Business Analytics & Data-Driven Decision-Making: Insights from INSEAD’s eLab

ISSUE #65 – Theodoros Evgeniou (pictured below), Professor of Decision Sciences and Technology Management at INSEAD and Academic Director of INSEAD eLab, introduces us to the work of the school’s eLab on data analytics and the opportunities in collaboration.


Could you introduce us to INSEAD eLab and what it works on?

The eLab has a history of more than 10 years and is a gateway for companies and organisations to collaborate with INSEAD on projects in focus areas, by bringing together necessary and relevant INSEAD resources to respond to the research challenges defined together. Working on data analytics, big data, machine learning, and recently AI, some example projects are:

    • Information aggregation and predictions of market/industry/company conditions: a team from the INSEAD faculty is working on innovative ways to aggregate information (for example about past company performance) across different sources such as analyst reports and forecasts, and relate such aggregated information to future market/industry/company performance. The problem of aggregating forecasts, opinions, information from diverse sources, is a central one in the world where different information sources (online company reviews, alternative data such as satellite images of cargo and trade movements, etc.) can now get combined in order to make better business and investment decisions. Developing the next-generation tools to achieve this as well as applying these tools to various business and financial cases, from financial markets-related problems to forecasts of corporate health or macroeconomic and consumer sentiment and trends, is one of the key streams of the centre;
    • Marketplace data analysis to manage buyer-supplier matching more efficiently and effectively: in collaboration with online companies, INSEAD faculty and researchers have developed a series of research results that can guide managers to better use data from sales and facilitate the discovery of products from buyers and of customers/buyers from sellers. The results of this stream can not only be used by online marketplaces, but can also provide insights on how organisations can better use data from customer transactions to develop better customer and market insights;
    • eLab also supports the development of innovative teaching on data analytics and machine learning. For example, we have developed one of the first courses in business schools globally where participants use cloud-based and open-source state-of-the-art tools to study quantitative and business topics in the area of analytics and big data.



Are there any interesting insights from your projects that you could share with us?

On a recent project on information aggregation, an innovative research stream looked at how information about corporate decisions can be integrated with that of financial markets to better understand future company stock returns. It turns out that corporate insiders – e.g. board members and senior executives – can signal internal information via actions such as share repurchase programmes or equity issuance.

Our work shows that the stock returns of companies we identify that announce a share repurchase programme are significantly higher in the two to four years post announcement of the programme than that of other companies, indicating a fascinating case where even the financial markets may be less efficient in aggregating information. Hence, stock returns predictions (known to being notoriously difficult to understand, let alone predict) can be improved if other information sources are brought into the analysis. If stock returns can be predicted (the specific case is known as the “buyback anomaly” in financial markets) when all relevant information sources are combined, then one can imagine how insights about other less complex situations can be developed – using careful data analytics processes that eLab and the INSEAD faculty are working on.


What opportunities in collaboration might there be with companies?

Any organisation that would have the interest and capacity to support innovative data-driven research is a candidate collaborator and contributor to eLab’s mission to develop innovative tools and insights from data to support business, regulatory, financial, and political decisions. Such collaborations to succeed need to have, among others, three key ingredients: commitment of a company sponsor and resources, innovative data and insights/hypotheses to be studied, and a fit with the skills and interests of the INSEAD faculty.



Interview with Theodoros Evgeniou, Professor of Decision Sciences and Technology Management at INSEAD and Academic Director of INSEAD eLab

Published in FOCUS Magazine — Issue #1 2018 “Ready? Start-Up. Go!”