Russell Walker

Walker, Russell and Tom Davenport. "LinkingIN to Data Products." Wall Street Journal.

Every so often we notice an interesting infographic using LinkedIn Corp. data. What universities, for example, are the primary feeders for tech employers like Apple Inc. (turns out it’s San Jose State) and Microsoft Corp. (University of Washington by a landslide)? What company internships lead to good jobs in different industries? (most are predictable, but surprises include Plante Moran in accounting, Protiviti in management consulting, and Persistent Systems in computer software) And for the inevitable holiday PR offering, what do professional Santa Clauses do when it’s not the holidays? (marketing event manager is the most likely role). These may seem like amusing ways to spend your time when you are tired of watching cat videos, but they are actually indicative of some serious business value. The infographics are summaries of what companies can do with data products. One of us (Tom) has written columns about data products on this site, and the other (Russ) has recently written a book on the topic called From Big Data to Big Profits. Incidentally, making data products has been enormously profitable for LinkedIn. It credits data products with $450M in additional revenue for 2013, and that doesn’t count very successful “internal” data products like People You May Know, to which the company credits half its memberships. We think that LinkedIn is an excellent example of how to make money from data products. Its offerings are an essentially free service to most of its members, of course, but it generates revenue from data products and premium services. The data generated through the normal use of the network is an incredibly rich source of insight, and advertisers, search firms, and premium users are willing to pay for LinkedIn’s valuable data products. For example, if we choose to get a premium account, we can find out exactly who has seen our profiles. If we were professional headhunters, we could pay to get even more specific information, such as all the robotics engineers who graduated from Northwestern University in 2004. And if we were writers or editors (the infographic on tech feeder schools was published by Wired magazine) or university administrators, we could look for connections between specific schools or degrees and actual careers, to the point of calculating the potential ROI for any given degree. Despite this success, we think that LinkedIn could go even further to make its amazing data more valuable. It has a data products group within the company, but at least when Tom visited a few years ago, it had a pretty unstructured process for data product creation. Some of the company’s most successful data products came from outside the group. That’s not terribly surprising, because with 364 million members across 200 countries, the company has way more data than a small data products group (and an additional data science group) can deal with. In fact, it’s a bigger resource than all of LinkedIn’s 7600 employees can take advantage of. So we’d argue that LinkedIn should create an institute—perhaps called the LinkedInstitute—of external people who can help to analyze all this data and extract value from it. We’re sure that some of the knowledge generated could be monetized in some fashion, and perhaps even more importantly, the world would learn a lot. How useful would it be to know, for example, what educational preparation is most likely to lead to rapid promotion? What jobs are great stepping stones for a fantastic career? What places should you live if you want to be successful in different industries? What training is most useful and who needs it most (rationalizing in part LinkedIn’s acquisition of Lynda)? With personalized data, LinkedIn could even recommend the next best career move for individuals. These could all be extremely useful and valuable types of information. Russ found in his research on data products that some of the most successful providers of them share a lot of data. Uber Technologies Inc. and Airbnb Inc., for example, are successful in large part because they share a lot of data—normally for free—with their drivers and service providers. They’ve developed digital platforms just for that purpose. Both companies are worth an amazing amount of money for privately-held firms, and we’d argue that their information sharing is a key component of their value. Sharing to create the network of users, as in the case of LinkedIn, Uber and Airbnb, has led to more valuable data products that are ultimately sold back to those same users, while also attracting new participants in the network. So it makes sense to look to LinkedIn as a model for data products, but we think that even that company—and other successful examples of this phenomenon—have only scratched the surface of what is to be done. There is a massive amount of value in the data that online (and offline, for that matter) firms have accumulated. Unlocking it and creating new offerings based on it can become a key growth area for individual firms and our entire economy. Thomas H. Davenport is a Distinguished Professor at Babson College, a Research Fellow at the Center for Digital Business, Director of Research at the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics. Russell Walker, Ph.D. is a Clinical Associate Professor at the Kellogg School of Management of Northwestern University. This article originally appeared in the Wall Street Journal on July 22, 2015.

Walker, Russell. "Monetizing Big Data For Big Profits: It Takes More Than Algorithms." Forbes.

The process of monetizing Big Data is really an exploration, driven by experimentation and identification of value. Here are a few points to keep in mind: 1. Look for Patterns in the Data – before trying to find the needle in the haystack, look for the patterns that describe customers, markets and operations that are directly linked to your decisions and investments. Look for the data to support big decisions, first! Such patterns can lead directly to wide-scale improvements and increase firm performance. It is about big hits. Before addressing finer points in complexity, look for answers to fundamental business questions: when, why, how, and through whom do your customers buy your products. For financial service firms this has been the vein of gold that has led to risk-based pricing and now on-line coupons. For eBay, the analysis is about popular products, successful sellers, and tracking customer preferences. money2. Allow and Encourage Your Data Science Team to Experiment – opportunities in data will not be self- evident. This will require exploration, time, and investment. Just like a stock analyst is expected to spend a great deal of time in research to find a few winners, expect your data science team to explore and to experiment to find the nuggets of value, too! With data scientists being in such high demand, this extra use of data scientists might be hard to justify. Liberating them of the coding and mundane analytical work (in part) needed by the firm for tactical work will be challenging. However, it will be important to do so if you want to achieve strategic goals of monetizing data. 3. Examine what Your Data Says about Assets – Just like Zillow has amassed a large data set about home prices, attracting the interest of outside users, including homeowners, home buyers, realtors and tax assessors (among others), consider who else might be interested in your data and who you can attract. If the data is not directly actionable to you, would others find it valuable? If so, consider strategies for selling the data or making it available to other parties via data products. 4. Form Data Products – Internally and Externally – Only very sophisticated teams are able and willing to buy raw data. They are also unlikely to pay high prices because they will expect to spend the time extracting the value or bringing the data to market. When leveraging data for value, it needs to be transformed into a data product that answers questions about the business. Internally, this is often about a resource allocation – where to market more? What to sell? What to make? For an external user of data, the questions are often about market performance and how they did relative to a competitor. eBay, for instance, has data products on how sellers perform and what products are selling where and at what prices. This creating of data products has many similarities to creating physical products. The product must be conceived, developed, marketed, sold, managed, and updated to create value for the user (and buyer). Zillow, Netflix, Google, eBay, and LinkedIn have all successfully created data products that help users. These data products are evolving in the market and change based on customer needs. Monetizing data will not be a one-stop operation but rather an on-going process. Recognizing that these steps must in place to monetize data is important. These steps suggest functions and requirements that are not often part of an analytical or data science team. Firms that broaden their vision and use of the data will lead to more value. These important steps in monetizing Big Data in the digital economy and more are developed in my recent book, From Big Data to Big Profits: Success with Data and Analytics. The book examines the evolving nature of Big Data and how businesses can leverage it to create new monetization opportunities. Using case studies on Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leading-edge users of Big Data, the book also explores how digital platforms, including mobile apps and social networks, are changing customer interactions and expectations, as well as the way Big Data is created and managed by companies. Companies looking to develop a Big Data strategy will find great value in the SIGMA framework, which assesses companies for Big Data readiness and provides direction on the steps necessary to get the most from Big Data.

Walker, Russell. 2014. Menus of Change Annual Report. An Initiative of the Harvard School of Public Health and the Culinary Institute of America. Menus of Change.

Menus of Change Annual Report. An Initiative of the Harvard School of Public Health and the Culinary Institute of America FOOD SUPPLY CHAIN TRANSPARENCY AND RESILIENCY In 2013, the food industry was rocked by controversial and large-scale food supply cases: a horsemeat scandal in Europe and the export of tainted milk to seven countries. Both cases demonstrate how food sourcing is highly globalized and why accurate labeling and better food traceability are more important than ever.

Walker, Russell. 2013. Winning with Risk Management. World Scientific Publishing Company.

This book develops the notion that companies can succeed on the basis of risk management, much as companies compete on efficiency, costs, labor, location, and other dimensions that provide advantages. The reality of risk and how it impacts companies is that it is definite, often catastrophic and looks like a shock to the firm. This is striking, as a difference between firms on risk management can be more definite and impactful than a difference in operating efficiencies, for example. Those successful with risk are more clearly identified and the spoils are more clearly and immediately claimed. Winning with risk management requires discipline and a commitment to using information in decisions. More specifically, it requires recognizing shocks in industries and when competitors are poorly prepared so that action can be taken. Winning with risk also requires protecting owned assets and guarding against threats and reputational risks. This book will examine how leading firms that compete on risk have successfully done so. Through select case studies, this book showcases best practices in making risk management a competitive advantage in an enterprise. The cases further suggest that the competitive advantage from risk management also has implication on the capital structure of firms and their organizational formation. The competitive use of risk is not simply based on a set of algorithms, but rather encompasses how the enterprise deals with uncertainty, how it gathers data and transforms such data into meaningful risk information. The use of risk information requires that organizations seek and examine disconfirming information and promote a culture for decision-making that is open to such disconfirming information. This book will also examine how organizations must develop, treat, and communicate risk information for the purposes of winning with risk management.

Walker, Russell and Rafique Jiwani. 2015. Reinventing E-Commerce: Amazon's Bet on Unmanned Vehicle Delivery. Case 5-315-501 (KEL911).

In a December 1, 2013, interview on American television program 60 Minutes, Amazon CEO Jeff Bezos announced that Amazon would soon change the future of online shopping by enabling customers to receive items within thirty minutes of ordering. This delivery service, Bezos said, would be powered by unmanned autonomous drones and could be offered as soon as 2015. The market reaction was instantaneous and positive.

Still, Amazon needed some answers before it could launch autonomous delivery services: Were customers ready to embrace and pay for this type of delivery service? Would regulators allow it? Should Amazon make or buy its drones? Would it be too risky for Amazon to wait to launch this service? If it decided to go ahead, how should it launch, and to whom?

Spanish translation available.

Walker, Russell. 2013. Maxxed Out: TJX Companies and the Largest-Ever Consumer Data Breach. Case 5-313-507 (KEL764).

In November 2005 Fidelity Homestead, a savings bank in Louisiana, began noticing suspicious charges from Mexico and southern California on its customers’ credit cards. More than a year later, an audit revealed peculiarities in the credit card data in the computer systems of TJX Companies, the parent company of more than 2,600 discount fashion and home accessories retail stores in the United States, Canada, and Europe.

The U.S. Secret Service, the U.S. Justice Department, and the Royal Canadian Mounted Police found that hackers had penetrated TJX’s systems in mid-2005, accessing information that dated as far back as 2003. TJX had violated industry security standards by failing to update its in-store wireless networks and by storing credit card numbers and expiration dates without adequate encryption. When TJX announced the intrusion in January 2007, it admitted that hackers had compromised nearly 46 million debit and credit card numbers, the largest-ever data breach in the United States.

Schmedders, Karl, Russell Walker and Michael Stritch. 2010. Arbor City Community Foundation (A): The Foundation. Case 5-310-502(A) (KEL585).

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the Fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the Fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the Value-at-Risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses.

The questions in part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF’s risk management.

In part (B) the foundation receives a major donation. As a result the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund’s new portfolio and to perform a portfolio rebalancing analysis.

Walker, Russell. 2016. Bank of America: Consumers Fight Back. Case 5-116-001 (KEL947).

On October 6, 2011, President Barack Obama publicly scolded Bank of America for developing a new revenue stream: a $5 monthly fee for all Bank of America debit card holders, which the bank had announced a month earlier. It was a strategy for replacing lost "swipe fee" revenue following the passage of the Dodd-Frank Act and accompanying Durbin Amendment, which capped swipe fees at 21 cents per transaction. This was the culmination of three tumultuous years for the world's largest financial services firm, but would not be the end of its public affairs challenges.

The president's public critique of Bank of America came in response to—and helped exacerbate—consumer anger about the bank's monthly fee, changes across the banking sector, and general discontent with Wall Street. Bank of America's situation was complicated further by ongoing legal action following acquisitions of Merrill Lynch and Countrywide, which hurt the firm's shareholders and led to large-scale employee layoffs.

In this case study, students will be challenged to analyze how Bank of America could have better managed the competing interests of different stakeholders, including shareholders, employees, regulators, customers, and the public.

Schmedders, Karl, Russell Walker and Michael Stritch. 2010. Arbor City Community Foundation (B): Managing Good Fortune. Case 5-310-502(B) (KEL586).

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the Fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the Fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the Value-at-Risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses.

The questions in part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF’s risk management.

In part (B) the foundation receives a major donation. As a result the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund’s new portfolio and to perform a portfolio rebalancing analysis.

Walker, Russell and Kyle Bell. 2015. Nestlé Ice Cream in Cuba. Case 5-315-504 (KEL919).

In 1996, as the Castro regime began welcoming limited international investment back to Cuba, Nestlé signed a letter of intent with the Cuban government to build an ice cream factory in Havana’s El Cotorro neighborhood. The plant, a joint venture between the Cuban government and Nestlé, would produce high-quality ice cream products for tourists and affluent Cubans.

Nearly twenty years after this decision to enter the Cuban market, it is not clear how successful the investment has been and what the future might hold for Nestlé on the island. Nestlé has faced important challenges in Cuba—such as supply shortages, entrenched domestic competitors, and risk of government interference—but there has been evidence of some marketing and financial success. The 2015 normalization of diplomatic relations may bring new strategic threats and opportunities as American companies begin to eye the Cuban market and current competitors prepare for market changes.

In the case, students will evaluate Nestle’s investment and strategy for future growth in the Cuban market and consider the company’s market entry strategy, operations, and finances.

Walker, Russell. 2014. Conseco: Market Assumptions and Risk. Case 5-311-509 (KEL796).

In March 2007 C. James Prieur, CEO of insurance provider Conseco, was faced with a crisis. The front page of the New York Times featured a story on the grieving family of an elderly woman who had faithfully paid for her Conseco long-term care (LTC) policy, only to find that it would not pay her claims. Her family had to pay for her care (until her recent death), which unfortunately resulted in the loss of the family business. The family was now very publicly pursuing litigation. For a company that depended on thousands of employees, investors, and independent agents who sold the insurance plans, this reputational risk was a serious threat. On top of this immediate crisis, all signs in the industry were pointing to the fact that the LTC business itself was not viable, yet over the years Conseco had acquired a number of LTC insurance providers. Students are asked to analyze not only what Prieur's priorities should be in addressing the immediate crisis but also the risks inherent in the LTC industry and how this might affect Conseco's success as a business moving forward.

Walker, Russell and Greg Merkley. 2017. Chipotle Mexican Grill: Food with Integrity?. Case 5-316-501 (KEL979).

By any measure, Chipotle Mexican Grill was a success story in the restaurant business. It grew from one location in 1993 to over 2,000 locations by 2016 and essentially created the fast casual dining category. Its stock appreciated more than 1,000% in the ten years following its 2006 IPO.

However, after more than 20 years without a major reported food safety incident, Chipotle was revealed as the source of multiple outbreaks of illness from norovirus, salmonella, and E. coli that sickened nearly 600 people in 13 states in 2015. The company closed stores, spent several months under investigation by the U.S. Centers for Disease Control and Prevention (CDC) and other health organizations, and faced a criminal investigation in connection with the incidents.

After a much-publicized closing of all of its stores on February 8, 2016, and numerous changes to its food sourcing and preparation practices, Chipotle tried to win back customers with dramatically increased advertising and free food promotions.

However, on April 26, the chain announced its first-ever quarterly loss as a public company. Same-store sales for the first quarter were 29.7% lower than in the previous year. Operating margins fell from 27.5% to 6.8% over the same period, and the company’s share price was down 41% from its summer 2015 high.

Walker, Russell, Mark Jeffery, Linus So, Sripad Sriram, Jon Nathanson, Joao Ferreira and Julia Feldmeier. 2010. Netflix Leading with Data: The Emergence of Data-Driven Video. Case 5-110-006 (KEL473).

By 2009 Netflix had all but trounced its traditional bricks-and-mortar competitors in the video rental industry. Since its founding in the late 1990s, the company had changed the face of the industry and threatened the existence of such entrenched giants as Blockbuster, in large part because of its easy-to-understand subscription model, policy of no late fees, and use of analytics to leverage customer data to provide a superior customer experience and grow its e-commerce media platform. Netflix’s investment in data collection, IT systems, and advanced analytics such as proprietary data mining techniques and algorithms for customer and product matching played a crucial role in both its strategy and success.

However, the explosive growth of the digital media market presents a serious challenge for Netflix’s business going forward. How will its analytics, customer data, and customer interaction models play a role in the future of the digital media space? Will it be able to stand up to competition from more seasoned players in the digital market, such as Amazon and Apple? What position must Netflix take in order to successfully compete in this digital arena?

Walker, Russell. 2013. Scandal at Société Générale: Rogue Trader or Willing Accomplice?. Case 5-313-505 (KEL766).

This case covers the scandal that occurred in 2008 at Société Générale when one trader, Jérôme Kerviel, lost the prominent French bank nearly €5 billion through his unauthorized trading. The case describes Kerviel’s schemes as well as SocGen’s internal monitoring and reporting processes, organizational structures, and culture so that students reading the case can identify and discuss the shortcomings of the firm’s risk management practices. The case and epilogue also describe the French government’s and Finance Minister Christine Lagarde’s reactions to the scandal (e.g., imposition of a €4 million fine and increased regulations), prompting students to consider the role of government in overseeing that healthy risk management practices are followed in key industries (such as banking) that are highly entwined with entire economies. Finally, the case encourages students—during class discussion—to critically consider whether it is truly possible for one rogue trader to act alone, which elements in a work environment enable or even encourage risky behavior, and who should be held accountable when such scandals occur. Interestingly, this case highlights a story that is not unique. Prior to Kerviel’s transgressions were the similar scandals of Nick Leeson at Barings Bank and Toshihide Iguchi at Daiwa Bank, yet history has repeated itself. This case gives students a vivid example of the dangers of internal, self-inflicted risk on organizations, and it opens a discussion on how to avoid it.

Walker, Russell and Joanna Wilson. 2016. Horse Trading: Food Sourcing in the Twenty-First Century. Case 5-216-250 (KEL945).

In January 2013, Irish authorities were the first to uncover the year's first food sourcing scandal: horsemeat sold as beef on supermarket shelves. It was not long before regulators and retailers realized the problem was truly a continental one. The incident involved French exporters, Luxembourger production facilities, Cypriot and Dutch meat traders, British and Swedish retailers, and Romanian horsemeat. Food service providers and retailers were forced to test beef products to ensure they were horse-free, pulling products that contained traces of equine meat. British supermarkets alone disposed of an estimated 10 million "beef" burgers in the wake of the scandal.

This case is an example of the challenges of managing the complex global supply chains that make up the modern food industry. In this class discussion, students will use concepts from management, economics, and public policy to assess the damage of this event and to analyze strategies for preventing similar incidents in the future.

Walker, Russell and Joanna Wilson. 2012. Nokia’s Supply Chain Management. Case 5-111-007 (KEL673).

In March 2000 a fire broke out at the Royal Philips Electronics plant, damaging its supply of semiconductor chips. Nokia Corporation and Ericsson LM relied on these chips to produce their cell phones; together they received 40 percent of the plant’s chip production. Both companies were about to release new cell phone designs that required the chips.

At Nokia, word of the setback spread quickly up the chain of command. Nokia’s team, which had a crisis plan in place, sprang into action. With an aggressive, multipronged strategy, Nokia avoided any cell phone production loss.

In contrast, the low-level technician who received the information at Ericsson did not notify his supervisors about the fire until early April and had to scramble to locate new sources for the chips. This search delayed production and proved a fatal blow to Ericsson’s independent production of mobile phones.

Nokia’s handling of its supply chain disruption provides a dramatic example of how a company’s strategic risk management can alleviate financial disaster and lay the groundwork for success in the future. Perturbations in supply chain management are inevitable, and grow harder and harder to assess as the marketplace becomes more globalized.

Walker, Russell, Israel Feuerberg, Lorena Sanchez Garcia and Santiago Trevino Villasenor. 2017. CEMEX: Information Technology, an Enabler for Building the Future. Case 5-315-502 (KEL992).

The case examines the role of IT in CEMEX, a giant Mexican building materials manufacturer in an industry categorized by low margins and high costs. In the early 1990s, CEMEX made significant investments in its IT systems, resulting in a data-based management operation that put it at the forefront of the industry. As the company grew through acquisitions, it integrated IT through "The CEMEX Way," a set of standardized processes, organizations, and systems implemented on a common IT platform.

In 2007, when CEMEX acquired Rinker, a major Australian concrete company, aligning Rinker with CEMEX IT systems was critical to quickly streamline operations and realize efficiencies. The CIO of CEMEX had developed a new integration process called Processes & IT (P&IT) that he was considering using for the Rinker integration. However, P&IT required additional resources, including significant upfront fixed costs and investment in new personnel teams at a time when the company was already struggling with the integration of another acquisition. CEMEX could either align Rinker to The CEMEX Way or use the opportunity to invest significantly more in evolving to the new P&IT approach that focused on business process management.

Walker, Russell and Tom Davenport. "LinkingIN to Data Products." Wall Street Journal.

Every so often we notice an interesting infographic using LinkedIn Corp. data. What universities, for example, are the primary feeders for tech employers like Apple Inc. (turns out it’s San Jose State) and Microsoft Corp. (University of Washington by a landslide)? What company internships lead to good jobs in different industries? (most are predictable, but surprises include Plante Moran in accounting, Protiviti in management consulting, and Persistent Systems in computer software) And for the inevitable holiday PR offering, what do professional Santa Clauses do when it’s not the holidays? (marketing event manager is the most likely role). These may seem like amusing ways to spend your time when you are tired of watching cat videos, but they are actually indicative of some serious business value. The infographics are summaries of what companies can do with data products. One of us (Tom) has written columns about data products on this site, and the other (Russ) has recently written a book on the topic called From Big Data to Big Profits. Incidentally, making data products has been enormously profitable for LinkedIn. It credits data products with $450M in additional revenue for 2013, and that doesn’t count very successful “internal” data products like People You May Know, to which the company credits half its memberships. We think that LinkedIn is an excellent example of how to make money from data products. Its offerings are an essentially free service to most of its members, of course, but it generates revenue from data products and premium services. The data generated through the normal use of the network is an incredibly rich source of insight, and advertisers, search firms, and premium users are willing to pay for LinkedIn’s valuable data products. For example, if we choose to get a premium account, we can find out exactly who has seen our profiles. If we were professional headhunters, we could pay to get even more specific information, such as all the robotics engineers who graduated from Northwestern University in 2004. And if we were writers or editors (the infographic on tech feeder schools was published by Wired magazine) or university administrators, we could look for connections between specific schools or degrees and actual careers, to the point of calculating the potential ROI for any given degree. Despite this success, we think that LinkedIn could go even further to make its amazing data more valuable. It has a data products group within the company, but at least when Tom visited a few years ago, it had a pretty unstructured process for data product creation. Some of the company’s most successful data products came from outside the group. That’s not terribly surprising, because with 364 million members across 200 countries, the company has way more data than a small data products group (and an additional data science group) can deal with. In fact, it’s a bigger resource than all of LinkedIn’s 7600 employees can take advantage of. So we’d argue that LinkedIn should create an institute—perhaps called the LinkedInstitute—of external people who can help to analyze all this data and extract value from it. We’re sure that some of the knowledge generated could be monetized in some fashion, and perhaps even more importantly, the world would learn a lot. How useful would it be to know, for example, what educational preparation is most likely to lead to rapid promotion? What jobs are great stepping stones for a fantastic career? What places should you live if you want to be successful in different industries? What training is most useful and who needs it most (rationalizing in part LinkedIn’s acquisition of Lynda)? With personalized data, LinkedIn could even recommend the next best career move for individuals. These could all be extremely useful and valuable types of information. Russ found in his research on data products that some of the most successful providers of them share a lot of data. Uber Technologies Inc. and Airbnb Inc., for example, are successful in large part because they share a lot of data—normally for free—with their drivers and service providers. They’ve developed digital platforms just for that purpose. Both companies are worth an amazing amount of money for privately-held firms, and we’d argue that their information sharing is a key component of their value. Sharing to create the network of users, as in the case of LinkedIn, Uber and Airbnb, has led to more valuable data products that are ultimately sold back to those same users, while also attracting new participants in the network. So it makes sense to look to LinkedIn as a model for data products, but we think that even that company—and other successful examples of this phenomenon—have only scratched the surface of what is to be done. There is a massive amount of value in the data that online (and offline, for that matter) firms have accumulated. Unlocking it and creating new offerings based on it can become a key growth area for individual firms and our entire economy. Thomas H. Davenport is a Distinguished Professor at Babson College, a Research Fellow at the Center for Digital Business, Director of Research at the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics. Russell Walker, Ph.D. is a Clinical Associate Professor at the Kellogg School of Management of Northwestern University. This article originally appeared in the Wall Street Journal on July 22, 2015.

Walker, Russell. "Monetizing Big Data For Big Profits: It Takes More Than Algorithms." Forbes.

The process of monetizing Big Data is really an exploration, driven by experimentation and identification of value. Here are a few points to keep in mind: 1. Look for Patterns in the Data – before trying to find the needle in the haystack, look for the patterns that describe customers, markets and operations that are directly linked to your decisions and investments. Look for the data to support big decisions, first! Such patterns can lead directly to wide-scale improvements and increase firm performance. It is about big hits. Before addressing finer points in complexity, look for answers to fundamental business questions: when, why, how, and through whom do your customers buy your products. For financial service firms this has been the vein of gold that has led to risk-based pricing and now on-line coupons. For eBay, the analysis is about popular products, successful sellers, and tracking customer preferences. money2. Allow and Encourage Your Data Science Team to Experiment – opportunities in data will not be self- evident. This will require exploration, time, and investment. Just like a stock analyst is expected to spend a great deal of time in research to find a few winners, expect your data science team to explore and to experiment to find the nuggets of value, too! With data scientists being in such high demand, this extra use of data scientists might be hard to justify. Liberating them of the coding and mundane analytical work (in part) needed by the firm for tactical work will be challenging. However, it will be important to do so if you want to achieve strategic goals of monetizing data. 3. Examine what Your Data Says about Assets – Just like Zillow has amassed a large data set about home prices, attracting the interest of outside users, including homeowners, home buyers, realtors and tax assessors (among others), consider who else might be interested in your data and who you can attract. If the data is not directly actionable to you, would others find it valuable? If so, consider strategies for selling the data or making it available to other parties via data products. 4. Form Data Products – Internally and Externally – Only very sophisticated teams are able and willing to buy raw data. They are also unlikely to pay high prices because they will expect to spend the time extracting the value or bringing the data to market. When leveraging data for value, it needs to be transformed into a data product that answers questions about the business. Internally, this is often about a resource allocation – where to market more? What to sell? What to make? For an external user of data, the questions are often about market performance and how they did relative to a competitor. eBay, for instance, has data products on how sellers perform and what products are selling where and at what prices. This creating of data products has many similarities to creating physical products. The product must be conceived, developed, marketed, sold, managed, and updated to create value for the user (and buyer). Zillow, Netflix, Google, eBay, and LinkedIn have all successfully created data products that help users. These data products are evolving in the market and change based on customer needs. Monetizing data will not be a one-stop operation but rather an on-going process. Recognizing that these steps must in place to monetize data is important. These steps suggest functions and requirements that are not often part of an analytical or data science team. Firms that broaden their vision and use of the data will lead to more value. These important steps in monetizing Big Data in the digital economy and more are developed in my recent book, From Big Data to Big Profits: Success with Data and Analytics. The book examines the evolving nature of Big Data and how businesses can leverage it to create new monetization opportunities. Using case studies on Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leading-edge users of Big Data, the book also explores how digital platforms, including mobile apps and social networks, are changing customer interactions and expectations, as well as the way Big Data is created and managed by companies. Companies looking to develop a Big Data strategy will find great value in the SIGMA framework, which assesses companies for Big Data readiness and provides direction on the steps necessary to get the most from Big Data.

Walker, Russell. 2014. Menus of Change Annual Report. An Initiative of the Harvard School of Public Health and the Culinary Institute of America. Menus of Change.

Menus of Change Annual Report. An Initiative of the Harvard School of Public Health and the Culinary Institute of America FOOD SUPPLY CHAIN TRANSPARENCY AND RESILIENCY In 2013, the food industry was rocked by controversial and large-scale food supply cases: a horsemeat scandal in Europe and the export of tainted milk to seven countries. Both cases demonstrate how food sourcing is highly globalized and why accurate labeling and better food traceability are more important than ever.

Walker, Russell. 2013. Winning with Risk Management. World Scientific Publishing Company.

This book develops the notion that companies can succeed on the basis of risk management, much as companies compete on efficiency, costs, labor, location, and other dimensions that provide advantages. The reality of risk and how it impacts companies is that it is definite, often catastrophic and looks like a shock to the firm. This is striking, as a difference between firms on risk management can be more definite and impactful than a difference in operating efficiencies, for example. Those successful with risk are more clearly identified and the spoils are more clearly and immediately claimed. Winning with risk management requires discipline and a commitment to using information in decisions. More specifically, it requires recognizing shocks in industries and when competitors are poorly prepared so that action can be taken. Winning with risk also requires protecting owned assets and guarding against threats and reputational risks. This book will examine how leading firms that compete on risk have successfully done so. Through select case studies, this book showcases best practices in making risk management a competitive advantage in an enterprise. The cases further suggest that the competitive advantage from risk management also has implication on the capital structure of firms and their organizational formation. The competitive use of risk is not simply based on a set of algorithms, but rather encompasses how the enterprise deals with uncertainty, how it gathers data and transforms such data into meaningful risk information. The use of risk information requires that organizations seek and examine disconfirming information and promote a culture for decision-making that is open to such disconfirming information. This book will also examine how organizations must develop, treat, and communicate risk information for the purposes of winning with risk management.

Walker, Russell and Rafique Jiwani. 2015. Reinventing E-Commerce: Amazon's Bet on Unmanned Vehicle Delivery. Case 5-315-501 (KEL911).

In a December 1, 2013, interview on American television program 60 Minutes, Amazon CEO Jeff Bezos announced that Amazon would soon change the future of online shopping by enabling customers to receive items within thirty minutes of ordering. This delivery service, Bezos said, would be powered by unmanned autonomous drones and could be offered as soon as 2015. The market reaction was instantaneous and positive.

Still, Amazon needed some answers before it could launch autonomous delivery services: Were customers ready to embrace and pay for this type of delivery service? Would regulators allow it? Should Amazon make or buy its drones? Would it be too risky for Amazon to wait to launch this service? If it decided to go ahead, how should it launch, and to whom?

Spanish translation available.

Walker, Russell. 2013. Maxxed Out: TJX Companies and the Largest-Ever Consumer Data Breach. Case 5-313-507 (KEL764).

In November 2005 Fidelity Homestead, a savings bank in Louisiana, began noticing suspicious charges from Mexico and southern California on its customers’ credit cards. More than a year later, an audit revealed peculiarities in the credit card data in the computer systems of TJX Companies, the parent company of more than 2,600 discount fashion and home accessories retail stores in the United States, Canada, and Europe.

The U.S. Secret Service, the U.S. Justice Department, and the Royal Canadian Mounted Police found that hackers had penetrated TJX’s systems in mid-2005, accessing information that dated as far back as 2003. TJX had violated industry security standards by failing to update its in-store wireless networks and by storing credit card numbers and expiration dates without adequate encryption. When TJX announced the intrusion in January 2007, it admitted that hackers had compromised nearly 46 million debit and credit card numbers, the largest-ever data breach in the United States.

Schmedders, Karl, Russell Walker and Michael Stritch. 2010. Arbor City Community Foundation (A): The Foundation. Case 5-310-502(A) (KEL585).

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the Fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the Fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the Value-at-Risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses.

The questions in part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF’s risk management.

In part (B) the foundation receives a major donation. As a result the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund’s new portfolio and to perform a portfolio rebalancing analysis.

Walker, Russell. 2016. Bank of America: Consumers Fight Back. Case 5-116-001 (KEL947).

On October 6, 2011, President Barack Obama publicly scolded Bank of America for developing a new revenue stream: a $5 monthly fee for all Bank of America debit card holders, which the bank had announced a month earlier. It was a strategy for replacing lost "swipe fee" revenue following the passage of the Dodd-Frank Act and accompanying Durbin Amendment, which capped swipe fees at 21 cents per transaction. This was the culmination of three tumultuous years for the world's largest financial services firm, but would not be the end of its public affairs challenges.

The president's public critique of Bank of America came in response to—and helped exacerbate—consumer anger about the bank's monthly fee, changes across the banking sector, and general discontent with Wall Street. Bank of America's situation was complicated further by ongoing legal action following acquisitions of Merrill Lynch and Countrywide, which hurt the firm's shareholders and led to large-scale employee layoffs.

In this case study, students will be challenged to analyze how Bank of America could have better managed the competing interests of different stakeholders, including shareholders, employees, regulators, customers, and the public.

Schmedders, Karl, Russell Walker and Michael Stritch. 2010. Arbor City Community Foundation (B): Managing Good Fortune. Case 5-310-502(B) (KEL586).

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the Fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the Fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the Value-at-Risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses.

The questions in part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF’s risk management.

In part (B) the foundation receives a major donation. As a result the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund’s new portfolio and to perform a portfolio rebalancing analysis.

Walker, Russell and Kyle Bell. 2015. Nestlé Ice Cream in Cuba. Case 5-315-504 (KEL919).

In 1996, as the Castro regime began welcoming limited international investment back to Cuba, Nestlé signed a letter of intent with the Cuban government to build an ice cream factory in Havana’s El Cotorro neighborhood. The plant, a joint venture between the Cuban government and Nestlé, would produce high-quality ice cream products for tourists and affluent Cubans.

Nearly twenty years after this decision to enter the Cuban market, it is not clear how successful the investment has been and what the future might hold for Nestlé on the island. Nestlé has faced important challenges in Cuba—such as supply shortages, entrenched domestic competitors, and risk of government interference—but there has been evidence of some marketing and financial success. The 2015 normalization of diplomatic relations may bring new strategic threats and opportunities as American companies begin to eye the Cuban market and current competitors prepare for market changes.

In the case, students will evaluate Nestle’s investment and strategy for future growth in the Cuban market and consider the company’s market entry strategy, operations, and finances.

Walker, Russell. 2014. Conseco: Market Assumptions and Risk. Case 5-311-509 (KEL796).

In March 2007 C. James Prieur, CEO of insurance provider Conseco, was faced with a crisis. The front page of the New York Times featured a story on the grieving family of an elderly woman who had faithfully paid for her Conseco long-term care (LTC) policy, only to find that it would not pay her claims. Her family had to pay for her care (until her recent death), which unfortunately resulted in the loss of the family business. The family was now very publicly pursuing litigation. For a company that depended on thousands of employees, investors, and independent agents who sold the insurance plans, this reputational risk was a serious threat. On top of this immediate crisis, all signs in the industry were pointing to the fact that the LTC business itself was not viable, yet over the years Conseco had acquired a number of LTC insurance providers. Students are asked to analyze not only what Prieur's priorities should be in addressing the immediate crisis but also the risks inherent in the LTC industry and how this might affect Conseco's success as a business moving forward.

Walker, Russell and Greg Merkley. 2017. Chipotle Mexican Grill: Food with Integrity?. Case 5-316-501 (KEL979).

By any measure, Chipotle Mexican Grill was a success story in the restaurant business. It grew from one location in 1993 to over 2,000 locations by 2016 and essentially created the fast casual dining category. Its stock appreciated more than 1,000% in the ten years following its 2006 IPO.

However, after more than 20 years without a major reported food safety incident, Chipotle was revealed as the source of multiple outbreaks of illness from norovirus, salmonella, and E. coli that sickened nearly 600 people in 13 states in 2015. The company closed stores, spent several months under investigation by the U.S. Centers for Disease Control and Prevention (CDC) and other health organizations, and faced a criminal investigation in connection with the incidents.

After a much-publicized closing of all of its stores on February 8, 2016, and numerous changes to its food sourcing and preparation practices, Chipotle tried to win back customers with dramatically increased advertising and free food promotions.

However, on April 26, the chain announced its first-ever quarterly loss as a public company. Same-store sales for the first quarter were 29.7% lower than in the previous year. Operating margins fell from 27.5% to 6.8% over the same period, and the company’s share price was down 41% from its summer 2015 high.

Walker, Russell, Mark Jeffery, Linus So, Sripad Sriram, Jon Nathanson, Joao Ferreira and Julia Feldmeier. 2010. Netflix Leading with Data: The Emergence of Data-Driven Video. Case 5-110-006 (KEL473).

By 2009 Netflix had all but trounced its traditional bricks-and-mortar competitors in the video rental industry. Since its founding in the late 1990s, the company had changed the face of the industry and threatened the existence of such entrenched giants as Blockbuster, in large part because of its easy-to-understand subscription model, policy of no late fees, and use of analytics to leverage customer data to provide a superior customer experience and grow its e-commerce media platform. Netflix’s investment in data collection, IT systems, and advanced analytics such as proprietary data mining techniques and algorithms for customer and product matching played a crucial role in both its strategy and success.

However, the explosive growth of the digital media market presents a serious challenge for Netflix’s business going forward. How will its analytics, customer data, and customer interaction models play a role in the future of the digital media space? Will it be able to stand up to competition from more seasoned players in the digital market, such as Amazon and Apple? What position must Netflix take in order to successfully compete in this digital arena?

Walker, Russell. 2013. Scandal at Société Générale: Rogue Trader or Willing Accomplice?. Case 5-313-505 (KEL766).

This case covers the scandal that occurred in 2008 at Société Générale when one trader, Jérôme Kerviel, lost the prominent French bank nearly €5 billion through his unauthorized trading. The case describes Kerviel’s schemes as well as SocGen’s internal monitoring and reporting processes, organizational structures, and culture so that students reading the case can identify and discuss the shortcomings of the firm’s risk management practices. The case and epilogue also describe the French government’s and Finance Minister Christine Lagarde’s reactions to the scandal (e.g., imposition of a €4 million fine and increased regulations), prompting students to consider the role of government in overseeing that healthy risk management practices are followed in key industries (such as banking) that are highly entwined with entire economies. Finally, the case encourages students—during class discussion—to critically consider whether it is truly possible for one rogue trader to act alone, which elements in a work environment enable or even encourage risky behavior, and who should be held accountable when such scandals occur. Interestingly, this case highlights a story that is not unique. Prior to Kerviel’s transgressions were the similar scandals of Nick Leeson at Barings Bank and Toshihide Iguchi at Daiwa Bank, yet history has repeated itself. This case gives students a vivid example of the dangers of internal, self-inflicted risk on organizations, and it opens a discussion on how to avoid it.

Walker, Russell and Joanna Wilson. 2016. Horse Trading: Food Sourcing in the Twenty-First Century. Case 5-216-250 (KEL945).

In January 2013, Irish authorities were the first to uncover the year's first food sourcing scandal: horsemeat sold as beef on supermarket shelves. It was not long before regulators and retailers realized the problem was truly a continental one. The incident involved French exporters, Luxembourger production facilities, Cypriot and Dutch meat traders, British and Swedish retailers, and Romanian horsemeat. Food service providers and retailers were forced to test beef products to ensure they were horse-free, pulling products that contained traces of equine meat. British supermarkets alone disposed of an estimated 10 million "beef" burgers in the wake of the scandal.

This case is an example of the challenges of managing the complex global supply chains that make up the modern food industry. In this class discussion, students will use concepts from management, economics, and public policy to assess the damage of this event and to analyze strategies for preventing similar incidents in the future.

Walker, Russell and Joanna Wilson. 2012. Nokia’s Supply Chain Management. Case 5-111-007 (KEL673).

In March 2000 a fire broke out at the Royal Philips Electronics plant, damaging its supply of semiconductor chips. Nokia Corporation and Ericsson LM relied on these chips to produce their cell phones; together they received 40 percent of the plant’s chip production. Both companies were about to release new cell phone designs that required the chips.

At Nokia, word of the setback spread quickly up the chain of command. Nokia’s team, which had a crisis plan in place, sprang into action. With an aggressive, multipronged strategy, Nokia avoided any cell phone production loss.

In contrast, the low-level technician who received the information at Ericsson did not notify his supervisors about the fire until early April and had to scramble to locate new sources for the chips. This search delayed production and proved a fatal blow to Ericsson’s independent production of mobile phones.

Nokia’s handling of its supply chain disruption provides a dramatic example of how a company’s strategic risk management can alleviate financial disaster and lay the groundwork for success in the future. Perturbations in supply chain management are inevitable, and grow harder and harder to assess as the marketplace becomes more globalized.

Walker, Russell, Israel Feuerberg, Lorena Sanchez Garcia and Santiago Trevino Villasenor. 2017. CEMEX: Information Technology, an Enabler for Building the Future. Case 5-315-502 (KEL992).

The case examines the role of IT in CEMEX, a giant Mexican building materials manufacturer in an industry categorized by low margins and high costs. In the early 1990s, CEMEX made significant investments in its IT systems, resulting in a data-based management operation that put it at the forefront of the industry. As the company grew through acquisitions, it integrated IT through "The CEMEX Way," a set of standardized processes, organizations, and systems implemented on a common IT platform.

In 2007, when CEMEX acquired Rinker, a major Australian concrete company, aligning Rinker with CEMEX IT systems was critical to quickly streamline operations and realize efficiencies. The CIO of CEMEX had developed a new integration process called Processes & IT (P&IT) that he was considering using for the Rinker integration. However, P&IT required additional resources, including significant upfront fixed costs and investment in new personnel teams at a time when the company was already struggling with the integration of another acquisition. CEMEX could either align Rinker to The CEMEX Way or use the opportunity to invest significantly more in evolving to the new P&IT approach that focused on business process management.