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    • All HBS Web  (1,989)
      • Faculty Publications  (524)

      Analytics and Data ScienceRemove Analytics and Data Science →

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      • January–February 2018
      • Article

      Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far

      By: Leslie John, Tami Kim and Kate Barasz
      Data gathered on the web has vastly enhanced the capabilities of marketers. With people regularly sharing personal details online and internet cookies tracking every click, companies can now gain unprecedented insight into individual consumers and target them with... View Details
      Keywords: Digital Marketing; Customization and Personalization; Information; Customers; Attitudes
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      John, Leslie, Tami Kim, and Kate Barasz. "Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far." Harvard Business Review 96, no. 1 (January–February 2018): 62–69.
      • January 2018
      • Article

      Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life

      By: Edward L. Glaeser, Scott Duke Kominers, Michael Luca and Nikhil Naik
      New, "big" data sources allow measurement of city characteristics and outcome variables at higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big data has the most value for... View Details
      Keywords: Analytics and Data Science; Urban Scope; City
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      Glaeser, Edward L., Scott Duke Kominers, Michael Luca, and Nikhil Naik. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life." Economic Inquiry 56, no. 1 (January 2018): 114–137.
      • Article

      Mitigating Bias in Adaptive Data Gathering via Differential Privacy

      By: Seth Neel and Aaron Leon Roth
      Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated... View Details
      Keywords: Bandit Algorithms; Bias; Analytics and Data Science; Mathematical Methods; Theory
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      Neel, Seth, and Aaron Leon Roth. "Mitigating Bias in Adaptive Data Gathering via Differential Privacy." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
      • December 2017
      • Teaching Note

      Yemeksepeti: Growing and Expanding the Business Model through Data

      By: William R. Kerr and Alexis Brownell
      Teaching Note for HBS No. 817-095. View Details
      Keywords: Turkey; Internet; Online Ordering; Restaurants; Big Data; Entrepreneurship; Analytics and Data Science; Internet and the Web; Growth and Development Strategy; Food and Beverage Industry; Turkey
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      Kerr, William R., and Alexis Brownell. "Yemeksepeti: Growing and Expanding the Business Model through Data." Harvard Business School Teaching Note 818-076, December 2017.
      • Article

      Rethinking the Profession Formerly Known as Advertising: How Data Science Is Disrupting the Work of Agencies

      By: John A. Deighton
      The article discusses the notion of advertising as a profession in relation to the impact of digital analytics and data-driven marketing. Topics include the history of internet marketing, the investments of the content-driven internet firms Facebook Inc. and Google... View Details
      Keywords: Data Science; Digital Marketing; Marketing; Internet and the Web; Analytics and Data Science; Disruption
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      Deighton, John A. "Rethinking the Profession Formerly Known as Advertising: How Data Science Is Disrupting the Work of Agencies." Journal of Advertising Research 57, no. 4 (December 2017): 357–361.
      • November 28, 2017
      • Editorial

      Active Investing v.2.0

      By: Gabriel Karageorgiou and George Serafeim
      Keywords: Investment; Investing; Technology; Big Data; Quantitative Analysis; ESG; ESG (Environmental, Social, Governance) Performance; Sustainability; Analytics and Data Science
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      Karageorgiou, Gabriel, and George Serafeim. "Active Investing v.2.0." Pensions & Investments (online) (November 28, 2017).
      • November 2017
      • Teaching Note

      Predicting Consumer Tastes with Big Data at Gap

      By: Ayelet Israeli and Jill Avery
      CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
      Keywords: Brands; Brand & Product Management; Big Data; "Marketing Analytics"; Consumer Behavior; Predictive Analytics; Forecasting; Preferences; Operation Management; Distribution Channels; Marketing; Marketing Channels; Marketing Strategy; Brands and Branding; Forecasting and Prediction; Data and Data Sets; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States; North America
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      Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Teaching Note 518-053, November 2017.
      • 2017
      • Working Paper

      The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond

      By: Josh Lerner
      Patents and citations are powerful tools for understanding innovative activity inside the firm and are increasingly used in corporate finance research. But due to the complexities of patent data collection and the changing spatial and industry composition of innovative... View Details
      Keywords: Patents; Analytics and Data Science; Corporate Finance; Research; Problems and Challenges
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      Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond." Harvard Business School Working Paper, No. 18-042, November 2017.
      • October 2017
      • Case

      Quantopian: A New Model for Active Management

      By: Sara Fleiss, Adi Sunderam, Luis M. Viceira and Caitlin Carmichael
      Keywords: Big Data; Hedge Fund; Crowdsourcing; Investment Fund; Quantitative Hedge Fun; Algorithmic Data; Analytics and Data Science
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      Fleiss, Sara, Adi Sunderam, Luis M. Viceira, and Caitlin Carmichael. "Quantopian: A New Model for Active Management." Harvard Business School Case 218-046, October 2017.
      • October 2017 (Revised November 2017)
      • Case

      NYC311

      By: Constantine E. Kontokosta, Mitchell Weiss, Christine Snively and Sarah Gulick
      Joe Morrisroe, executive director for NYC311, had some gut instincts but no definitive answer to the question he was just asked by one of the mayor’s deputies: “Are some communities being underserved by 311? How do we know we are hearing from the right people?” Founded... View Details
      Keywords: New York City; NYC; 311; NYC311; Big Data; Equal Access; Bias; Data Analysis; Public Entrepreneurship; Urban Informatics; Predictive Analytics; Chief Data Officer; Data Analytics; Cities; City Leadership; Analytics and Data Science; Analysis; Prejudice and Bias; Entrepreneurship; Public Sector; City; Public Administration Industry; New York (city, NY)
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      Kontokosta, Constantine E., Mitchell Weiss, Christine Snively, and Sarah Gulick. "NYC311." Harvard Business School Case 818-056, October 2017. (Revised November 2017.)
      • October 2017 (Revised April 2018)
      • Case

      Improving Worker Safety in the Era of Machine Learning (A)

      By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
      Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
      Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States
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      Toffel, Michael W., Dan Levy, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (A)." Harvard Business School Case 618-019, October 2017. (Revised April 2018.)
      • October 2017 (Revised July 2018)
      • Case

      Data Science at Target

      By: Srikant M. Datar and Caitlin N. Bowler
      Paritosh Desai joined Target.com in 2013 as VP of Business Intelligence, Analytics & Testing to explore how the retailer could use its relatively small but thriving e-commerce arm to drive sales and win customers. The case explores the technological and organizational... View Details
      Keywords: Data Science; Analytics and Data Science; Organizational Change and Adaptation; Competitive Strategy; Problems and Challenges; Innovation Leadership
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      Datar, Srikant M., and Caitlin N. Bowler. "Data Science at Target." Harvard Business School Case 118-016, October 2017. (Revised July 2018.)
      • September 2017
      • Case

      Sensing (and Monetizing) Happiness at Hitachi

      By: Ethan Bernstein and Stephanie Marton
      Inspired by research linking happiness and productivity, Hitachi had invested in developing new “people analytics” technologies to help companies increase employee happiness. Hitachi had begun manufacturing high-tech badges that quantify a wearer’s activity patterns.... View Details
      Keywords: People Analytics; Japan; Sociometers; Wearables; Interpersonal Communication; Human Resources; Happiness; Technology Industry; Japan
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      Bernstein, Ethan, and Stephanie Marton. "Sensing (and Monetizing) Happiness at Hitachi." Harvard Business School Case 418-019, September 2017.
      • 2017
      • Chapter

      Venture Capital Data: Opportunities and Challenges

      By: Steven N. Kaplan and Josh Lerner
      This paper describes the available data and research on venture capital investments and performance. We comment on the challenges inherent in those data and research as well as possible opportunities to do better. View Details
      Keywords: Venture Capital; Analytics and Data Science; Research
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      Kaplan, Steven N., and Josh Lerner. "Venture Capital Data: Opportunities and Challenges." Chap. 10 in Measuring Entrepreneurial Businesses: Current Knowledge and Challenges. Vol. 75, edited by John Haltiwanger, Erik Hurst, Javier Miranda, and Antoinette Schoar. Studies in Income and Wealth (NBER). Chicago: University of Chicago Press, 2017.
      • August 2017 (Revised July 2019)
      • Case

      GROW: Using Artificial Intelligence to Screen Human Intelligence

      By: Ethan Bernstein, Paul McKinnon and Paul Yarabe
      Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro... View Details
      Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
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      Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.)
      • August 2017 (Revised December 2018)
      • Case

      Tamarin App: Natural Language Processing

      By: Srikant M. Datar and Caitlin N. Bowler
      In this case, students explore the challenges of using sentiment analysis to monitor and understand public perception around a software application, Tamarin SEO App. Technical topics include building a filtering classifier using naive Bayes and sentiment analysis This... View Details
      Keywords: Data Science; Branding; Data Analytics; Analytics and Data Science; Brands and Branding; Analysis; Perception; Planning
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      Datar, Srikant M., and Caitlin N. Bowler. "Tamarin App: Natural Language Processing." Harvard Business School Case 118-015, August 2017. (Revised December 2018.)
      • August 2017 (Revised August 2018)
      • Case

      Busbud: Building a Data Company

      By: Srikant M. Datar, Alistair Croll and Caitlin N. Bowler
      The case features the work of LP Maurice (HBS '08) as he decides to take on the fragmented bus travel industry and launch an online business that aggregates and shares bus schedules for routes around the world. His first challenge: finding that the data he needs is... View Details
      Keywords: Data Science; Analytics and Data Science; Business Startups; Knowledge Acquisition; Customers; Measurement and Metrics; Transportation Industry
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      Datar, Srikant M., Alistair Croll, and Caitlin N. Bowler. "Busbud: Building a Data Company." Harvard Business School Case 118-011, August 2017. (Revised August 2018.)
      • August 2017 (Revised August 2018)
      • Case

      The Oakland Athletics: Strategy & Metrics for a Budget

      By: Srikant M. Datar and Caitlin N. Bowler
      This case considers Oakland Athletics General Manager Billy Beane’s data driven and, in baseball circles unconventional, approach to winning games over the duration of the long Major League Baseball season. Beane’s critical approach to crafting strategy within his... View Details
      Keywords: Data Analysis; Metrics; Data Science; Analytics and Data Science; Analysis; Measurement and Metrics; Competitive Strategy; Organizational Culture; Sports Industry
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      Datar, Srikant M., and Caitlin N. Bowler. "The Oakland Athletics: Strategy & Metrics for a Budget." Harvard Business School Case 118-010, August 2017. (Revised August 2018.)
      • May 2017 (Revised March 2018)
      • Case

      Predicting Consumer Tastes with Big Data at Gap

      By: Ayelet Israeli and Jill Avery
      CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
      Keywords: Retailing; Preference Elicitation; Big Data; Predictive Analytics; Artificial Intelligence; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States; Canada; North America
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      Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
      • Article

      Selecting the Right Growth Metrics: Fewer but Better

      By: Leonard A. Schlesinger
      Keywords: Supply Chains; Big Data; Corporations; Franchising; Performance Metrics; Analytics and Data Science
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      Schlesinger, Leonard A. "Selecting the Right Growth Metrics: Fewer but Better." Stanford Social Innovation Review (website) (April 21, 2017).
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