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      Analytics and Data ScienceRemove Analytics and Data Science →

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      • November 2018
      • Case

      Komatsu Komtrax: Asset Tracking Meets Demand Forecasting

      By: Willy Shih, Paul Hong and YoungWon Park
      Komatsu's Komtrax system started as a way of remotely monitoring and tracking equipment for the purpose of improving operational efficiency. This case follows its evolution towards other uses including demand forecasting for its sales, marketing, and production... View Details
      Keywords: Big Data; Manufacturing; Manufacturing Industry; Data Strategy; Internet Of Things; Construction; Production; Analytics and Data Science; Strategy; Performance Efficiency; Forecasting and Prediction; Industrial Products Industry; Construction Industry; Japan
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      Shih, Willy, Paul Hong, and YoungWon Park. "Komatsu Komtrax: Asset Tracking Meets Demand Forecasting." Harvard Business School Case 619-022, November 2018.
      • November 2018
      • Article

      Global Evidence on Economic Preferences

      By: Armin Falk, Anke Becker, Thomas Dohmen, Benjamin Enke, David Huffman and Uwe Sunde
      This article studies the global variation in economic preferences. For this purpose, we present the Global Preference Survey (GPS), an experimentally validated survey data set of time preference, risk preference, positive and negative reciprocity, altruism, and trust... View Details
      Keywords: Economic Preferences; Economics; Behavior; Surveys; Analytics and Data Science; Global Range
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      Falk, Armin, Anke Becker, Thomas Dohmen, Benjamin Enke, David Huffman, and Uwe Sunde. "Global Evidence on Economic Preferences." Quarterly Journal of Economics 113, no. 4 (November 2018): 1645–1692.
      • November 2018
      • Case

      Sportradar (A): From Data to Storytelling

      By: Ramon Casadesus-Masanell, Karen Elterman and Oliver Gassmann
      In 2013, the Swiss sports data company Sportradar debated whether to expand from its core business of data provision to bookmakers into sports media products. Sports data was becoming a commodity, and in the future, sports leagues might reduce their dependence on... View Details
      Keywords: Sports Data; Data; Sport; Sportradar; Football; Soccer; Gambling; Betting; Betting Markets; Statistics; Odds; Live Data; Bookmakers; Betradar; Visualization; Integrity; Monitoring; Gaming; Streaming; 2013; St.Gallen; Algorithm; Mathematical Modeling; Carsten Koerl; Betandwin; Bwin; Wagering; Probability; Sports; Analytics and Data Science; Mathematical Methods; Games, Gaming, and Gambling; Transition; Strategy; Media; Media and Broadcasting Industry; Media and Broadcasting Industry; Media and Broadcasting Industry; Media and Broadcasting Industry; Europe; Switzerland; Asia; Austria; Germany; England
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      Casadesus-Masanell, Ramon, Karen Elterman, and Oliver Gassmann. "Sportradar (A): From Data to Storytelling." Harvard Business School Case 719-429, November 2018.
      • October 2018 (Revised August 2023)
      • Case

      Safecast: Bootstrapping Human Capital to Big Data

      By: Ethan Bernstein and Stephanie Marton
      On March 11, 2011, at 2:46pm, a 9.1-on-the-Richter-scale, six-minute long earthquake unleashed a tsunami that ravaged the Tohoku region of Japan, damaging the Fukushima Daiichi Nuclear Power facility and releasing sufficient radioactive material into the air and ocean... View Details
      Keywords: Citizen Science; Creative Commons; Open Data; Open Architecture; Volunteer-based Organization; Fukushima Daiichi Nuclear Power Facility; 311; Nuclear; Radiation; Crowdsourcing; Bgeigie; Geiger Counters; Kickstarter; Sustainability; Sustainable Business And Innovation; Design; Energy Generation; Social Entrepreneurship; Human Capital; Innovation and Invention; Crisis Management; Organizational Structure; Organizational Design; Information Technology; Business Model; Energy Industry; Technology Industry; Japan; North and Central America; Europe
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      Bernstein, Ethan, and Stephanie Marton. "Safecast: Bootstrapping Human Capital to Big Data." Harvard Business School Case 419-033, October 2018. (Revised August 2023.)
      • October 2018
      • Case

      BreezoMeter: Making Air Pollution Data Actionable

      By: Frank V. Cespedes, Allison M. Ciechanover and Margot Eiran
      The case focuses on an Israeli startup that provides actionable air pollution data and forecasts. The company has over 50 enterprise customers and its tool reached a million people daily in 67 countries. The co-founders wrestle with which markets and customers to focus... View Details
      Keywords: Startups; Entrepreneurship; Business Startups; Pollutants; Analytics and Data Science; Sales; Marketing; Decision Choices and Conditions; Technology Industry; Israel; United States
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      Cespedes, Frank V., Allison M. Ciechanover, and Margot Eiran. "BreezoMeter: Making Air Pollution Data Actionable." Harvard Business School Case 819-058, October 2018.
      • October 2018
      • Case

      Fundraising at St. Camillus Hospital

      By: Srikant M. Datar and Caitlin N. Bowler
      St. Camillus is a fictional non-profit hospital in rural Maine facing a serious budget deficit. As Director of Marketing, Victoria Stern is building a team to modernize the hospital fundraising efforts. An interview with a promising candidate, who is also a digital... View Details
      Keywords: Data Analysis; Data Privacy; Data Governance; Non-profit; Health Care; Fundraising; Data Security; Analytics and Data Science; Safety; Governance; Ethics; Health Care and Treatment; Cybersecurity
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      Datar, Srikant M., and Caitlin N. Bowler. "Fundraising at St. Camillus Hospital." Harvard Business School Case 119-027, October 2018.
      • October 2018 (Revised July 2023)
      • Case

      Innovation at Uber: The Launch of Express POOL

      By: Chiara Farronato, Alan MacCormack and Sarah Mehta
      Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This product offers a reduced price to riders willing to carpool, walk a short distance to/from their pick-up and drop-off points, and wait a... View Details
      Keywords: Innovation and Management; Innovation Leadership; Innovation Strategy; Technological Innovation; Information Technology; Mobile and Wireless Technology; Applications and Software; Digital Platforms; Decision Making; Technology Industry; California; San Francisco
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      Farronato, Chiara, Alan MacCormack, and Sarah Mehta. "Innovation at Uber: The Launch of Express POOL." Harvard Business School Case 619-003, October 2018. (Revised July 2023.)
      • 2018
      • Book

      The Gift of Global Talent: How Migration Shapes Business, Economy & Society

      By: William R. Kerr
      The global race for talent is on, with countries and businesses competing for the best and brightest. Foreign talent has transformed U.S. science and engineering, reshaped the economy, and influenced society at large. But America is bogged down in thorny debates on... View Details
      Keywords: Immigration; Policy; Labor; Economy; Talent and Talent Management; United States
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      Kerr, William R. The Gift of Global Talent: How Migration Shapes Business, Economy & Society. Stanford, CA: Stanford Business Books, 2018.
      • 2020
      • Working Paper

      Machine Learning for Pattern Discovery in Management Research

      By: Prithwiraj Choudhury
      Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
      Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
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      Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
      • September 2018
      • Case

      Verisk: Trailblazing in the Big Data Jungle

      By: Andrew Wasynczuk, Francesca Gino and Karim Sameh
      This case revolves around Verisk Analytics' initiatives to drive innovation throughout the firm's many business verticals. Verisk, originally named ISO, started life as an insurance rating agency in the early 1970s, acting as an intermediary between insurance companies... View Details
      Keywords: Verisk; Argus; Wood Mackenzie; Insurance; Energy; Analytics; Data; Big Data; Acquisitions; Acquisition Strategy; Innovation; Organic Growth; Innovation Strategy; Innovation Leadership; Technological Innovation; Acquisition; Growth and Development Strategy; Analytics and Data Science; Insurance Industry; Energy Industry; Consulting Industry; United States; United Kingdom; New York (state, US); England
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      Wasynczuk, Andrew, Francesca Gino, and Karim Sameh. "Verisk: Trailblazing in the Big Data Jungle." Harvard Business School Case 919-014, September 2018.
      • September 2018
      • Article

      Assembling the Sales Team

      By: Frank V. Cespedes
      Data and analytical tasks have lengthened productivity ramp-up times in many sales contexts, making each hire a bigger sunk cost for a longer time. Most companies adopt two common practices: They hire on the basis of “experience” and/or look at their best reps and try... View Details
      Keywords: Sales; Selection and Staffing
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      Cespedes, Frank V. "Assembling the Sales Team." Top Sales Magazine (September 2018).
      • Article

      The Critical Role of Second-order Normative Beliefs in Predicting Energy Conservation

      By: Jon M. Jachimowicz, Oliver P. Hauser, Julia D. O'Brien, Erin Sherman and Adam D. Galinsky
      Sustaining large-scale public goods requires individuals to make environmentally friendly decisions today to benefit future generations. Recent research suggests that second-order normative beliefs are more powerful predictors of behaviour than first-order personal... View Details
      Keywords: Climate Change; Energy; Environmental Sustainability; Household; Behavior; Values and Beliefs; Forecasting and Prediction
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      Jachimowicz, Jon M., Oliver P. Hauser, Julia D. O'Brien, Erin Sherman, and Adam D. Galinsky. "The Critical Role of Second-order Normative Beliefs in Predicting Energy Conservation." Nature Human Behaviour 2, no. 10 (October 2018): 757–764.
      • Article

      Uninformed Consent

      By: Leslie K. John
      Companies want access to more and more of your personal data—from where you are to what’s in your DNA. Can they unlock its value while respecting consumers’ privacy? View Details
      Keywords: Personal Data; Privacy; Customers; Analytics and Data Science; Ethics; Governing Rules, Regulations, and Reforms
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      John, Leslie K. "Uninformed Consent." Special Issue on The Big Idea: Tracked. Harvard Business Review (website) (September–October 2018).
      • Third Quarter 2018
      • Article

      Why and How Investors Use ESG Information: Evidence from a Global Survey

      By: Amir Amel-Zadeh and George Serafeim
      Using survey data from a sample of senior investment professionals from mainstream (i.e., not SRI funds) investment organizations, we provide insights into why and how investors use reported environmental, social, and governance (ESG) information. Relevance to... View Details
      Keywords: ESG; ESG (Environmental, Social, Governance) Performance; Sustainability; Investment Management; Investment Strategy; Metrics; Standard Setting; Accounting Standards; Finance; Investment; Information; Environmental Sustainability; Governance; Performance Effectiveness; Strategy
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      Amel-Zadeh, Amir, and George Serafeim. "Why and How Investors Use ESG Information: Evidence from a Global Survey." Financial Analysts Journal 74, no. 3 (Third Quarter 2018): 87–103.
      • August 2018 (Revised September 2018)
      • Case

      Predicting Purchasing Behavior at PriceMart (A)

      By: Srikant M. Datar and Caitlin N. Bowler
      This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
      Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction
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      Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (A)." Harvard Business School Case 119-025, August 2018. (Revised September 2018.)
      • August 2018 (Revised September 2018)
      • Supplement

      Predicting Purchasing Behavior at PriceMart (B)

      By: Srikant M. Datar and Caitlin N. Bowler
      Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details
      Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction
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      Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (B)." Harvard Business School Supplement 119-026, August 2018. (Revised September 2018.)
      • August 2018 (Revised April 2019)
      • Case

      Chateau Winery (A): Unsupervised Learning

      By: Srikant M. Datar and Caitlin N. Bowler
      This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups... View Details
      Keywords: Clustering; Data Science; Analytics and Data Science; Customers; Marketing; Analysis
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      Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
      • August 2018 (Revised April 2019)
      • Supplement

      Chateau Winery (B): Supervised Learning

      By: Srikant M. Datar and Caitlin N. Bowler
      This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
      Keywords: Data Science; Clustering; Analytics and Data Science; Customers; Marketing; Analysis
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      Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
      • August 2018 (Revised September 2018)
      • Case

      LendingClub (A): Data Analytic Thinking (Abridged)

      By: Srikant M. Datar and Caitlin N. Bowler
      LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
      Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model
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      Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.)
      • August 2018 (Revised September 2018)
      • Supplement

      LendingClub (B): Decision Trees & Random Forests

      By: Srikant M. Datar and Caitlin N. Bowler
      This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
      ... View Details
      Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
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      Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, August 2018. (Revised September 2018.)
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