harvard case study data

Case collection: Harvard Business Publishing

About Harvard Business Publishing

Headquartered in Boston, Massachusetts, Harvard Business Publishing (HBP) is the leading provider of teaching materials for management education.

HBP was founded in 1994 as a not-for-profit, wholly-owned subsidiary of Harvard University, reporting into Harvard Business School. HBP's mission is to improve the practice of management in a changing world. This mission influences how they approach what they do and what they believe is important.

With approximately 450 employees, primarily based in Boston, with offices in New York City, India, Singapore, Qatar and the United Kingdom, HBP serves as a bridge between academia and enterprises around the globe through its publications and multiple platforms for content delivery, and its reach into three markets: academic, corporate, and individual managers. HBP has a conventional governance structure comprising a  Board of Directors , an internal  Executive Committee , and Business Unit Directors.

About the collection

The Case Centre distributes a comprehensive range of materials including the complete collection of more than 7,500 Harvard Business School case studies, teaching notes, background notes, case videos, and a selection of software ancillaries.

Also included are:

• Brief Cases that are rigorous and compact with five-eight pages and three-four exhibits
• case studies that are popular for undergraduate-level courses
• executive education cases that provide rich yet efficient learning for managers at every level.

Additional top quality HBP teaching materials available from The Case Centre include:

• articles from the  Harvard Business Review  and other top management journals
• case method books from the Harvard Business School Press
• over 2,000  individual chapters  from popular Harvard Business School Press books
• newsletter articles  from Harvard Management Update, Strategy & Innovation, Negotiation, and Balanced Scorecard Report
• Core Curriculum Readings  that cover the foundational concepts, theories, and frameworks that business students must learn. Authored by faculty at Harvard Business School, each Reading includes a teaching note, related course materials, and exhibit slides. Many include test banks, practice questions, video clips, and Interactive Illustrations to enhance student comprehension of specific topics.

HBP also offer a number of free cases.  Browse here

Collection contact

For any queries related to the Harvard Business Publishing collection, please visit:

Travis Stewart e [email protected]

Browse the full collection Browse prize-winning cases

Available from the case centre.

The HBP collection of over 16,000 cases, and their accompanying instructor materials, software and videos, 7,000 management articles and 2,000 individual book chapters are available from The Case Centre.

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Materials from Harvard Business Publishing are not available to customers at corporate organisations or at organisations in China.

www.hbsp.harvard.edu/educators

Top ten bestselling cases

Browse the top ten bestselling cases from Harvard Business Publishing in 2023.

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What is the Case Study Method?

Overview Dropdown up

Overview dropdown down, celebrating 100 years of the case method at hbs.

The 2021-2022 academic year marks the 100-year anniversary of the introduction of the case method at Harvard Business School. Today, the HBS case method is employed in the HBS MBA program, in Executive Education programs, and in dozens of other business schools around the world. As Dean Srikant Datar's says, the case method has withstood the test of time.

Case Discussion Preparation Details Expand All Collapse All

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How Cases Unfold In the Classroom

How cases unfold in the classroom dropdown up, how cases unfold in the classroom dropdown down, preparation guidelines expand all collapse all, read the professor's assignment or discussion questions read the professor's assignment or discussion questions dropdown down, read the first few paragraphs and then skim the case read the first few paragraphs and then skim the case dropdown down, reread the case, underline text, and make margin notes reread the case, underline text, and make margin notes dropdown down, note the key problems on a pad of paper and go through the case again note the key problems on a pad of paper and go through the case again dropdown down, how to prepare for case discussions dropdown up, how to prepare for case discussions dropdown down, read the professor's assignment or discussion questions, read the first few paragraphs and then skim the case, reread the case, underline text, and make margin notes, note the key problems on a pad of paper and go through the case again, case study best practices expand all collapse all, prepare prepare dropdown down, discuss discuss dropdown down, participate participate dropdown down, relate relate dropdown down, apply apply dropdown down, note note dropdown down, understand understand dropdown down, case study best practices dropdown up, case study best practices dropdown down, participate, what can i expect on the first day dropdown down.

Most programs begin with registration, followed by an opening session and a dinner. If your travel plans necessitate late arrival, please be sure to notify us so that alternate registration arrangements can be made for you. Please note the following about registration:

HBS campus programs – Registration takes place in the Chao Center.

India programs – Registration takes place outside the classroom.

Other off-campus programs – Registration takes place in the designated facility.

What happens in class if nobody talks? Dropdown down

Professors are here to push everyone to learn, but not to embarrass anyone. If the class is quiet, they'll often ask a participant with experience in the industry in which the case is set to speak first. This is done well in advance so that person can come to class prepared to share. Trust the process. The more open you are, the more willing you’ll be to engage, and the more alive the classroom will become.

Does everyone take part in "role-playing"? Dropdown down

Professors often encourage participants to take opposing sides and then debate the issues, often taking the perspective of the case protagonists or key decision makers in the case.

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• 11 May 2021
• Working Paper Summaries

Time Dependency, Data Flow, and Competitive Advantage

The perishability of data has strategic implications for businesses that provide data-driven products and services. This paper illustrates how different business areas might differ with respect to the rate of decay in data value and the importance of data flow in their operations.

• 06 Apr 2020

A General Theory of Identification

Statistical inference teaches us how to learn from data, whereas identification analysis explains what we can learn from it. This paper proposes a simple unifying theory of identification, encouraging practitioners to spend more time thinking about what they can estimate from the data and assumptions before trying to estimate it.

• 09 Dec 2019
• Research & Ideas

Identify Great Customers from Their First Purchase

Using data from their very first transaction, companies can identify shoppers who will create the best long-term value, says Eva Ascarza. Open for comment; 0 Comments.

• 29 Oct 2019

Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders

Research on the traumatic 1947 partition of British India has most often been carried out by scholars in the humanities and qualitative social sciences. This article presents mixed methods research and analysis to explore tensions within current scholarship and to inspire new understandings of the Partition, and more generally, mass migrations and displacement.

• 30 Jun 2019

The Comprehensive Effects of Sales Force Management: A Dynamic Structural Analysis of Selection, Compensation, and Training

When sales forces are well managed, firms can induce greater performance from them. For this study, the authors collaborated with a major multinational firm to develop and estimate a dynamic structural model of sales employee responses to various management instruments like compensation, training, and recruiting/termination policies.

• 07 Jan 2019

The Better Way to Forecast the Future

We can forecast hurricane paths with great certainty, yet many businesses can't predict a supply chain snafu just around the corner. Yael Grushka-Cockayne says crowdsourcing can help. Open for comment; 0 Comments.

• 28 Nov 2018

On Target: Rethinking the Retail Website

Target is one big-brand retailer that seems to have survived and even thrived in the apocalyptic retail landscape. What's its secret? Srikant Datar discusses the company's relentless focus on online data. Open for comment; 0 Comments.

• 01 Nov 2018

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

Passengers arriving at international hubs often endure delays, especially at immigration and security. This study of London’s Heathrow Airport develops a system to provide real-time information about transfer passengers’ journeys through the airport to better serve passengers, airlines, and their employees. It shows how advanced machine learning could be accessible to managers.

• 29 Apr 2018

Analyzing the Aftermath of a Compensation Reduction

This study of the effects of compensation cuts in a large sales organization provides a unique lens for analyzing the link between compensation schemes, worker performance, and turnover.

• 11 Dec 2017

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

Corporate finance researchers who analyze patent data are at risk of making highly predictable errors. The problem arises from dramatic changes in the direction and location of technological innovation (and patenting practice) over recent decades. This paper explains the pitfalls and suggests practical steps for avoiding them.

• 21 Aug 2017
• Lessons from the Classroom

Companies Love Big Data But Lack the Strategy To Use It Effectively

Big data is a critical competitive advantage for companies that know how to use it. Harvard Business School faculty share insights that they teach to executives. Open for comment; 0 Comments.

• 06 Jul 2017

Do All Your Detailing Efforts Pay Off? Dynamic Panel Data Methods Revisited

Personal selling in the form of detailing to physicians is the main go-to-market practice in the pharmaceutical industry. This paper provides a practical framework to analyze the effectiveness of detailing efforts. The method and empirical insights can help firms allocate sales-force resources more efficiently and devise optimal routes and call-pattern designs.

• 09 Dec 2015

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

Michael Luca, Scott Duke Kominers and colleagues describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities.

• 09 Apr 2014

Visualizing and Measuring Software Portfolio Architectures: A Flexibility Analysis

Contemporary business environments are constantly evolving, requiring continual changes to the software applications that support a business. Moreover, during recent decades, the sheer number of applications has grown significantly, and they have become increasingly interdependent. Many companies find that managing applications and implementing changes to their application portfolio architecture is increasingly difficult and expensive. Firms need a way to visualize and analyze the modularity of their software portfolio architectures and the degree of coupling between components. In this paper, the authors test a method for visualizing and measuring software portfolio architectures using data of a biopharmaceutical firm's enterprise architecture. The authors also use the measures to predict the costs of architectural change. Findings show, first, that the biopharmaceutical firm's enterprise architecture can be classified as core-periphery. This means that 1) there is one cyclic group (the "Core") of components that is substantially larger than the second largest cyclic group, and 2) this group comprises a substantial portion of the entire architecture. In addition, the classification of applications in the architecture (as being in the Core or the Periphery) is significantly correlated with architectural flexibility. In this case the architecture has a propagation cost of 23 percent, meaning almost one-quarter of the system may be affected when a change is made to a randomly selected component. Overall, results suggest that the hidden structure method can reveal new facts about an enterprise architecture. This method can aid the analysis of change costs at the software application portfolio level. Key concepts include: This method for architectural visualization could provide valuable input when planning architectural change projects (in terms of, for example, risk analysis and resource planning). The method reveals a "hidden" core-periphery structure, uncovering new facts about the architecture that could not be gained from other visualization procedures or standard metrics. Compared to other measures of complexity, coupling, and modularity, this method considers not only the direct dependencies between components but also the indirect dependencies. These indirect dependencies provide important input for management decisions. Closed for comment; 0 Comments.

• 10 Jun 2013

How Numbers Talk to People

In their new book Keeping Up with the Quants, Thomas H. Davenport and Jinho Kim offer tools to sharpen quantitative analysis and make better decisions. Read our excerpt. Open for comment; 0 Comments.

• 25 Apr 2012
• What Do You Think?

How Will the “Age of Big Data” Affect Management?

Summing up: How do we avoid losing useful knowledge in a seemingly endless flood of data? Jim Heskett's readers offer some wise suggestions. What do you think? Closed for comment; 0 Comments.

• 05 May 2010

Is Denial Endemic to Management?

Poring over reader responses to his May column, HBS professor Jim Heskett is struck by the fact that they include behavioral, structural, and even mechanical remedies. (Forum now closed. Next forum opens June 3.) Closed for comment; 0 Comments.

• 15 Apr 2010

The Consequences of Entrepreneurial Finance: A Regression Discontinuity Analysis

What difference do angel investors make for the success and growth of new ventures? William R. Kerr and Josh Lerner of HBS and Antoinette Schoar of MIT provide fresh evidence to address this crucial question in entrepreneurial finance, quantifying the positive impact that angel investors make to the companies they fund. Angel investors as research subjects have received much less attention than venture capitalists, even though some estimates suggest that these investors are as significant a force for high-potential start-up investments as venture capitalists, and are even more significant as investors elsewhere. This study demonstrates the importance of angel investments to the success and survival of entrepreneurial firms. It also offers an empirical foothold for analyzing many other important questions in entrepreneurial finance. Key concepts include: Angel-funded firms are significantly more likely to survive at least four years (or until 2010) and to raise additional financing outside the angel group. Angel-funded firms are also more likely to show improved venture performance and growth as measured through growth in Web site traffic and Web site rankings. The improvement gains typically range between 30 and 50 percent. Investment success is highly predicated by the interest level of angels during the entrepreneur's initial presentation and by the angels' subsequent due diligence. Access to capital per se may not be the most important value-added that angel groups bring. Some of the "softer" features, such as angels' mentoring or business contacts, may help new ventures the most. Closed for comment; 0 Comments.

• 22 Aug 2005

The Hard Work of Failure Analysis

We all should learn from failure—but it's difficult to do so objectively. In this excerpt from "Failing to Learn and Learning to Fail (Intelligently)" in Long Range Planning Journal, HBS professor Amy Edmondson and coauthor Mark Cannon offer a process for analyzing what went wrong. Closed for comment; 0 Comments.

Digital Innovation and Transformation

Mba student perspectives.

• Assignments
• Assignment: Competing with Data

The Perfect Blend: Starbucks and Data Analytics

Every day, Starbucks grinds through mounds of coffee beans to serve its customers. In doing so, the company has also been collecting mounds of data that could be used to improve customer experience and business performance. In this article, we will investigate how this 26 Billion USD company captures value through data analytics.

An opportunity brewing

Through its network of over 30,000 stores worldwide, Starbucks has been gathering over 100 million transactions a week. To make use of these data, the company set up a dedicated team of data scientists, led by Jon Francis, Starbucks’ Senior Vice President of enterprise analytics, data science, research data, and analytics. Since then, the team and the company have been able to tap into the power of data analytics to enhance its business performance. 

Using data collected at the store and through its mobile apps with over 17M members, the company has been able to drive business improvements in 3 significant ways. 

(1) Personalized experiences and promotions

Pathways to a Just Digital Future

When Starbucks launched its rewards program and mobile app, they dramatically increased the data they collected and could use to get to know their customers and extract info about purchasing habits. Through its mobile app, Starbucks has been collecting data about what, where, and when members buy coffee. To do so, Starbucks leverages the Digital flywheel program, a cloud-based artificial intelligence engine that’s able to recommend food and drink items in a precise manner. As such, even when people visit a new Starbucks location, the store’s point-of-sale system can identify the customer through their phone and give the barista their preferred order.

Based on customers’ purchase history, Starbucks could also suggest new products a consumer might enjoy and provides unique discounts and rewards on certain items based on customers’ unique preferences. Taking it a step further, Starbucks has also been collecting data on weather patterns and their relationship with customer order patterns. Doing so allows the company to provide even more personalized experiences and promotions such as targeting a customer with cold drinks on hot days.

(2) New product introduction

When launching new products, Starbucks also turned to the data collected to determine what products they should offer. Specifically, when expanding its product lines into grocery stores, the company relies heavily on the data collected. For example,  data collected has shown that 43 percent of tea-drinking customers tend to skip the sugar. To cater to this segment, Starbucks created its lines of unsweetened ice tea. When data has shown that 25 percent of consumers don’t add milk to their coffee, the company launched a new line of black iced coffee without milk.

(3) Location selection

Selecting the right location is critical to winning in retail. Using location-based analytics powered by Atlas, a mapping and business intelligence tool developed by Esri, the company can select the most strategic location to open up its new stores. The tool enables Starbucks to evaluate massive amounts of data including variables such as population, income levels, traffic, competitor presence, and proximity to other Starbucks locations before recommending a new store location. Using these data, the company can also predict revenues, profits, and other aspects of economic performance associated with that location.

While Starbucks was not born in the digital era, it has successfully integrated new technologies into its core business like a digitally native company. Over the years, data analytics has undeniably become the backbone of Starbucks’s continuous improvement. Looking ahead, I have no doubt that Starbucks will continue to gather more data and make even more innovative use of those data to create an even more personalized customer experience and achieve business excellence.  

“Starbucks Isn’t a Coffee Business – It’s a Data Tech Company,” Marker, Jan 16, 2020

“Big Data: The Secret to Starbucks’ Supply Chain Success,” Sisense, Jun 25, 2020

“Starbucks: Using Big Data, Analytics And Artificial Intelligence To Boost Performance,” Forbes, May 28, 2018

“6 Ways in Which Starbucks Uses Big Data,” Analyticsteps, Nov 17, 2020

“How data empowers human connection at Starbucks,” Tableau, Jan 15, 2021

“Starbucks knows how you like your coffee,” CNBC, Apr 6, 2016

Student comments on The Perfect Blend: Starbucks and Data Analytics

Thanks, Max, for the very interesting article! I am just wondering how successfully Starbucks was able to attract new customers with their initiatives with big data. It definitely added a lot of value to existing customers but was it enough to pull customers who like other coffee shops? Also, I wonder what would happen (or maybe is already happening) if competitors start to do the same things with big data. In a such setting, what would be the real competitive advantage? Would it go back to the basic things such as the quality of the coffee?

Great post Max! Very informative. I did not know that Starbucks is actively monitoring the weather information to make product decisions. I would like to know if you think that data is giving Starbucks any sustained competitive advantage?

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Case Studies in Functional Genomics

Get to the point to investigate relevant biological questions..

Join Harvard faculty in this online course to perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses.

What You'll Learn

We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions. Throughout the case studies, we will make use of exploratory plots to get a general overview of the shape of the data and the result of the experiment. We start with RNA-seq data analysis covering basic concepts and a first look at FASTQ files. We will also go over quality control of FASTQ files; aligning RNA-seq reads; visualizing alignments and move on to analyzing RNA-seq at the gene-level : counting reads in genes; Exploratory Data Analysis and variance stabilization for counts; count-based differential expression; normalization and batch effects. Finally, we cover RNA-seq at the transcript-level : inferring expression of transcripts (i.e. alternative isoforms); differential exon usage. We will learn the basic steps in analyzing DNA methylation data, including reading the raw data, normalization, and finding regions of differential methylation across multiple samples. The course will end with a brief description of the basic steps for analyzing ChIP-seq datasets, from read alignment, to peak calling, and assessing differential binding patterns across multiple samples.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

The course will be delivered via edX and connect learners around the world. By the end of the course, participants will understand:

• Mapping reads
• Quality assessment of Next Generation Data
• Analyzing RNA-seq data
• Analyzing DNA methylation data
• Analyzing ChIP Seq data

Your Instructors

Rafael Irizarry

Professor of Biostatistics at Harvard University Read full bio.

Michael Love

Assistant Professor, Departments of Biostatistics and Genetics at UNC Gillings School of Global Public Health Read full bio. 

Vincent Carey

Professor, Medicine at Harvard Medical School Read full bio.

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Ways to take this course

When you enroll in this course, you will have the option of pursuing a Verified Certificate or Auditing the Course.

A Verified Certificate costs $149 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate. 

Alternatively, learners can Audit the course for free and have access to select course material, activities, tests, and forums.  Please note that this track does not offer a certificate for learners who earn a passing grade.

Related Courses

Introduction to bioconductor.

Join Harvard faculty in this online course to learn the structure, annotation, normalization, and interpretation of genome scale assays.

Principles, Statistical and Computational Tools for Reproducible Data Science

Join Harvard faculty in this online course to learn skills and tools that support data science and reproducible research.

Data Science Principles

Data Science Principles gives you an overview of data science with a code- and math-free introduction to prediction, causality, data wrangling, privacy, and ethics.

Supreme Court Decision

Dear Members of the Harvard Community,

Today, the Supreme Court delivered its decision in Students for Fair Admissions v. President and Fellows of Harvard College . The Court held that Harvard College’s admissions system does not comply with the principles of the equal protection clause embodied in Title VI of the Civil Rights Act. The Court also ruled that colleges and universities may consider in admissions decisions “an applicant’s discussion of how race affected his or her life, be it through discrimination, inspiration, or otherwise.” We will certainly comply with the Court’s decision.

We write today to reaffirm the fundamental principle that deep and transformative teaching, learning, and research depend upon a community comprising people of many backgrounds, perspectives, and lived experiences. That principle is as true and important today as it was yesterday. So too are the abiding values that have enabled us—and every great educational institution—to pursue the high calling of educating creative thinkers and bold leaders, of deepening human knowledge, and of promoting progress, justice, and human flourishing.

We affirm that:

• Because the teaching, learning, research, and creativity that bring progress and change require debate and disagreement, diversity and difference are essential to academic excellence.
• To prepare leaders for a complex world, Harvard must admit and educate a student body whose members reflect, and have lived, multiple facets of human experience. No part of what makes us who we are could ever be irrelevant.
• Harvard must always be a place of opportunity, a place whose doors remain open to those to whom they had long been closed, a place where many will have the chance to live dreams their parents or grandparents could not have dreamed.

For almost a decade, Harvard has vigorously defended an admissions system that, as two federal courts ruled, fully complied with longstanding precedent. In the weeks and months ahead, drawing on the talent and expertise of our Harvard community, we will determine how to preserve, consistent with the Court’s new precedent, our essential values.

The heart of our extraordinary institution is its people. Harvard will continue to be a vibrant community whose members come from all walks of life, all over the world. To our students, faculty, staff, researchers, and alumni—past, present, and future—who call Harvard your home, please know that you are, and always will be, Harvard. Your remarkable contributions to our community and the world drive Harvard’s distinction. Nothing today has changed that.

Lawrence S. Bacow President, Harvard University

Alan M. Garber Provost, Harvard University

Meredith Weenick Executive Vice President, Harvard University

Claudine Gay Dean, Faculty of Arts and Sciences President-elect, Harvard University

Tomiko Brown-Nagin Dean, Radcliffe Institute for Advanced Study

Nancy Coleman Dean, Division of Continuing Education and University Extension

George Q. Daley Dean, Harvard Medical School

Srikant Datar Dean, Harvard Business School

Emma Dench Dean, Harvard Kenneth C. Griffin Graduate School of Arts and Sciences

Francis J. Doyle III Dean, Harvard John A. Paulson School of Engineering and Applied Sciences

Douglas Elmendorf Dean, Harvard Kennedy School of Government

William V. Giannobile Dean, Harvard School of Dental Medicine

David N. Hempton Dean, Harvard Divinity School

Rakesh Khurana Dean, Harvard College

Bridget Terry Long Dean, Harvard Graduate School of Education

John F. Manning Dean, Harvard Law School

Sarah M. Whiting Dean, Graduate School of Design

Michelle A. Williams Dean, Harvard T.H. Chan School of Public Health

Application of multicomponent seismic data to tight gas reservoir characterization: A case study in the Sichuan Basin, China

• Zhang, Ming
• Liang, Jing
• Jiang, Xiaoyu
• Gan, Lideng
• Sun, Xiping
• Yu, Xiaowei

Combining PP and PS waves from multicomponent data is an effective hydrocarbon characterization strategy because these two wave types are sensitive to different subsurface properties. We develop a case study using multicomponent data to characterize tight sandstone gas reservoirs in the Jurassic Shaximiao Formation, the western Sichuan Basin, China. In the study area, with PP data it is difficult to distinguish sandstones, mudstones, and gas sand, whereas recently acquired multicomponent data indicate potential for the joint characterization of lithology, porosity, and gas saturation from the combination of PP and PS reflections. Sandstones and mudstones have small P-wave velocity contrasts and large S-wave velocity contrasts. Thus, PS data provide a more accurate description of sandstones, as a substantial proportion of sandstones are undetectable from PP sections. P impedance is sensitive to sandstone porosity variation, and seismic-predicted porosities based on impedance inversion are in good agreement with log-interpreted porosities. The ratio of P-wave velocity to S-wave velocity is sensitive to gas accumulation, and the ratios derived from joint PP-PS prestack inversion are determined to be better than from PP prestack inversion in terms of their agreements with logs and distinct gas-sand boundaries.

The state of EV charging in America: Harvard research shows chargers 78% reliable and pricing like the ‘Wild West’

Featuring Omar Asensio . By Barbara DeLollis and Glen Justice on June 26, 2024 .

BiGS Actionable Intelligence:

BOSTON — New data-driven research led by a Harvard Business School fellow reveals a significant obstacle to increasing electric vehicle (EV) sales and decreasing carbon emissions in the United States: owners’ deep frustration with the state of charging infrastructure, including unreliability, erratic pricing, and lack of charging locations.

The research proves that frustration extends beyond “range anxiety,” the common fear that EV batteries won't maintain enough charge to reach a destination. Current EV drivers don’t see that as a dominant issue. Instead, many have "charge anxiety," a fear about keeping an EV powered and moving, according to scholar Omar Asensio, the climate fellow at HBS’s Institute for the Study of Business in Global Society (BiGS) who led the study.

Asensio’s research is based on a first-ever examination of more than 1 million charging station reviews by EV drivers across North America, Europe, and Asia written over 10 years. In their reviews, these drivers described how they regularly encounter broken and malfunctioning chargers, erratic and secretive pricing, and even “charging deserts” — entire counties in states such as Washington and Virginia that don’t have a single public charger and that have even lost previously available chargers. EV drivers also routinely watch gas-engine vehicle drivers steal parking spots reserved for EV charging.

Asensio said that listening to the current drivers — owners rather than potential buyers — provides a new window on the state of America’s charging system because drivers are incredibly candid about their experiences.

“It’s different than what any one company or network would want you to believe,” said Asensio, who is also an associate professor at the Georgia Institute of Technology . He added that most charging providers don’t share their data and have few regulatory incentives to do so.

Research: EV chargers less reliable than gas pumps

One of the study’s main findings, discovered using customized artificial intelligence (AI) models trained on EV review data, is that charging stations in the U.S. have an average reliability score of only 78%, meaning that about one in five don’t work. They are, on average, less reliable than regular gas stations, Asensio said. “Imagine if you go to a traditional gas station and two out of 10 times the pumps are out of order,” he said. “Consumers would revolt.”

Elizabeth Bruce, director, Microsoft Innovation and Society, said, "This project is a great example of how increasing access to emerging AI technologies enables researchers to better understand how we can build a more sustainable and equitable society.”

Asensio’s research is timely as U.S. policymakers, entrepreneurs, automakers such as General Motors and Tesla , and others grapple with how to develop the nation’s charging network, who should finance it, and who should maintain it. Because charging influences vehicle sales and the ability to meet emissions targets, it’s a serious question. EV sales have climbed, topping 1 million in 2023, but concerns over batteries and charging could slow that growth.

Today, there are more than 64,000 public EV charging stations in the U.S., according to the U.S. Department of Energy's Alternative Fuels Data Center. Experts say that the nation needs many times more to make a smooth, sustainable, and equitable transition away from gas-powered vehicles — and to minimize the anxiety surrounding EVs.

“I couldn’t even convince my mother to buy an EV recently,” Asensio said. “Her decision wasn’t about the price. She said charging isn’t convenient enough yet to justify learning an entirely new way of driving.”

Reviews give voice to 1 million drivers

An economist and engineer by training, Asensio has been studying EV infrastructure since its infancy in 2010. At that time, the consensus among experts was that the private sector would finance a flourishing charging network, Asensio said. But that didn’t happen at the scale expected, which sparked his curiosity about how the charging market would emerge at points of interest rather than only near highways.

To get answers, Asensio focused on consumer reviews “because they offer objective, unsolicited evidence of peoples’ experience,” he said.

The smartphone apps that EV drivers use to pay for charging sessions allow them to review each station for factors such as functionality and pricing in real-time, much like consumers do on Yelp or Amazon. Asensio and his team, supported by Microsoft and National Science Foundation awards, spent years building models and training AI tools to extract insights and make predictions from drivers leaving these reviews in more than 72 languages.

Until now, this type of data hasn’t existed anywhere, leaving consumers, policymakers, and business leaders — including auto industry executives — in the dark.

Research reveals five facts about EV life

Here are some of the top findings from Asensio’s research about public EV charging stations:

Reliability problems. EV drivers often find broken equipment, making charging unreliable at best and simply not as easy as the old way of topping off a tank of gas. The reason? “No one’s maintaining these stations,” Asensio said. Entrepreneurs are already stepping in with a solution. For example, at Harvard Business School’s climate conference in April 2023, ChargerHelp! Co-founder Evette Ellis explained that her Los Angeles-based technology startup trains people to operate and maintain public charging stations. But until quality control improves nationwide, drivers will likely continue to encounter problems.

Driver clashes. One consumer complaint that surprised Asensio was a mysterious gripe from drivers about “getting ICE’d.” The researchers didn’t know what it meant, so they did some digging and discovered that ICE stands for “internal combustion engine.” EV drivers adopted the term to grouse about gas-fueled car drivers stealing their public EV charger spots for parking.

Price confusion. Drivers are vexed by the pricing they encounter at public charging stations, which are owned by a mix of providers, follow different pricing models, and do not regularly disclose pricing information. The result is often surprises on the road. As one reviewer wrote, “$21.65 to charge!!!!!!! Holy moly!!!! Don’t come here unless you are desperate!!”

Equity questions. Public charging stations are not equally distributed across the U.S., concentrated more heavily in large population centers and wealthy communities and less so in rural areas and smaller cities. The result is that drivers have disparate experiences, well-served in some areas and starved in others. Some parts of the country have become “charging deserts,” with no station at all.

Commercial questions. Commercial drivers in many areas can’t find enough public EV charging stations to reliably charge their cars. Here too, drivers are having very different experiences, well-supplied in some areas and not in others.

‘Wild West’ pricing is a major pain point

The research shows that EV drivers are dissatisfied with EV charging station pricing models, likening the situation to the “Wild West.” Indeed, vehicle charging is both unregulated and non-transparent.

Pricing can vary substantially by facility, level of demand, time of day, and other factors, including the type of charger available. A 45-minute fast charger may have one price, while a traditional charger that takes 3 to 5 hours may have another. Pricing can also change by the hour, based on market conditions.

Unlike traditional gas stations, which often display fuel prices on lighted signs, EV stations rarely advertise what charging will cost. Drivers often arrive without any information on what to expect or how to make comparisons, because there’s no reliable way for consumers to find the most cost-effective places to charge. “The government has a source that lists all locations, but not in real-time,” Asensio said. “You might need five different apps to figure it out.”

The driver reviews in Asensio’s data reflect the irritation caused by the current system. “People are getting frustrated because they don’t feel like they’re getting their money’s worth,” he said.

Why is the charging network so opaque? Research conducted by Asensio and his colleagues in 2021 found that charging station hosts, in the absence of regulation, have no incentive to share data — and they don’t. Station hosts are typically privately owned, highly decentralized, not well-monitored, and have highly varied patterns of demand and pricing.

The lack of transparency prevents researchers — and journalists — from investigating trends. In stark contrast to headlines trumpeting the ups and downs of gas prices, news organizations are not reporting on differential pricing among EV charging stations.

‘Charging deserts’ emerge

With municipal, state, and federal governments all pushing to increase the number of electric vehicles on the road and decrease carbon emissions, experts agree that America will need more charging stations — a lot more.

Looking only at Level 2 chargers, which top off an EV battery in 3 to 5 hours and are the most common type, S&P Global Mobility estimates a need for 1.2 million nationwide by 2027 and almost twice that by 2030. That’s in addition to in-home chargers.

Of course, that assumes robust growth in EV sales. “The transition to a vehicle market dominated by electric vehicles (EVs) will take years to fully develop, but it has begun,” said Ian McIlravey, an analyst at S&P. “With the transition comes a need to evolve the public vehicle charging network, and today's charging infrastructure is insufficient to support a drastic increase in the number of EVs in operation.”

Making matters more difficult, the chargers that do exist are not evenly distributed. Predictably, the places with the most public chargers installed are those with the highest number of registered electric vehicles, including states like California, Florida, and Texas. Yet, even as the federal government invests billions in new charging stations, many of them along major transportation corridors, places are left behind.

Asensio’s research shows that small urban centers and rural areas attract fewer public charging stations, and in some cases, there are “charging deserts” with no facilities at all — and they may not be where you think.

For example, electric vehicles are popular in Washington state, which ranked fourth in number of EV registrations and sixth in number of public charging stations in 2023. Yet Ferry County , an area outside Spokane with about 7,500 residents, where the average commute is 25 minutes and the median income is about $46,000, had only one charging station for several years. And now there are none.

Similarly, Virginia ranked 11th in EV registrations and 13th in public chargers in 2023. There, researchers found Wise County, an area outside Roanoke and Knoxville, Tennessee, with about 3,500 residents and a median income of almost $45,000. The county has an average commute time of 22 minutes, but there are no public charging stations available.

EV charging presents a classic “chicken and egg” situation, begging the question of whether cars or charging facilities must come first. However, a lack of public charging in areas like Ferry County and Wise County makes electric vehicle adoption difficult.

As American drivers debate whether to swap their gas-powered vehicles for EVs and lower emissions, Asensio said research should play a larger role. Policymakers, auto manufacturers, entrepreneurs, and investors need more and better data to build infrastructure where it’s needed, provide reliable charging, and facilitate EV sales.

“How [else] can we make effective decisions about the economics of EVs?” Asensio said.

General Motors: ‘Anxiety around EV charging’

Omar Vargas, head of public policy at General Motors, emphasized the importance of public EV charging infrastructure to driving EV adoption during an interview with The BiGS Fix at one of BiGS’ business leadership roundtables in Northern Virginia.

“We're looking at what are the best places to install an EV charging station for a community,” Vargas said. “The anxiety around EV charging is an inhibitor to EV adoption.”

Beyond the public investment in rolling out charging infrastructure, GM (whose brands include Chevrolet and Cadillac) has committed $750 million in private capital to the development of EV charging stations. It is partnering with car dealerships and other companies. For instance, GM is testing charging stations at Flying J rest stops.

GM, which reported full-year revenue of $171.8 billion for 2023 , also is joining community partnership efforts that are being formed to secure federal dollars through state and local governments. “We're helping that kind of planning, and we're pretty confident that in the next couple of years, we're going to have a vigorous EV charging network in the United States,” Vargas said.

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