The Fisher Center for Business Analytics coordinates a range of educational programs that applies UC Berkeley’s leadership in Data Science to business and reflects the distinct brand of the Berkeley Haas Defining Leadership Principles:


The Haas School of Business develops leaders.  At Haas, courses introduce principles of data analytics in the context of business and leadership. Business analytics is framed not as a distinct subject but as fundamental to every discipline.  The curriculum is coordinated to enable a student to learn basic concepts (e.g. supervised v. unsupervised learning, evaluating the performance of a categorical classifier, experimental design) through one of several different courses. Analytics is thus diffused throughout the general, MBA curriculum.


The Haas analytics curriculum is deliberately coordinated in a layered fashion. All students are required to take Data and Decisions so as to achieve basic literacy in quantitative analysis. Students interested in understanding the landscape of business analytics concepts may select from one or more Primary Analytics courses. The syllabi of the Primary courses are coordinated to maximize complementarities (and minimize redundancies) among methods and problem-domains while providing the next level of depth in quantitative, data-driven decision-making. Beyond the Primary courses are a number of Secondary, domain-specific courses. Each includes additional quantitative, analytics modules.

Business Analytics Courses at Haas

The Haas School is part of the broader UC Berkeley community. Students at Haas may weave threads from programs across the University into their studies. UC Berkeley’s programs in Statistics, Computer Science, Mathematics, and Information are defining the leading edge of Data Science. Haas students have the opportunity to pursue advanced studies from global experts across the University.

Technology Platform

In addition to Excel, Haas has deployed a common technology platform for business analytics. The Jupyter Notebook is a technology standard in the data science community. Although open source, Jupyter was largely invented and currently developed and maintained at UC Berkeley. Jupyter is one implementation of the Notebook paradigm. R-studio, a popular interface for R now has a format that mimics the notebook paradigm as does Matlab (these are other software tools for algorithmic data manipulation). Haas supports the Jupyter environment through a software-as-a- service platform called JupyterHub which students access via a Web browser. Depending upon the course, students use use R or Python. No one tool strictly dominates the other; they stem from different traditions. Python is more common in the engineering-based courses. R is more common in advanced statistics courses. At UC Berkeley, both the Statistics and EECS (Electrical Engineering and Computer Science) departments have converged on Python as the base platform for all introductory courses and teach using Jupyter notebooks.

Business Analytics Certificate

The Graduate Certificate in Business Analytics responds to an escalating need for leaders and managers who can translate data into business insights and who are literate consumers of data science techniques. It is designed for students aspiring to leadership roles involving business decision making informed by data.


Haas programs in Business Analytics extend beyond degree programs to support continuing education and industry best practices.

Executive and Professional Education

Executive and Professional Education Programs in Business Analytics bring business leaders to campus to continue their lifelong education.  Courses in analytics include open-enrollment programs as well as opportunities for custom programs through Berkeley’s Center for Executive Education.

The program helps coordinate three regional networks of strategic information technology leaders who meet monthly to educate and support one another (Silicon Valley, San Francisco, East Bay).
With the Gartner Group, the Center established the Fisher-Hopper Prize for Lifetime Achievement in CIO Leadership.

Each year, the prize ceremony is part of an annual, day-long seminar on strategic information technology


Through the support of the Ryoichi Sasakawa Foundation, the Center administers Fellowships to PhD students applying analytics in their doctoral research. Current Fellows in Business Analytics are:

Kimberlyn George


Kimberlyn is currently working on a project related to the applications of blockchain technologies in business analytics. Blockchain technology allows for the recording and verification of transactions in real time. 

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Its applications in financial reporting, audit and supply chain will have vast implications for business operations and organization, capital markets and beyond. By authenticating and recording immutable transactions, a decentralized blockchain performs the same function as many intermediaries in our society that establish trust and maintain integrity between transacting parties. In this project, Kimberlyn is exploring the ways in which blockchain technology will eliminate barriers in various aspects of business operations, allowing for continuous assurance, integrated supply chains, real time financial reporting, and fraud detection.

Gauri Subramani


Gauri examines another source of potential friction that may result in the duplication of costly services: cross gender referrals. Her project therefore examines whether the duplication of health services is more prevalent when PCP and specialists are of different genders.

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Recent research has demonstrated that one of the reasons why health care costs have continued to rise steeply over the past decade is that patients receive care that adds little or no value. Prior work has shown that the duplication of services is more likely in settings where PCP and specialist are part of different organizations and therefore have no access to a shared IT system. Prior work has also shown that part of the gender pay gap among specialists is caused by the fact that male PCPs have a strong preference to refer to male specialists. Likewise, male PCPs are less forgiving when their patient experiences an adverse health event on the watch of a female specialist than when the specialist is male. Both studies suggest that friction in the referral process is more common if the PCP and the specialist do not match on gender. This project therefore examines whether the duplication of health services is more prevalent when PCP and specialists are of different genders. To study this question Gauri leverages the Massachusetts All Payers Claims Database (MA APCD). The MA APCD contains more than one billion medical claims for every patient in Massachusetts between 2010 and 2016. These claims also contain detailed information on the diagnoses, services provided, and whether the patient was referred and by whom.

Troup Howard


Troup’s work is at the intersection of public finance, labor economics, and corporate finance. He studies racial gaps in the value of houses assessed by local government for property tax purposes. 

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For this purpose, Troup has collected a unique dataset that allows him to observe, for a large subset of houses in the US, the house value as assessed by the local government assessor, as well as the transaction value of the house in the same year. Troup finds that in Census tracts with a larger share of the African-American population, the gap between assessed and market value is significantly larger. What is unique to this setting relative to standard settings in the economics of discrimination is that Troup observes a very precise measure of the fundamental value of the house — its transaction value. Howard. Troup is also working on extending his dataset to obtain information about race at the house level (as opposed to using Census-tract level information on race).

Alexey Sinyashin


Alexey’s work studies the effects of consumer non-monetary incentives on demand and environmental impact of “green” products in the US market for electric vehicles. 

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Electric vehicles are typically priced higher than comparable gas-powered cars but less costly to operate, which makes them financially most appealing for high-mileage drivers. Environment conscious drivers may also be willing to pay a price premium for an electric car although they do not necessarily drive a lot of miles per year. On the one hand, environmental consciousness among all drivers improves adoption of the “green” technology, but, on the other hand, demand from eco-conscious drivers drives prices for electric cars up and makes them less appealing for consumers who care only about financial benefits. As a result, total miles traveled substituted by “green” vehicles for gas-powered vehicles could be lower in the presence of environmental consciousness. First, this means lower instantaneous environmental effect of electric vehicles, and, second, this means lower demand for charging infrastructure, which, in its turn, means slower subsequent adoption. The paper builds a structural model to estimate a price premium that environment conscious drivers pay for electric vehicles, its environmental effects and effects on demand and adoption of electric vehicles.

Matteo Tranchero


Matteo studies physician behavior and the availability of new information. Matteo also examines the adoption of new practices by physicians following the release of new information about the effectiveness of specific treatments. 

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Despite detailed standards on the content of medical education, physicians exhibit wide variation in the way they provide medical care, which has an impact on the costs of care sand health outcomes of patients. Research on the sources of variation is scant. Matteo examines the introduction of a drug to treat blood clots with less side effects, and the release of a new guideline regarding the optimal (lower) frequency of pap smears. He also examines which physicians adopt these new perspectives on treatment by focusing specifically on the organizational structure in which physicians are embedded. The project uses the Massachusetts All Payers Claims Database to test whether physicians in large practices are more likely to incorporate new insights into their medical decision making while accounting for selection issues by exploiting acquisitions of small physician practices by larger health care systems.

Jesse Yao


Jesse studies advertising by publisher. Jesse estimates and tests the effectiveness of the advertising of each publisher, so that the advertiser could compensate multiple publishers according to their marginal contributions.

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Advertisers usually use more than one publisher to deliver ads. Traditionally, advertisers only compensate the last publisher who showed the ad to the customers before the conversion. This method, however, will lead to some undesired behavior of the publisher such as free-riding, which might harm the advertiser.

Byung Hyun Ahn


Byung investigates the role of active ETFs in capital markets. The tremendous growth in exchange-traded funds (ETFs) and passive investing summarizes the post-financial crisis investment landscape.

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Contrary to expectations, actively-managed ETFs have also gained popularity since the SEC’s approval of such ETFs in March 2008. As of today, 223 actively- managed ETFs are registered with the SEC, totaling $51.7 billion of assets under management with smart beta ETFs being one of the fastest growing investment instruments. Hyung will contribute to the literature by analyzing the performance actively-managed ETFs, their management fee structure, and investor base characteristics, as well as the interplay with passive strategies and alternative active strategies. Hyung will examine the implications of the growth in actively-managed ETFs on the underlying constituents’ security lending conditions to gain insights about the interplay of limits to arbitrage with stock market pricing efficiency.

Oren Reshef


Oren Reshef’s research is entitled “Information Simplification and Strategic Reaction: Evidence from the Israeli Food Market.”

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In a world of complex choices, consumers may make uninformed decisions even when all relevant information is readily available. A common policy suggestion is to aid consumers by making information more accessible, simple, and standardized. The goal of this project is to study the general equilibrium effects of the provision of simple information. Specifically, the focus is on a nationwide, mandatory labeling policy, advocated by the Israeli Ministry of Health, to promote healthy nutrition. Oren Reshef develops a simple conceptual framework to formalize the mechanisms governing consumers’ and firms’ behavior examining consumers’ understanding and usage of the simplified labels and whether demand for healthier products changes as a result. Oren focuses on the unintended consequences of the policy, especially those affecting individual information acquisition and demand for nutritional dimensions not explicitly included in the labeling. Additionally, he studies the supply side response by examining how the shift in incentives drives product innovation, reformulation, and readjustment of pricing strategies. Finally, he derives the aggregated welfare implications.

Xin Chen


Xin Chen is working on a project titled “Social Promotional Strategies and Consumer Choice: Evidence from an Online Field Experiment”

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This paper examines the effects of bundling social incentives with promotions. When using these “social promotions,” a firm must decide whether or not to require customers to share the promotion on social media with friends. On the one hand, this requirement may make it easier for the firm to get the word out. On the other hand, this requirement may inconvenience customers and lower their propensity to purchase. To conduct valid inference on this trade-off between the costs and benefits, I devise novel empirical strategies that flexibly accommodate the amount of information available to a firm. Through a field experiment on a Chinese online grocery site, randomized both at the city and individual level, I find that social promotions can serve as an effective growth strategy. The social obligation can benefit a firm through two channels. First, the customers who do share add additional value through both new customer acquisition and existing customer retention. Second, the firm does not lose profit from the customers who choose not to purchase the promoted products when forced to share (but would otherwise purchase the promoted products without mandatory sharing); they contribute instead by purchasing other substitutes from the same site. Furthermore, exploiting customer heterogeneity and targeting mandatory sharing to certain types of customers can further improve the efficacy of social promotions.

Richard Lu


Richard Lu is working on a project with Jenny Chatman, Amir Goldberg, and Sameer Srivastava that is focused on understanding how cognition and behavior relate to one another.

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Using survey data and email data from a mid-sized organization, he is establishing the linkages between the cognitive manifestations of cultural fit– that is, how someone thinks about how they fit into an organization based on self-reports- -and the behavioral manifestations– based on linguistic similarity between a person and her interlocutors in internal email communications. He is using the tools of computational linguistics and machine learning to identify the “linguistic signature” of cognitive cultural fit so that we can impute self-reported cultural fit for people and time periods where these data are not available. This will enable him to transform a one-time survey into a longitudinal assessment, which will in turn enable him to examine the dynamic interplay between cognitive and behavioral cultural fit and its consequences for individual performance.

Santiago Truffa


Santiago Truffa is working on an ambitious project about the agglomeration of talent and the economics of inequality across and within cities.

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This is a project that aims to account for a complex empirical pattern within a unified framework that can speak to the data. The pattern involves cross-city differentials: vast inequality in wages and property prices, and differences in the human capital that on average flocks to different cities. But in addition, individual human capital and wages differ within cities. The understanding of these patterns require a general equilibrium framework, which Santiago has developed, and one that is estimable. In order to estimate the role of the key forces at play in driving the various inequalities in the U.S., Santiago has launched into fascinating data work. On the one hand, he has collected data on wages, city amenities, and property values in 50 metropolitan areas in the U.S., and analyzed those data to first describe the overall patterns, and then used the data to estimate his model. In addition, Santiago has worked with a leading online brain training company (Lumosity) to obtain from them their user data. Santiago has succeeded and is now in the process of analyzing it. These data are exciting because they include millions of observations of users all over the country, that among other things allow us to produce an “IQ map” that helps us better understand the distribution of talent over space. These data complement his analysis of the human capital distribution across cities, but they have great additional potential. An obvious challenge in using these data is the fact that they reflect self-selection into using a brain-training service. Santiago has deployed state-of- the-art selection techniques to undo these selection effects, which tells me there is truly fantastic potential for the use of these data.

Jean Zeng


Jean Zeng plans to work on a novel and very comprehensive database with industry-level analytics, including long-term forecasts of value drivers (e.g., employment growth, operating performance etc.).