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      Analytics and Data ScienceRemove Analytics and Data Science →

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      • July 2020
      • Case

      Applying Data Science and Analytics at P&G

      By: Srikant M. Datar, Sarah Mehta and Paul Hamilton
      Set in December 2019, this case explores how P&G has applied data science and analytics to cut costs and improve outcomes across its business units. The case provides an overview of P&G’s approach to data management and governance, and reviews the challenges associated... View Details
      Keywords: Data Science; Analytics; Analysis; Information; Information Management; Information Types; Innovation and Invention; Strategy; Analytics and Data Science; Consumer Products Industry; United States; Ohio
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      Datar, Srikant M., Sarah Mehta, and Paul Hamilton. "Applying Data Science and Analytics at P&G." Harvard Business School Case 121-006, July 2020.
      • June 2020
      • Background Note

      Customer Management Dynamics and Cohort Analysis

      By: Elie Ofek, Barak Libai and Eitan Muller
      The digital revolution has allowed companies to amass considerable amounts of data on their customers. Using this information to generate actionable insights is fast becoming a critical skill that firms must master if they wish to effectively compete and win in today’s... View Details
      Keywords: Cohort Analysis; Customers; Analytics and Data Science; Segmentation; Analysis; Customer Value and Value Chain
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      Ofek, Elie, Barak Libai, and Eitan Muller. "Customer Management Dynamics and Cohort Analysis." Harvard Business School Background Note 520-122, June 2020.
      • 2021
      • Working Paper

      The Project on Impact Investments' Impact Investment Database

      By: M. Diane Burton, Shawn Cole, Abhishek Dev, Christina Jarymowycz, Leslie Jeng, Josh Lerner, Fanele Mashwama, Yue (Cynthia) Xu and T. Robert Zochowski
      Impact investing has grown significantly over the past 15 years. From a niche investing segment with only $25 billion AUM in 2013 (WEF 2013), it experienced double-digit growth and developed into a market with an estimated $502 billion AUM (Mudaliapar and Dithrich... View Details
      Keywords: Impact Investing; Investment; Analytics and Data Science; Analysis
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      Burton, M. Diane, Shawn Cole, Abhishek Dev, Christina Jarymowycz, Leslie Jeng, Josh Lerner, Fanele Mashwama, Yue (Cynthia) Xu, and T. Robert Zochowski. "The Project on Impact Investments' Impact Investment Database." Harvard Business School Working Paper, No. 20-117, May 2020. (Revised August 2021.)
      • May 8, 2020
      • Article

      Which Covid-19 Data Can You Trust?

      By: Satchit Balsari, Caroline Buckee and Tarun Khanna
      The COVID-19 pandemic has produced a tidal wave of data, but how much of it is any good? And as a layperson, how can you sort the good from the bad? The authors suggest a few strategies for dividing the useful data from the misleading: Beware of data that’s too broad... View Details
      Keywords: COVID-19 Pandemic; Health Pandemics; Analytics and Data Science
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      Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
      • May 2020
      • Article

      Inventory Auditing and Replenishment Using Point-of-Sales Data

      By: Achal Bassamboo, Antonio Moreno and Ioannis Stamatopoulos
      Spoilage, expiration, damage due to employee/customer handling, employee theft, and customer shoplifting usually are not reflected in inventory records. As a result, records often report phantom inventory, i.e., units of good not available for sale. We derive an... View Details
      Keywords: Shelf Availability; Inventory Record Inaccuracy; Optimal Replenishment; Retail Analytics; Performance Effectiveness; Analysis; Mathematical Methods
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      Bassamboo, Achal, Antonio Moreno, and Ioannis Stamatopoulos. "Inventory Auditing and Replenishment Using Point-of-Sales Data." Production and Operations Management 29, no. 5 (May 2020): 1219–1231.
      • 2020
      • Article

      Public Sentiment and the Price of Corporate Sustainability

      By: George Serafeim
      Combining corporate sustainability performance scores based on environmental, social, and governance (ESG) data with big data measuring public sentiment about a company’s sustainability performance, I find that the valuation premium paid for companies with strong... View Details
      Keywords: Sustainability; ESG; ESG (Environmental, Social, Governance) Performance; Investment Management; Investment Strategy; Big Data; Machine Learning; Environment; Environmental Sustainability; Corporate Governance; Performance; Asset Pricing; Investment; Management; Strategy; Human Capital; Public Opinion; Value; Analytics and Data Science
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      Serafeim, George. "Public Sentiment and the Price of Corporate Sustainability." Financial Analysts Journal 76, no. 2 (2020): 26–46.
      • April 2020
      • Case

      Ment.io: Knowledge Analytics for Team Decision Making

      By: Yael Grushka-Cockayne, Jeffrey T. Polzer, Susie L. Ma and Shlomi Pasternak
      Ment.io was a software platform that used proprietary data analytics technology to help organizations make informed and transparent decisions based on team input. Ment was born out of founder Joab Rosenberg’s frustration that, while organizations collected ever... View Details
      Keywords: Decision Making; Information Technology; Knowledge; Knowledge Acquisition; Knowledge Management; Operations; Information Management; Product; Product Development; Entrepreneurship; Business Startups; Communications Industry; Information Industry; Information Technology Industry; Web Services Industry; Middle East; Israel
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      Grushka-Cockayne, Yael, Jeffrey T. Polzer, Susie L. Ma, and Shlomi Pasternak. "Ment.io: Knowledge Analytics for Team Decision Making." Harvard Business School Case 420-078, April 2020.
      • March 2020 (Revised June 2022)
      • Case

      GreenLight Fund

      By: Brian Trelstad, Julia Kelley and Mel Martin
      As Tara Noland, the Executive Director (ED) of GreenLight Cincinnati, reflected on her first few years on the job. Noland had delivered on what she had been hired to do in the city: work with leading philanthropists and nonprofit executives to use data and evidence to... View Details
      Keywords: Philanthropy; Venture Philanthropy; Replication; Philanthropy and Charitable Giving; Venture Capital; Social Issues; Decision Making; Analytics and Data Science; Cincinnati
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      Trelstad, Brian, Julia Kelley, and Mel Martin. "GreenLight Fund." Harvard Business School Case 320-053, March 2020. (Revised June 2022.)
      • March 2020
      • Supplement

      People Analytics at Teach For America (B)

      By: Jeffrey T. Polzer and Julia Kelley
      This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, situated one year after the A case, Managing Director Michael Metzger must decide how to apply his team's predictive models generated from the previous year’s data. View Details
      Keywords: Analytics; Human Resource Management; Data; Workforce; Hiring; Talent Management; Forecasting; Predictive Analytics; Organizational Behavior; Recruiting; Analytics and Data Science; Forecasting and Prediction; Recruitment; Selection and Staffing; Talent and Talent Management
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      Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (B)." Harvard Business School Supplement 420-086, March 2020.
      • 2021
      • Working Paper

      Corporate Environmental Impact: Measurement, Data and Information

      By: David Freiberg, DG Park, George Serafeim and T. Robert Zochowski
      As an organization’s environmental impact has become a central societal consideration, thereby affecting industry and organizational competitiveness, interest in measuring and analyzing environmental impact has increased. We develop a methodology to derive comparable... View Details
      Keywords: Environment; Impact; Measurement; Environmental Ratings; Corporate Valuation; Financial Materiality; Sustainability; Environmental Impact; Environmental Strategy; Impact-Weighted Accounts; IWAI; Environmental Sustainability; Corporate Social Responsibility and Impact; Measurement and Metrics; Valuation
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      Freiberg, David, DG Park, George Serafeim, and T. Robert Zochowski. "Corporate Environmental Impact: Measurement, Data and Information." Harvard Business School Working Paper, No. 20-098, March 2020. (Revised February 2021.)
      • March 2020
      • Article

      Diagnosing Missing Always at Random in Multivariate Data

      By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
      Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
      Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
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      Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
      • 2020
      • Book

      The Power of Experiments: Decision-Making in a Data-Driven World

      By: Michael Luca and Max H. Bazerman
      Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of changes to an... View Details
      Keywords: Experiments; Randomized Controlled Trials; Organizations; Decision Making; Analytics and Data Science; Management Analysis, Tools, and Techniques
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      Luca, Michael, and Max H. Bazerman. The Power of Experiments: Decision-Making in a Data-Driven World. Cambridge, MA: MIT Press, 2020.
      • 2020
      • Working Paper

      A General Theory of Identification

      By: Iavor Bojinov and Guillaume Basse
      What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree on a definition in the context of parametric statistical models — roughly, a parameter θ in a model P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective.... View Details
      Keywords: Identification; Econometric Models; Analytics and Data Science; Theory
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      Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
      • February 2020
      • Technical Note

      Talent Management and the Future of Work

      By: William R. Kerr and Gorick Ng
      The nature of work is changing—and it is changing rapidly. Few days go by without industry giants such as Amazon and AT&T announcing plans to invest billions of dollars towards retraining nearly half of their respective workforces for jobs of the future. What changes... View Details
      Keywords: Human Resource Management; Human Capital Development; Human Resource Practices; Talent; Talent Acquisition; Talent Development; Talent Development And Retention; Talent Management; Talent Retention; Labor Flows; Labor Management; Labor Market; Strategy Development; Strategy Management; Strategy Execution; Strategy And Execution; Strategic Change; Transformations; Organization; Organization Alignment; Organization Design; Organizational Adaptation; Organizational Effectiveness; Management Challenges; Management Of Business And Political Risk; Change Leadership; Future Of Work; Future; Skills Gap; Skills Development; Skills; Offshoring And Outsourcing; Investment; Capital Allocation; Work; Work Culture; Work Force Management; Work/life Balance; Work/family Balance; Work-family Boundary Management; Workers; Worker Productivity; Worker Performance; Work Engagement; Work Environment; Work Environments; Productivity; Organization Culture; Soft Skills; Technology Management; Technological Change; Technological Change: Choices And Consequences; Technology Diffusion; Disruptive Technology; Global Business; Global; Workplace; Workplace Context; Workplace Culture; Workplace Wellness; Collaboration; Competencies; Productivity Gains; Digital; Digital Transition; Competitive Dynamics; Competitiveness; Competitive Strategy; Data Analytics; Data; Data Management; Data Strategy; Data Protection; Aging Society; Diversity; Diversity Management; Millennials; Communication Complexity; Communication Technologies; International Business; Work Sharing; Global Competitiveness; Global Corporate Cultures; Intellectual Property; Intellectual Property Management; Intellectual Property Protection; Intellectual Capital And Property Issues; Globalization Of Supply Chain; Inequality; Recruiting; Hiring; Hiring Of Employees; Training; Job Cuts And Outsourcing; Job Performance; Job Search; Job Design; Job Satisfaction; Jobs; Employee Engagement; Employee Attitude; Employee Benefits; Employee Compensation; Employee Fairness; Employee Relationship Management; Employee Retention; Employee Selection; Employee Motivation; Employee Feedback; Employee Coordination; Employee Performance Management; Employee Socialization; Process Improvement; Application Performance Management; Stigma; Institutional Change; Candidates; Digital Enterprise; Cultural Adaptation; Cultural Change; Cultural Diversity; Cultural Context; Cultural Strategies; Cultural Psychology; Cultural Reform; Performance; Performance Effectiveness; Performance Management; Performance Evaluation; Performance Appraisal; Performance Feedback; Performance Measurement; Performance Metrics; Performance Measures; Performance Efficiency; Efficiency; Performance Analysis; Performance Appraisals; Performance Improvement; Automation; Artificial Intelligence; Technology Companies; Managerial Processes; Skilled Migration; Assessment; Human Resources; Management; Human Capital; Talent and Talent Management; Retention; Demographics; Labor; Strategy; Change; Change Management; Transformation; Organizational Change and Adaptation; Organizational Culture; Working Conditions; Information Technology; Technology Adoption; Disruption; Economy; Competition; Globalization; AI and Machine Learning; Digital Transformation
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      Kerr, William R., and Gorick Ng. "Talent Management and the Future of Work." Harvard Business School Technical Note 820-084, February 2020.
      • February 2020 (Revised April 2021)
      • Case

      StockX: The Stock Market of Things

      By: Chiara Farronato, John J. Horton, Annelena Lobb and Julia Kelley
      Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust... View Details
      Keywords: Markets; Auctions; Bids and Bidding; Demand and Consumers; Consumer Behavior; Analytics and Data Science; Market Design; Digital Platforms; Market Transactions; Marketplace Matching; Supply and Industry; Analysis; Price; Product Marketing; Product Launch; Apparel and Accessories Industry; Apparel and Accessories Industry; North and Central America; United States; Michigan; Detroit
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      Farronato, Chiara, John J. Horton, Annelena Lobb, and Julia Kelley. "StockX: The Stock Market of Things." Harvard Business School Case 620-062, February 2020. (Revised April 2021.)
      • 2020
      • Book

      Experimentation Works: The Surprising Power of Business Experiments

      By: Stefan Thomke
      Don’t fly blind. See how the power of experiments works for you. When it comes to improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. They discover that intuition,... View Details
      Keywords: Experimentation; Experiments; Market Research; Innovation and Invention; Innovation and Management; Customers; Research
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      Thomke, Stefan. Experimentation Works: The Surprising Power of Business Experiments. Boston, MA: Harvard Business Review Press, 2020.
      • January 2020
      • Case

      Banorte Móvil: Data-Driven Mobile Growth

      By: Ayelet Israeli, Carla Larangeira and Mariana Cal
      In mid-2019, Carlos Hank was deliberating over the results for Banorte Móvil—the mobile application for Banorte, Mexico’s most profitable and second-largest financial institution. Hank, who had been appointed as Banorte´s Chairman of the Board in January 2015, had... View Details
      Keywords: Data Analytics; Customer Lifetime Value; Financial Institutions; Mobile and Wireless Technology; Growth and Development Strategy; Customers; Technology Adoption; Communication Strategy; Banking Industry; Mexico; Latin America
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      Israeli, Ayelet, Carla Larangeira, and Mariana Cal. "Banorte Móvil: Data-Driven Mobile Growth." Harvard Business School Case 520-068, January 2020.
      • January 2020 (Revised July 2020)
      • Supplement

      MoviePass: The 'Get Big Fast' Strategy

      By: Benjamin C. Esty and Daniel Fisher
      In August 2017, MoviePass dramatically lowered its subscription price from $50 per month to just $10 for up to one movie per day. The idea was to rapidly scale the business to the point where they could generate incremental revenue streams form related businesses... View Details
      Keywords: Market Entry; Growth Strategy; Profit Vs. Growth; Subscription Business; Cash Burn; Data Analytics; Get-big-fast; Buyer Power; Strategy Implementation; Movie Industry; Racing; Business Strategy; Value Creation; Consolidation; Cash Flow; Growth Management; Business Startups; Entrepreneurship; Disruptive Innovation; Mobile Technology; Motion Pictures and Video Industry; Motion Pictures and Video Industry; Motion Pictures and Video Industry; Motion Pictures and Video Industry; United States
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      Esty, Benjamin C., and Daniel Fisher. "MoviePass: The 'Get Big Fast' Strategy." Harvard Business School Spreadsheet Supplement 720-854, January 2020. (Revised July 2020.)
      • Article

      Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error

      By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
      Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
      Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
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      Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
      • May 2020
      • Article

      Scalable Holistic Linear Regression

      By: Dimitris Bertsimas and Michael Lingzhi Li
      We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
      Keywords: Mathematical Methods; Analytics and Data Science
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      Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
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