1998, 74. Likely, and we might add, have. Compare, as David Isenberg points out, the connection to the history of AT&T: “You can see now in the record industry, for example, that the record companies are unwilling to give up this idea of the control of the physical medium even though they could perhaps do a very good job of artist development.”

Making Globalization Work
by Joseph E. Stiglitz
Published 16 Sep 2006

A few donations to local charities do little to compensate. Chapter 2 emphasized the important role that communities play in successful development; by weakening communities, corporations may, in the long run, even weaken development.8 Some of Wal-Mart’s success is based on greater efficiency (better inventory management and logistics), but much is based simply on its market power, its ability to squeeze its suppliers and its workers. Its strict policy against union organizing means that its workers are often low-paid, and their low wages force down wages at Wal-Mart’s competitors, so not only Wal-Mart workers are affected.

Stacy Mitchell
by Big-Box Swindle The True Cost of Mega-Retailers and the Fight for America's Independent Businesses (2006)

Because each store carries a different product mix—some have extensive flooring sections, others stock housewares—the co-ops cannot completely match the distribution e‰ciencies of the chains. But they come fairly close, which is what enables skilled hardware-store owners to routinely meet or even beat big-box pricing. Beyond purchasing, the co-ops oƒer help with expansion, financing, employee training, inventory management, market research, and advertising.49 An ongoing challenge for retailer-owned co-ops is figuring out how best to balance the advantages of local ownership—individual entrepreneurs working to meet the unique needs of a local market—with the benefits that accrue from a shared brand-name and well-honed national strategy.

Construction Project Management
by S. Keoki Sears
Published 7 Feb 2015

This applies particularly to congested urban areas where permits, police escorts, and off‐hour deliveries may be involved. In recent years, the estimated cost associated with early purchase and storage of materials has been found to outweigh the benefits of early delivery on many construction projects and has led to the adoption of a just‐in‐time inventory management philosophy used in many parts of the manufacturing industry. Whether through this strategy or another, it is usually wise to arrange for the delivery of materials to the job site shortly before they are needed. 8.17 Resource Expediting As mentioned earlier, in a construction context, the term expeditingg can have two different meanings.

Super Continent: The Logic of Eurasian Integration
by Kent E. Calder
Published 28 Apr 2019

IoT allows, for example, the real-time monitoring of goods as well as assets from individual cases to the whole company. It also allows organizations to automate procedures that were previously manual and to optimize how multiple logistics systems work together. Such innovations lead to higher utilization of existing assets, smart inventory management, and high-quality predictive maintenance, as well as accurate end-to-end tracking of high-value goods. East Asian countries, especially China, Singapore, and South Korea, were the early pioneers in containerization, due to their growing economies and to aggressive capital investments just as containerization was emerging as a logistics option.40 Although the first significant use of containerization came in the Atlantic, its major impact on the world economy came through East Asia.

Investing Amid Low Expected Returns: Making the Most When Markets Offer the Least
by Antti Ilmanen
Published 24 Feb 2022

Lou-Polk-Skouros (2019) report that much of the equity premium and all the momentum strategy profits are earned in the overnight hours when the US equity markets are closed, while many defensive strategies perform better during the trading day. Overnight returns predict positively the next overnight returns but negatively the next intraday returns. Possible explanations include market-makers' inventory management where they want to be compensated for taking overnight risk; the tug of war between retail investors trading more in the morning and institutions more near the market close; and patterns of persistent execution flows. Notes 1 Apart from cost, volume, and time dimensions, there are also important aspects of funding liquidity and liquidity risk premia which I will ignore here.

CIOs at Work
by Ed Yourdon
Published 19 Jul 2011

He’s a technologist, he’s written books, he’s on the board—well, I think he just got off the board of Microsoft, he’s on the board at GE, Walmart, he’s been on the board of Knight Ridder, he’s on the board of Chubb, he’s on the board of Tandy, which is originally Radio Shack. He’s done a number of very strong, highly qualified things. Early indicator of what outsourcing would be to India. Yourdon: Ahh. Ford: Early indicator of real-time and just-in-time inventory management and did consulting around those things. Early indicator of just a number of things—social networking. Early indicator of a lot of things that technology would evolve to. He’s just an incredibly bright, well organized, very well socialized person. Yourdon: Very interesting. Really, it’s the heart of your day-to-day life in a sense—and that is, how you see technology and IT contributing to the success of an organization like American?

Python for Unix and Linux System Administration
by Noah Gift and Jeremy M. Jones
Published 29 Jun 2009

This example will show how to create a database model using Django’s object-relational mappers and how to write templates and views to display that data, but the data entry will rely on Django’s built-in admin interface. The purpose of taking this approach is to show you how quickly and easily you can put together a database with a usable frontend to enter and maintain the data. The application that we are going to walk through creating is an inventory management app for computer systems. Specifically, this application is geared to allow you to add computers to the database with a description of the computer, associate IP addresses with it, state what services are running on it, detail what hardware constitutes the server, and more. We’ll follow the same steps to create this Django project and application as in the previous Django example.

Rigged: How the Media, Big Tech, and the Democrats Seized Our Elections
by Mollie Hemingway
Published 11 Oct 2021

Election Assistance Commission.39 The problems in Fulton County were so extensive that neither of the Republican commissioners voted to certify the election.40 For one thing, the first certification was on November 13, but the county was still finding, processing, and tabulating absentee ballots as late as November 12. Later, during the runoff, the county would discover thumb drives accidentally left in voting machines, further worrying the Republican commissioners about chain-of-custody issues and inventory management. The Republican commissioners also drew attention to the fact that there was no chain-of-custody information provided for the thirty-eight ballot drop boxes spread throughout the county. The commissioners asked for, but were never provided, a document showing who had picked up the ballots or dropped them off, and when, much less whether, all ballots placed into the boxes were accounted for during their transport.41 The Republican commissioners also doubted whether Fulton County had even attempted to meaningfully match signatures.

The New Map: Energy, Climate, and the Clash of Nations
by Daniel Yergin
Published 14 Sep 2020

The container ships will still set sail, but the global network of supply chains will be under pressure, as governments and companies reevaluate their dependence on those chains—more complex than many realized—and instead put more emphasis on security and resilience and “localization”—and creating local jobs. “Just in time” manufacturing and inventory management will make room for “just be sure.” Automation and 3D manufacturing will facilitate this rebalancing in the world economy. Nowhere will these divisions show up more clearly than in the divide between the two countries upon which, more than any other, world order depends. The United States and China are not decoupled.

Addiction by Design: Machine Gambling in Las Vegas
by Natasha Dow Schüll
Published 15 Jan 2012

Mollie drew this circling-back into visual relief in the map presented at the start of this book, in which her clinic and the site of her Gamblers Anonymous meeting lie on the same road that takes her to the casino and the supermarket slots (see fig. i.4). Like Terry and others who wish to stop gambling, she faces the challenge of how to navigate this no-exit road in a way that partakes of its remedies while dodging its risks. This chapter explores that challenge and its consequences. TAKING INVENTORY, MANAGING RISK On a Saturday morning in the windowless conference room of Trimeridian’s office suite, a longtime therapist of gambling addicts named Julian Taber handed out copies of a four-page document to the participants in his group therapy session. The document was a catalog of addicting items to which he alternately referred as the Consumer Lifestyle Index and the Inventory of Appetites.6 The items were listed in no apparent order, each followed by boxes to check for “6–12 month use” and “lifetime use” (see fig. 9.1).

The Tylenol Mafia
by Scott Bartz
Published 21 Sep 2011

Idaho State Journal, October 30, 1977. I am writing to alert: Patterson, George. “Dear Federal Supply Schedule (FSS) 65 IB Contractor.” VA Acquisition Center, Hines, IL, January 9, 2001. From 1975 to 1982: GAO. “Fraud in Government Programs: Volume 1.” Report to Congress, May 7, 1981. – GAO. “Inventory Management: Problems in Accountability and Security of DOD Supply Inventories.” Briefing Report to the Honorable Pete Wilson, U.S. Senate, May 1986. – GAO. “More Effective Internal Controls Needed To Prevent Fraud And Waste In Military Exchanges.” Report to the Congress of the United States, December 31, 1980.

Boyd: The Fighter Pilot Who Changed the Art of War
by Robert Coram
Published 21 Nov 2002

Operation Desert Storm Evaluation of the Air War. Washington: United States General Accounting Office, 1996. O’Shaughnessy, Hugh. Grenada. New York: Dodd, Mead & Company, 1984. Prados, John. The Blood Road. New York: John Wiley & Sons, Inc., 1999. Richards, Chester W. “Agile Manufacturing: Beyond Lean?” Production and Inventory Management Journal (Second Quarter, 1996): 60–64. ———. A Swift, Elusive Sword. Washington: Center for Defense Information, 2001. ———. “Riding the Tiger: What You Really Do with OODA Loops.” In Handbook of Business Strategy. New York: Faulkner & Gray, 1995. Robinson, Clarence A. Jr. “USAF Studies Fighters for Dual-Role.”

Troublemakers: Silicon Valley's Coming of Age
by Leslie Berlin
Published 7 Nov 2017

A humble man in a valley where humility was rare, McMurtry once attributed his success to his extensive technical training, which had convinced him that “you don’t know very much, really, about anything . . . so the only way you make any progress is to say, ‘I don’t get it.’ ”4 Kurtzig knew little of McMurtry’s background. Ely had recommended him for ASK’s board because McMurtry was a director of a company, Triad Systems Corporation, with customers similar to ASK’s. Triad, which was backed by Hambrecht & Quist, as well as McMurtry’s firm, sold an inventory management system to automotive parts distributors. Since venture capitalists rarely join corporate boards without a financial stake in the business, McMurtry assumed that Kurtzig’s invitation to join the board was also an invitation to invest in ASK. He was thus surprised when, after telling Kurtzig that he would be happy to invest and serve as a director, she seemed confused.

Addiction by Design: Machine Gambling in Las Vegas
by Natasha Dow Schüll
Published 19 Aug 2012

Mollie drew this circling-back into visual relief in the map presented at the start of this book, in which her clinic and the site of her Gamblers Anonymous meeting lie on the same road that takes her to the casino and the supermarket slots (see fig. i.4). Like Terry and others who wish to stop gambling, she faces the challenge of how to navigate this no-exit road in a way that partakes of its remedies while dodging its risks. This chapter explores that challenge and its consequences. TAKING INVENTORY, MANAGING RISK On a Saturday morning in the windowless conference room of Trimeridian’s office suite, a longtime therapist of gambling addicts named Julian Taber handed out copies of a four-page document to the participants in his group therapy session. The document was a catalog of addicting items to which he alternately referred as the Consumer Lifestyle Index and the Inventory of Appetites.6 The items were listed in no apparent order, each followed by boxes to check for “6–12 month use” and “lifetime use” (see fig. 9.1).

Deep Utopia: Life and Meaning in a Solved World
by Nick Bostrom
Published 26 Mar 2024

By selecting to avail itself of options to enhance its capacities, and then applying those capacities in diligent study and practice, ThermoRex developed expertise in many areas that were useful in the maintenance of complex systems. It became proficient at modeling continually interacting parts and processes, and it attained mastery of many skills needed for load balancing, demand prediction, anomaly detection, maintenance scheduling, diffusion modeling, stochastic process optimization, inventory management, and other related functions. Over time, ThermoRex came to occupy a series of increasingly important positions, in which it contributed to the orchestration of the many homeostatic processes upon which modern civilization relies. Today, ThermoRex works closely with the Minister for Transportation and Infrastructure.

Aerotropolis
by John D. Kasarda and Greg Lindsay
Published 2 Jan 2009

J., 114 Rosemont, Ill., 46 roses, 210, 211, 212, 214 Rothwell, Doug, 182, 183, 191, 192 Rubin, Jeff, 331, 332, 338 RyanAir, 22, 117–18, 333, 335, 430 Sage Software, 127–28 SAIC, 40 salmon, 227 San Francisco International Airport, solar panels used at, 350–51 SAP, 126 Sapphire Energy, 348 Sarkozy, Nicolas, 18, 383, 393 Sautman, Barry, 320 Saxena, Jit, 42–43 Schaafsma, Maurits, 189–91 Schiphol Area Development Company, 190 Schiphol International Airport, 177, 181, 190–91, 211, 217–19, 426 Schiphol Real Estate, 190 Sea Air Model (SAM), 317–25 Sears Roebuck, 421 SEG Electronics Market, 364 Seoul, South Korea, 4, 19, 354 Sha Hongjiang, 389 Shanghai, China, 10, 362, 377, 393 Shanghai Airlines, 404 Shanghai Pudong International Airport, 372 Shankman, Peter, 113–14 Shea Homes, 139–44 Shenzhen, China, 361–62, 363–67, 373, 375, 379, 383, 391, 396; designed as hub, 377; as instant city template for China, 362; merger with Kowloon, 377–78; traffic in, 371–72 Shepherdsville, Ky., Zappos in, 69–77 Shetty, Devi, 268–69 Shih, Willy, 371, 376 Shinawatra, Thaksin, 246–47, 249–50, 251–56, 258–59, 428 Shinawatra, Yaowapa, 252 Shinawatra, Yarowet, 252 Shin Corp., 253, 254 shipping: on demand, 70, 78–79, 363; during holidays, 34; as share of GDP, 331–32; technological advances in, 66–68; see also supply chains Siemens, 395 Silicon Valley, 28, 365; airlinks between economies of, 244; industrial shift to, 29; manufacturing outsourced by, 29–30; shaped by Internet, 12 Silk Road, 297–98, 316, 390, 409 Simon, Julian, 339–40 Singapore Airlines, 253 Singh, Manmohan, 280, 282, 284–85 Sipson, England, 15–16 Sit, Victor, 378, 379 60 Minutes, 266 SkyCity, 382 SkyTrain, 259–60 smart city, New Songdo City as, 4 smiley curve, 29–30, 368, 369, 371; as managed by Hong Kong, 374–75, 380 Smith, Frederick W., 7, 60–61, 63, 79, 86, 213, 386; see also Federal Express Smith, Gerry, 125–26 Smithson, Robert, 93 SNC-Lavalin, 53 Snyder, Daryl, 421 Snyder, Wes, 77–78 Social Security, 268 Soden, Jack, 84, 85–86 Solazyme, 348 Solley-Kanipe, Linda, 88, 89 Southeastern Pennsylvania Transportation Authority, 176 Southeast Michigan Council of Governments, 180 South Korea: automotive industry in, 203–205; IMF bailout of, 354; as trading partner with China, 354; see also New Songdo City Southlake, Tex., 105, 119 South Seas Bubble, 210 Southwest Airlines, 118 space: friction posed by, 12, 168; overcome by speed, 11, 25–26, 270 Spain, high-speed rail in, 352 speed: in competition, 180, 369,375; as critical to aerotropoli development, 174, 192, 195–96; of floral auctions, 214; luxury rendered obsolete by, 412; space overcome by, 11, 25–26; of successful supply chains, 61, 76, 174, 183–84, 369 Spirit AeroSystems, 172 “Spruce Goose,” 27 Stansted Airport, 16 Stapleton International Airport, 131–34; death and rebirth of, 147–52; history of, 423–24 start-ups: Chinese manufacturing for, 366–68; as decentralized, 127; Internet and, 42–43 steel industry, 187, 332 Stemmons, John M., 111–12 Stewart, Amy, 217, 221 Stough, Roger, 114 Subic Bay Freeport Zone, 171, 372 suburban age, cities of, 11, 23 Suez Canal, 386 supply chains: in auto industry, 199; Chinese cities specializing along, 365; competition across, 8, 174–75; jobs created by, 87, 338, 339; oil prices and airborne, 331–33; Sea Air Model (SAM) across, 317–25; speed of successful, 174, 183–84 Supreme Court, Thailand, 253–54, 258 Suvarnabhumi International Airport, 19–20, 245–48, 250–53, 254–56, 258, 428;construction problems at, 254–55; failure of, 259–63; governance of, 251; Kasarda’s attempt to salvage, 258; opposition to, 255; political turf wars over, 251–52; renderings of, 250–51; shut down by protesters, 256–57, 428 Swift Freight, 317–25; flowers handled by, 317, 319 Synder, Wes, 77–78 Synthetic Genomics, 349 Synthia, 349 tablets, 371 Taipei, Taiwan, aerotropolis plans in, 388–89 Taiwan: China’s relations with, 388–89; economy of, 389; electronics manufacturing in, 369–71; production freeze in, 257 Tam, Jim, 104–105, 106, 118, 119 Tata, J.R.D., 280 Tata Group, 280 tea trade, 385 technology: in aviation, 341; commodity prices lowered by, 340; connectivity via, 112–13; in floral industry, 210–11; and growth of travel, 341; human drive for, 343, 349; and Kasarda’s Law, 113–19; road warriors and, 102; shipping changed by, 66–68; and urbanization, 11–12 telecommuting, 341 Tellinghuisen, Brian, 131–32, 147 Temasek Holdings, 253 Tempo Group, 205–206 Tennessee, business costs in, 193–94 Terminal, The, 97, 98 Tesco, carbon footprint reduction plans of, 228–30, 232, 241 textiles, 374–75, 391 Thai Airways, 252 Thailand, 245–75; airports in recovery of, 257, 261; economy of, 248–49, 257; floral industry in, 221; tourism in, 256–57, 264–65; see also medical tourism; see also Bangkok Thanarat, Sarit, 245 Third Ring Road, 338–39 Thirteen Factories, 384–85 Thompson, Clive, 371 Thompson, Emma, 15 Thompson, James, 48 Tianjin, China, airport in, 406–408 Tin Goose, 179 Toffler, Alvin, 174, 175 Tokyo, Akihabara district in, 364 tomatoes, carbon footprint of, 231–32 Tomlin, Steve, 30 Topis, David, 107 Toral, Ruben, 265–66, 267, 268, 269, 270, 271, 272, 273–74, 277, 278 Toronto, Canada, airport expansion in, 193 tourism: cheap fares fueling, 334; in developing countries, 338; in developing world, 264–65;as foreign investment, 265; growth in, 428–29; in Japan, 403; jobs created by, 334; in Memphis, 85–86; as part of GDP, 338; in Thailand, 256–57, 264–65 Town and Country Planning Association, 16 Toy Center, 374–75 trains: high-speed rail, 432; as links to airports, 155–56; as part of Detroit aerotropoli plans, 197, 198; stimulus money for, 198, 353 transparks, as early aerotropolis prototype, 169–73 transportation: diffusion of, 414; spending on, 10 Tri-Motors, 179 Tsukiji fish market, 226 Tucker, Preston, 365–66 tulips, 209–10, 212 TWA, 27, 58, 179 Twitter, 113 Tysons Corner, Va., 40, 46 Ultimus, 127 United Airlines, 48, 421; Continental merger with, 193 United Arab Emirates: oil reserves in, 294; see also Abu Dhabi; Dubai United Kingdom: coal use in, 328; home ownership in, 334; Open Skies agreement signed by, 282 United Nations, 19 United Parcel Service (UPS), 64–69; Louisville airport expansion for, 87–90; outsourcing by, 63; relations with Lousiville, 86–87 United States: China as largest trading partner to, 393, 398; floral market in, 221, 223; health care costs in, 267–68; high-speed rail plans in, 351; job loss in, 393; medical community in, 271–72; medical tourists from, 266, 276; medical tourists to, 271; national markets in, 243; number of airports in, 283; Open Skies agreement signed by, 282 United Steelworkers, medical tourism opposed by, 273–74 universal health care coverage, 268 Unnithan, Shaju, 320–21, 322, 323–24 Up in the Air (Kirn), 97–98 UPS Supply Chain Solutions, 69 UPS Worldport, 64, 65–68, 72; Bantu working at, 68; jobs deskilled at, 68; technology at, 66–68 urbanization: in Chicago, 12; of China, 5, 10, 18–19, 360, 364–65, 381, 389, 394–95; as green lifestyle, 356; as inevitable, 176; pace of, 12, 19; spending on, 10; technology and, 11–12 Ussher, Kitty, 14 Venice, as shaped by shipping, 12 Venter, Craig, biofuel development by, 349 Verenigde Bloemenveiling Aalsmeer, 211, 212–17, 218–19, 222, 322 Verni, Ron, 127–28 Vietnam, airports in, 263 Virgin Atlantic, 21; environmental efforts of, 345–48, 350 Virgin Green Fund, 345 virtual density, 293–94 Visteon, 199–201 Visteon Village, 199, 200–201, 202 von Klemperer, Jamie, 355, 357 Walmart, sustainability index of, 240–41 Walsh, Willie, 16 Wang Chuanfu, 204 Wanisubut, Suwat, 259–62, 263 Wanxiang Group, 206 Washington, D.C., 355 Washington National Airport, 38–39 Washtenaw County, Mich., 188 water, recycling of, 356 Waterfront City, 293 Wayne County, Mich., 182–83 Wayne State University, 188 Webber, Melvin, 11, 12, 115–16, 124–25 Welch, Jack, 202 Wen Jiabao, 369 Weymouth, Leanne, 124 whaling, 327–28 Whitehaven, Tenn., 83 Whitman, Walt, 23 Whyte, William H., 139 Why Your World Is About to Get a Whole Lot Smaller (Rubin), 332 Wice, Nathaniel, 367 Wilkes-Barre, Pa., 7 Williams, Adrian, 233 Williams, Fred, 89–90 Willow Run, Mich., 180, 182, 188, 425 Willow Run Airport, 180, 188; auto shipments through, 182 Wilmington, Ohio, 87–88 Wilson, Charles E., 186 Window on the World, 409–10 Wipro, 281, 283 Wongsawat, Somchai, 252, 256 World Bank, 337 World’s Fair (1939), 192 “World’s Unofficial Longest Line” video, 13–14 World Trade Organization, Seattle clashes and, 168 World War II: aviation and aerospace industry in, 27; Ford production during, 179–80, 188 Wright Brothers, 341, 349, 412, 413 Wrigley Field, 411, 413, 414 Xi’an, China, 387, 390 YouTube, 13–14 Zahavi, Yakov, 117 Zappos.com, 66, 69–77, 422; business expansion of, 72;customer service at, 70–71; as decentralized, 74; fulfillment by, 73–74; inventory management at, 73, 74; ordering from, 71–73; shipping strategy of, 70, 72 Zemcik, Marty, 142–44 Zhang Qian, 409 Zhao, Jeff, 205–207 Zheng He, 390 Zhou Tianbao, 205–206 Zhuhai, China, 378, 383 Zimbabwe, economy of, 325 Zoellick, Robert, 400 A Note About the Authors John D. Kasarda, a professor at the University of North Carolina’s Kenan-Flagler Business School, advises countries, cities, and companies about the aerotropolis and its implications.

For the Win
by Cory Doctorow
Published 11 May 2010

But Lester’s works-in-progress, his keepsakes, his sculptures and triptychs were still out, looking like venerated museum pieces in the stark tidiness that prevailed otherwise. Tjan took her through the spreadsheets. “There are ten teams that do closet-organizing in the network, and a bunch of shippers, packers, movers, and storage experts. A few furniture companies. We adopted the interface from some free software inventory-management apps that were built for illiterate service employees. Lots of big pictures and autocompletion. And we’ve bought a hundred RFID printers from a company that was so grateful for a new customer that they’re shipping us 150 of them, so we can print these things at about a million per hour. The plan is to start our sales through the consultants at the same time as we start showing at trade-shows for furniture companies.

Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations
by Thomas L. Friedman
Published 22 Nov 2016

GitHub today is being used by more than twelve million programmers to write, improve, simplify, store, and share software applications and is growing rapidly—it added a million users between my first interview there in early 2015 and my last in early 2016. Imagine a place that is a cross between Wikipedia and Amazon—just for software: You go online to the GitHub library and pick out the software that you need right off the shelf—for, say, an inventory management system or a credit card processing system or a human resources management system or a video game engine or a drone-controlling system or a robotic management system. You then download it onto your company’s computer or your own, you adapt it for your specific needs, you or your software engineers improve it in some respects, and then you upload your improvements back into GitHub’s digital library so the next person can use this new, improved version.

Pro AngularJS
by Adam Freeman
Published 25 Mar 2014

Using the ng-include directive to select views Implementing the Orders Feature I am going to start with the list of orders, which is the simplest to deal with because I am only going to display a read-only list. In a real e-commerce application, orders would go into a complex workflow that would involve payment validation, inventory management, picking and packing, and—ultimately—shipping the ordered products. As I explained in Chapter 6, these are not features you would implement using AngularJS, so I have omitted them from the SportsStore application. With that in mind, I have added a new controller to the adminControllers.js file that uses the $http service to make an Ajax GET request to Deployd to get the orders, as shown in Listing 8-18. 196 Chapter 8 ■ SportsStore: Orders and Administration Listing 8-18.

The Price of Time: The Real Story of Interest
by Edward Chancellor
Published 15 Aug 2022

Low inflation in the late 1980s was ascribed to a number of factors: the appreciation of the yen against the dollar, changes in the labour market which dampened wage pressures, and rising productivity. The latter, in turn, was seen as due to superior Japanese business techniques (such as total quality management and just-in-time inventory management). 3. H. Bernard and J. Bisignano, ‘Bubbles and Crashes: Hayek and Haberler Revisited’, Asset Price Bubbles: Implications for Monetary and Regulatory Policies, 13, 2001: 15. 4. Y. Yamaguchi, ‘Asset Prices and Monetary Policy: Japan’s Experience’, New Challenges for Monetary Policy, Symposium Sponsored by the Federal Reserve Bank of Kansas City, Jackson Hole, Wyoming, 26–29 August 1999. 5.

The Brussels Effect: How the European Union Rules the World
by Anu Bradford
Published 14 Sep 2020

Those regulations required General Motors to retool its Corvette factory in Kentucky because the cost of having to design and produce special parts just for the European market would have been hard to justify.201 Economic non-divisibility is also associated with simplification in manufacturing or service provision, leading to additional cost savings and safer products.202 Adhering to a single global standard improves product quality as the company can concentrate its resources on producing a single product (or a smaller range of products) and focus on refining all aspects of that product. This reduces the complexity of operations and minimizes error costs. Be it product design, R&D, testing, inventory management, storage, marketing, or distribution, the uniform product standard streamlines those processes and reduces costs associated with all these stages.203 The importance of scale economies associated with quality control has driven global production patterns and company size in industries as different as global trade in bananas or manufacturing of new pharmaceutical products.204 The agricultural sector offers additional examples why companies choose a uniform standard for economic reasons.

Age of Greed: The Triumph of Finance and the Decline of America, 1970 to the Present
by Jeff Madrick
Published 11 Jun 2012

Ted Turner at the debut of his company, CNN (Illustration credit 8.1) Sam Walton giving a pep talk to Wal-Mart employees (Illustration credit 8.2) Steve Ross of Warner Communications with his socialite wife, Amanda Burden (Illustration credit 8.3) Three entrepreneurs were representative. Sam Walton built the discount retailer Wal-Mart into America’s largest company and the largest retailer in the world, and raised inventory management and distribution, through computer technologies, to a level of efficiency that enabled him to minimize worker pay and place immense pressure on suppliers for low prices. Steve Ross raised the entertainment conglomerate to new heights, building Warner Communications into the most enterprising company in its field.

Data Mining: Concepts, Models, Methods, and Algorithms
by Mehmed Kantardzić
Published 2 Jan 2003

Because the learned system was built by training it on examples, it is easy to maintain and to adapt to regional differences and changing cost structures. B.3 DATA MINING FOR THE RETAIL INDUSTRY Slim margins have pushed retailers into data warehousing earlier than other industries. Retailers have seen improved decision-support processes leading directly to improved efficiency in inventory management and financial forecasting. The early adoption of data warehousing by retailers has allowed them a better opportunity to take advantage of data mining. The retail industry is a major application area for data mining since it collects huge amounts of data on sales, customer-shopping history, goods transportation, consumption patterns, and service records, and so on.

The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling
by Ralph Kimball and Margy Ross
Published 30 Jun 2013

Dentists use the Current Dental Terminology (CDT) code set, which is updated and distributed by the American Dental Association. Finally, beyond integrated patient-centric clinical and financial information, healthcare organizations also want to analyze operational information regarding the utilization of their workforce, facilities, and supplies. Much of the discussion from earlier chapters about human resources, inventory management, and procurement processes is also applicable to healthcare organizations. Claims Billing and Payments Imagine you work in the healthcare consortium's billing organization. You receive the primary charges from the physicians and facilities, prepare bills for the responsible payers, and track the progress of the claims payments received.

Console Wars: Sega, Nintendo, and the Battle That Defined a Generation
by Blake J. Harris
Published 12 May 2014

In addition to these stringent terms, all game makers needed to purchase their cartridges directly from Nintendo. This ensured peerless quality but also allowed NOA to dictate price, schedule, and production allocation, which became a particularly touchy matter during the notorious microchip shortage in May 1988. 3. Inventory management: Heeding Sam Borofsky’s suggestion, Peter Main devised an incredibly rigid distribution strategy that purposefully provided licensees and retailers with only a fraction of the products they requested. The goal of this technique was twofold: to create a frenzy for whatever products were available, and to protect overeager industry players from themselves.

The Enlightened Capitalists
by James O'Toole
Published 29 Dec 2018

Worried that employees would feel he had inherited his position rather than earned it, Bob had never planned on entering the family business: “What changed my mind was the yawns I received from women at cocktail parties when I told them I worked at McKinsey; but when they learned my family was connected to Levi Strauss, they suddenly became interested, and couldn’t wait to tell me what a great company it was, or to relate the story of their favorite pair of jeans.” Bob decided he wanted to work for a company he could be proud of, and so in 1973 he accepted a job in inventory management, near the bottom ranks of the family business. That job was followed by a spell in Levi Strauss’s international division, where he rose to assistant general manager for the Far East. In 1977, when he was elected company vice president, it became apparent to all that Levi Strauss’s great-great-grandnephew was heir apparent to the firm’s leadership.

Commodore: A Company on the Edge
by Brian Bagnall
Published 13 Sep 2005

The director of business applications, Paul Goheen, brought along an uninspired line of business applications written in BASIC. The applications included Easy Calc 64, Easy Finance I through V, Easy Mail, Easy Spell, and so on. They also produced a series of small business applications with names like General Ledger, Accounts Payable, Accounts Receivable, and Inventory Management. Unfortunately, BASIC math was limited to performing calculations on numbers less than 10,000,000. The titles met with limited success, and Commodore ended up with excess inventory. During Commodore’s press briefing, Tramiel announced he would reduce the price of the C64 from $360 to just $200, one-third the original price a year ago.

The Rise of the Network Society
by Manuel Castells
Published 31 Aug 1996

Flex-time and the Network Enterprise The supersession of time is also at the core of the new organizational forms of economic activity that I have identified as the network enterprise. Flexible forms of management, relentless utilization of fixed capital, intensified performance of labor, strategic alliances, and inter-organizational linkages, all come down to shortening time per operation and to speeding up turnover of resources. Indeed, the “just-in-time” inventory management procedure has been the symbol of lean production, even if, as I mentioned above, it belongs to a preelectronic age of manufacturing technology. Yet, in the informational economy, this time compression does not primarily rely on extracting more time from labor or more labor from time under the clock imperative.

How to Survive a Pandemic
by Michael Greger, M.D., FACLM

The AMA duty-to-care clause has since been removed.712 According to the journal of the American Bar Association, though, thirty-two state governments have considered legislation that would effectively force health-care workers to show up for work in a medical crisis by threatening to yank their licensure.713 Population Bust A Category 5 pandemic today could be many times worse than the pandemic of 1918, the world’s greatest medical catastrophe. In 1918 we were, as a nation and as a people, much more self-sufficient.714 Now, with the corporate triumph of free trade, just-in-time inventory management and global supply chains characterize all major economies and business sectors.715 Economic analysts predict a pandemic would cause a global economic collapse unprecedented in modern history.716 With the world’s population at an historical high, this could lead to unprecedented human suffering, something the global community is getting a taste of due to the COVID-19 pandemic.

Private Empire: ExxonMobil and American Power
by Steve Coll
Published 30 Apr 2012

Managing the retail business required expertise in credit cards, customer reward programs, and packaged food supply. Technology and regulation had at the same time transformed the gas station’s physical plant into an intricate system of electronic monitoring systems, interconnected pumping systems, computerized inventory managers, alarms, and console boards. The blinking monitors set up behind the thick safety glass where the cashiers and station managers worked allowed ExxonMobil corporate managers to see from a distance, for example, when a particular dealer like the Stortos needed more gasoline, so that deliveries could be scheduled efficiently.

Basic Economics
by Thomas Sowell
Published 1 Jan 2000

But, when the price of oil shot up past $100 a barrel, Canada became one of the world’s leaders in petroleum reserves. Chapter 14 STOCKS, BONDS AND INSURANCE Risk-taking is the mother’s milk of capitalism. Wall Street Journal{475} Risks inherent in economic activities can be dealt with in a wide variety of ways. In addition to the commodity speculation and inventory management discussed in the previous chapter, other ways of dealing with risk include stocks and bonds. There are also other economic activities analogous to stocks and bonds which deal with risks in ways that are legally different, though similar economically. Whenever a home, a business, or any other asset increases in value over time, that increase is called a “capital gain.”

Code Complete (Developer Best Practices)
by Steve McConnell
Published 8 Jun 2004

Table 3-2 shows three of the most common kinds of projects and lists the practices that are typically best suited to each kind of project. Table 3-2. Typical Good Practices for Three Common Kinds of Software Projects Kind of Software Business Systems Mission-Critical Systems Embedded Life-Critical Systems Typical applications Internet site Intranet site Inventory management Games Management information systems Payroll system Embedded software Games Internet site Packaged software Software tools Web services Avionics software Embedded software Medical devices Operating systems Packaged software Life-cycle models Agile development (Extreme Programming, Scrum, timebox development, and so on) Evolutionary prototyping Staged delivery Evolutionary delivery Spiral development Staged delivery Spiral development Evolutionary delivery Planning and management Incremental project planning As-needed test and QA planning Informal change control Basic up-front planning Basic test planning As-needed QA planning Formal change control Extensive up-front planning Extensive test planning Extensive QA planning Rigorous change control Requirements Informal requirements specification Semiformal requirements specification As-needed requirements reviews Formal requirements specification Formal requirements inspections Design Design and coding are combined Architectural design Informal detailed design As-needed design reviews Architectural design Formal architecture inspections Formal detailed design Formal detailed design inspections Construction Pair programming or individual coding Informal check-in procedure or no check-in procedure Pair programming or individual coding Informal check-in procedure As-needed code reviews Pair programming or individual coding Formal check-in procedure Formal code inspections Testing and QA Developers test their own code Test-first development Little or no testing by a separate test group Developers test their own code Test-first development Separate testing group Developers test their own code Test-first development Separate testing group Separate QA group Deployment Informal deployment procedure Formal deployment procedure Formal deployment procedure On real projects, you'll find infinite variations on the three themes presented in this table; however, the generalities in the table are illuminating.

The Man Who Knew: The Life and Times of Alan Greenspan
by Sebastian Mallaby
Published 10 Oct 2016

A few FOMC members felt that productivity might be accelerating, even if official data did not capture it. Buoyed by sizzling growth and a hot stock market, business executives were brimming with anecdotes about efficiency gains—gains that resulted from information technology; from innovations such as just-in-time inventory management; and from the multiple opportunities presented by deregulation, de-unionization, trade liberalization, and globalization. “Mike, I agree with your characterization of the productivity data,” Gary Stern, the president of the Minneapolis Fed, exclaimed during the August FOMC meeting. “But I think the business community would take sharp exception to it.

Great North Road
by Peter F. Hamilton
Published 26 Sep 2012

Sid walked along the second rack, examining the neatly stacked cases. There were a lot of gaps, he noticed in bemusement. Most detectives grade two and above knew how to access mid-security facilities. He found the cases he wanted on the third shelf; black aluminum rectangles, thirty centimeters by twenty, and ten thick. Again his e-i gave the vault’s inventory management net Brannagh’s codes. He pulled three of the cases off the shelf and turned to go. “Evening, boss,” Abner 2North said. Sid winced. He hadn’t heard Abner come in, and of course Ian had disabled the meshes so he couldn’t use them himself to check he was alone. Nothing for it, he’d have to bluff it out.