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- Faculty Publications (93)
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- All HBS Web (222)
- Faculty Publications (93)
- 2016
- Working Paper
The Impact of Supplier Inventory Service Level on Retailer Demand
By: Nathan Craig, Nicole DeHoratius and Ananth Raman
To set inventory service levels, suppliers must understand how changes in inventory service level affect demand. We build on prior research, which uses analytical models and laboratory experiments to study the impact of a supplier's service level on demand from... View Details
Keywords: Customer Satisfaction; Forecasting and Prediction; Learning; Consumer Behavior; Service Delivery; Performance Expectations; Apparel and Accessories Industry; Service Industry
Craig, Nathan, Nicole DeHoratius, and Ananth Raman. "The Impact of Supplier Inventory Service Level on Retailer Demand." Working Paper. (Revised January 2016.)
- 19 Jan 2021
- Working Paper Summaries
The Value of Descriptive Analytics: Evidence from Online Retailers
- 2010
- Book
The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance
By: Marshall Fisher and Ananth Raman
Retailers today are drowning in data but lacking in insight: They have huge volumes of information at their disposal. But they're unsure of how to sort through it and use it to make smart decisions. The result? They're struggling with profit-sapping supply chain... View Details
Keywords: Profit; Knowledge Use and Leverage; Logistics; Supply Chain Management; Mathematical Methods; Retail Industry
Fisher, Marshall, and Ananth Raman. The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance. Harvard Business Press, 2010.
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- 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; Retail Industry; Retail Industry; Retail Industry; Retail Industry; United States; Canada; North America
Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
- 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; Retail Industry; United States
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.)
- Article
Integration of Online and Offline Channels in Retail: The Impact of Sharing Reliable Inventory Availability Information
By: Santiago Gallino and Antonio Moreno
Using a proprietary data set, we analyze the impact of the implementation of a “buy-online, pick-up-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can... View Details
Keywords: Retail Operations; Inventory Availability; Empirical Operations Management; Business Analytics; Online Retail; Ecommerce; Operations; Management; Distribution Channels; Consumer Behavior; E-commerce; Retail Industry
Gallino, Santiago, and Antonio Moreno. "Integration of Online and Offline Channels in Retail: The Impact of Sharing Reliable Inventory Availability Information." Management Science 60, no. 6 (June 2014): 1434–1451. (Finalist of Management Science Best Paper award in Operations Management.)
- 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
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.
- September 2020 (Revised March 2022)
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details
Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Retail Industry; Retail Industry; Retail Industry; United States; Ohio
Ferreira, Kris, and Srikanth Jagabathula. "JOANN: Joannalytics Inventory Allocation Tool." Harvard Business School Case 621-055, September 2020. (Revised March 2022.)
- April 2015 (Revised March 2017)
- Case
Instacart and the New Wave of Grocery Startups
By: John Deighton and Leora Kornfeld
Instacart is testing an Uber-style solution to the challenge of building a home-delivered grocery business. It is backed by $220 million of venture funding. Will this model succeed where businessses like Webvan failed? What are the questions that this exploratory... View Details
Keywords: Food Retailing; Outsourced Grocery Delivery; Online Ordering; Dynamic Pricing; Data Analytics; Marketing Strategy; Food; Distribution Channels; Business Startups; Food and Beverage Industry; California
Deighton, John, and Leora Kornfeld. "Instacart and the New Wave of Grocery Startups." Harvard Business School Case 515-089, April 2015. (Revised March 2017.)
- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Retail Industry; Retail Industry; Retail Industry; Retail Industry; United States
Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
- 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
- October 2021 (Revised June 2022)
- Case
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; AI; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
Israeli, Ayelet. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Case 522-046, October 2021. (Revised June 2022.)
- November 2021 (Revised December 2021)
- Supplement
PittaRosso (B): Human and Machine Learning
By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case. View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
Israeli, Ayelet. "PittaRosso (B): Human and Machine Learning." Harvard Business School Supplement 522-047, November 2021. (Revised December 2021.)
- October 2021 (Revised March 2022)
- Supplement
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli and Fabrizio Fantini
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; Retail Industry; Italy
- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
- March 2019
- Case
HOPI: Turkey's Shopping Companion
By: Sunil Gupta, Donald Ngwe and Gamze Yucaoglu
The case opens in 2017 as Onur Erbay, CEO of HOPI, a multi-vendor loyalty platform, is contemplating a critical decision. The case chronicles the origins of Boyner Group, the parent company of HOPI and a major retailer in Turkey, and development of retail and customer... View Details
Keywords: Loyalty Programs; Multi-vendor Platform; Retail; Big Data; Customer Relationship Management; Mobile and Wireless Technology; Business Model; Analytics and Data Science; Competitive Strategy; Decision Making; Applications and Software; Digital Platforms; Retail Industry; Retail Industry; Turkey
Gupta, Sunil, Donald Ngwe, and Gamze Yucaoglu. "HOPI: Turkey's Shopping Companion." Harvard Business School Case 519-057, March 2019.
- Research Summary
Overview
Professor Israeli utilizes econometric methods and field experiments to study pricing and channel management. Her current research examines how the prevalence of the online channel affects both the interactions between manufacturers and their downstream channel... View Details
- Research Summary
Overview
Professor Israeli utilizes econometric methods and field experiments to study pricing and channel management. Her current research examines how the prevalence of the online channel affects both the interactions between manufacturers and their downstream channel... View Details
- September 2022 (Revised November 2022)
- Teaching Note
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
Teaching Note for HBS Case No. 522-046. View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy