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  • All HBS Web  (1,722)
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    • News  (318)
    • Research  (1,047)
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  • All HBS Web  (1,722)
    • People  (9)
    • News  (318)
    • Research  (1,047)
    • Events  (15)
    • Multimedia  (10)
  • Faculty Publications  (859)
← Page 8 of 1,722 Results →
  • 13 Aug 2014
  • News

A Whole-Brain Approach to Marketing

Keywords: data analytics; creativity; marketing
  • August 2015 (Revised January 2017)
  • Technical Note

From Correlation to Causation

By: Feng Zhu and Karim R. Lakhani
To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details
Keywords: Statistics; Regression; Data Analytics; Decisions; Forecasting and Prediction; Judgments
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Zhu, Feng, and Karim R. Lakhani. "From Correlation to Causation." Harvard Business School Technical Note 616-009, August 2015. (Revised January 2017.)
  • December 2013
  • Article

How Google Sold Its Engineers on Management

By: David A. Garvin
High-performing knowledge workers often question whether managers actually contribute much, especially in a technical environment. Until recently, that was the case at Google, a company filled with self-starters who viewed management as more destructive than beneficial... View Details
Keywords: Organizational Behavior; Human Resource Management; Managing Change; Organizational Change; Analytics; Management; Leadership; Human Resources; Talent and Talent Management
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Garvin, David A. "How Google Sold Its Engineers on Management." R1312D. Harvard Business Review 91, no. 12 (December 2013): 74–82.
  • March 2018 (Revised August 2018)
  • Case

Matching Markets for Googlers

By: Bo Cowgill and Rembrand Koning
This case describes how Google designed and launched an internal matching market to assign individual workers with projects and managers. The case evaluates how marketplace design considerations—and several alternative staffing models—could affect the company’s goals... View Details
Keywords: People Analytics; Google; Labor Market; Staffing; Market Design; Marketplace Matching; Selection and Staffing; Goals and Objectives; Technology Industry; United States
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Cowgill, Bo, and Rembrand Koning. "Matching Markets for Googlers." Harvard Business School Case 718-487, March 2018. (Revised August 2018.) (More about Bo Cowgill.)
  • February 2021 (Revised February 2021)
  • Background Note

eGrocery and the Role of Data for CPG Firms

By: Ayelet Israeli, Fedor (Ted) Lisitsyn and Mark A. Irwin
This notes provides information about the eGrocery industry and how traditional CPG companies handle this channel and potential data. It is recommended to use together with a series of exercises entitled: "E-Commerce Analytics for CPG Firms (A), (B), and (C)." View Details
Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Optimization; Analytics and Data Science; Analysis; Customer Value and Value Chain; Marketing Channels; E-commerce; Retail Industry; Consumer Products Industry; United States
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Israeli, Ayelet, Fedor (Ted) Lisitsyn, and Mark A. Irwin. "eGrocery and the Role of Data for CPG Firms." Harvard Business School Background Note 521-077, February 2021. (Revised February 2021.)
  • March 2016
  • Supplement

Advertising Experiments at RestaurantGrades

By: Weijia Dai, Hyunjin Kim and Michael Luca
This exercise provides students with a data set consisting of results from a hypothetical experiment, and asks students to make recommendations based on the data. Through this process, the exercise teaches students to analyze, design, and interpret experiments. The... View Details
Keywords: Experimental Methods; Analytics; Web Technology; Marketing; Digital Marketing; Analysis; Performance Effectiveness; Social Media
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Dai, Weijia, Hyunjin Kim, and Michael Luca. "Advertising Experiments at RestaurantGrades." Harvard Business School Spreadsheet Supplement 916-702, March 2016.
  • Research Summary

Overview

By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data... View Details
Keywords: Channel Management; Pricing; Pricing Policies; Online Marketing; E-commerce; Analytics; Econometrics; Field Experiments; Data Analytics; Artificial Intelligence; Value Of Data
  • October 2015 (Revised October 2016)
  • Case

Building Watson: Not So Elementary, My Dear! (Abridged)

By: Willy C. Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the... View Details
Keywords: Analytics; Big Data; Business Analytics; Product Development Strategy; Machine Learning; Machine Intelligence; Artificial Intelligence; Product Development; AI and Machine Learning; Information Technology; Analytics and Data Science; Information Technology Industry; United States
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Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)
  • 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.)
  • February 2017 (Revised August 2018)
  • Case

Sarah Powers at Automated Precision Products

By: Jeffrey T. Polzer, Michael Norris, Julia Kelley and Kristina Tobio
In 2017, Sarah Powers, VP of Sales at an automation hardware firm, is trying to understand why some members of her sales team have been underperforming. She is tasked with analyzing her firm’s email and calendar data to try to find relationships between communications... View Details
Keywords: People Analytics; Sales Attainment; Communication Networks; Data; Human Resources; Business Processes; Sales; Communication; Analytics and Data Science; Analysis; Industrial Products Industry; Manufacturing Industry; United States
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Polzer, Jeffrey T., Michael Norris, Julia Kelley, and Kristina Tobio. "Sarah Powers at Automated Precision Products." Harvard Business School Case 417-072, February 2017. (Revised August 2018.)
  • January 2017 (Revised January 2017)
  • Case

Susan Cassidy at Bertram Gilman International

By: Jeffrey T. Polzer and Michael Norris
In 2016, Susan Cassidy, VP of sales and marketing for the packaged foods division at CPG firm Bertram Gilman International, has to make a promotion decision. Should she choose the person she has been grooming for the position or another candidate recommended by central... View Details
Keywords: People Analytics; Algorithms; Promotion Decision; Human Resources; Business Processes; Consumer Products Industry; United States
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Polzer, Jeffrey T., and Michael Norris. "Susan Cassidy at Bertram Gilman International." Harvard Business School Case 417-053, January 2017. (Revised January 2017.)
  • July 2013
  • Case

Sample6: Innovating to Make Food Safer

By: Robert F. Higgins and Kirsten Kester
Tim Curran, CEO of Sample6, a start-up biotechnology company developing a novel food safety diagnostics platform, must decide how to partner with food industry players. How can he best convince leaders in this mature industry to adopt a new technology and improve food... View Details
Keywords: Data Analytics; Food Safety; Biotechnology; Nutrition; Entrepreneurship; Product; Partners and Partnerships; Food; Technological Innovation; Business Startups; Governing Rules, Regulations, and Reforms; Product Development; Agribusiness; Information Technology; Globalization; Performance Improvement; Safety; Technology Adoption; Agriculture and Agribusiness Industry; Food and Beverage Industry; Biotechnology Industry; Information Industry; United States; Boston; Massachusetts
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Higgins, Robert F., and Kirsten Kester. "Sample6: Innovating to Make Food Safer." Harvard Business School Case 814-014, July 2013.
  • February 2021
  • Tutorial

Getting Started in RStudio Cloud

By: Chiara Farronato and Caleb Kwon
This video provides an introduction to the free programming language R using an online cloud version of RStudio, which is the most popular editor and interface for writing and executing R code. The video begins by providing a brief background of R and RStudio and... View Details
Keywords: Data Analysis; Data Analytics; Experiment; Experimental Design; Analytics and Data Science; Analysis; Applications and Software
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Farronato, Chiara, and Caleb Kwon. Getting Started in RStudio Cloud. Harvard Business School Tutorial 621-708, February 2021.
  • 22 May 2014
  • News

For Website Personalization, Simple Is the New Sexy

Keywords: web analytics; customer data; web personalization
  • January 2021 (Revised February 2021)
  • Case

Tech with a Side of Pizza: How Domino's Rose to the Top

By: Boris Groysberg, Sarah L. Abbott and Susan Seligson
After hitting an all-time low in 2008, Domino’s Pizza underwent a vigorous rebranding, product development, and embraced innovative technologies to become the world’s leading international fast-food retailer. Domino’s considered itself as much a tech company as it was... View Details
Keywords: Digital Marketing; Digital Technology; Innovation; Scaling; Data Analytics; Turnaround; Technological Innovation; Information Technology; Strategy; Management; Marketing; Operations; Human Resources; Entrepreneurship; Change Management; Analysis; Performance; Customers; Growth and Development; Competitive Advantage; Employees; Training; Leadership Development; Food and Beverage Industry; Technology Industry; United States
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Groysberg, Boris, Sarah L. Abbott, and Susan Seligson. "Tech with a Side of Pizza: How Domino's Rose to the Top." Harvard Business School Case 421-057, January 2021. (Revised February 2021.)
  • Teaching Interest

Data Science and Artificial Intelligence for Leaders

By: Chiara Farronato
With artificial intelligence (AI)... View Details
Keywords: Data Science; Data Science And Analytics Management; Data Analytics; Data Analysis; Artificial Intelligence; Generative Ai; Generative Models
  • Article

Algorithms Need Managers, Too

By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details
Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science
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Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
  • Spring 2016
  • Article

Has Social Science Taken Over Electoral Campaigns and Should We Regret It?

By: Vincent Pons
Keywords: Data Analytics; Elections; Electoral Campaigns; Persuasion; Randomized Experiments
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Pons, Vincent. "Has Social Science Taken Over Electoral Campaigns and Should We Regret It?" French Politics, Culture and Society 34, no. 1 (Spring 2016): 34–47.
  • February 2021
  • Tutorial

T-tests: Theory and Practice

By: Michael Parzen, Natalie Epstein, Chiara Farronato and Michael Toffel
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with... View Details
Keywords: Data Analysis; Data Analytics; Experiment Design; Experimentation; Analytics and Data Science; Analysis
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Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021.
  • August 2020
  • Technical Note

Comparing Two Groups: Sampling and t-Testing

By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
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Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
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