Skip to main content
About HEC About HEC
Summer School Summer School
Faculty & Research Faculty & Research
Master’s programs Master’s programs
Bachelor Programs Bachelor Programs
MBA Programs MBA Programs
PhD Program PhD Program
Executive Education Executive Education
HEC Online HEC Online
About HEC
Overview Overview
Who
We Are
Who
We Are
Egalité des chances Egalité des chances
HEC Talents HEC Talents
International International
Campus
Life
Campus
Life
Sustainability Sustainability
Diversity
& Inclusion
Diversity
& Inclusion
Stories Stories
The HEC
Foundation
The HEC
Foundation
Summer School
Youth Programs Youth Programs
Summer programs Summer programs
Online Programs Online Programs
Faculty & Research
Overview Overview
Faculty Directory Faculty Directory
Departments Departments
Centers Centers
Chairs Chairs
Grants Grants
Knowledge@HEC Knowledge@HEC
Master’s programs
Master in
Management
Master in
Management
Master's
Programs
Master's
Programs
Double Degree
Programs
Double Degree
Programs
Bachelor
Programs
Bachelor
Programs
Summer
Programs
Summer
Programs
Exchange
students
Exchange
students
Student
Life
Student
Life
Our
Difference
Our
Difference
Bachelor Programs
Overview Overview
Course content Course content
Admissions Admissions
Fees and Financing Fees and Financing
MBA Programs
MBA MBA
Executive MBA Executive MBA
TRIUM EMBA TRIUM EMBA
PhD Program
Overview Overview
HEC Difference HEC Difference
Program details Program details
Research areas Research areas
HEC Community HEC Community
Placement Placement
Job Market Job Market
Admissions Admissions
Financing Financing
Executive Education
Home Home
About us About us
Management topics Management topics
Open Programs Open Programs
Custom Programs Custom Programs
Events/News Events/News
Contacts Contacts
HEC Online
Overview Overview
Degree Program Degree Program
Executive certificates Executive certificates
MOOCs MOOCs
Summer Programs Summer Programs
Youth programs Youth programs
Article

Analytics in the Era of Big Data: Opportunities and Challenges

Data Science
Published on:

This special issue of Knowledge@HEC highlights several research projects and teaching initiatives at HEC Paris in the context of big data and business analytics. Nowadays it does not take much to convince students or managers alike of the importance of data for businesses. As Wedel and Kannan (2016) put it, “data is the oil of the digital economy”. Indeed, data is completely transforming organizations, and data-driven decision making is becoming more and more a part of a company’s core. In an increasing digital world, all of us are walking data generators, leaving long data trails: we have more data on everything.

Analytics in the Era of Big Data: Opportunities and Challenges - @Fotolia-shanghainesewang

Big data is often characterized by three (sometimes four or even five) V’s (e.g. Wedel and Kannan, 2016, Marr, 2016): Volume, Velocity, and Variety. More data was created in the past two years than in the entire previous history of mankind. At the same time, data is coming in at a much higher speed, often close to real-time. Furthermore, data nowadays is much more diverse, including not only numeric data but also text, images or video data to mention a few. The first two V’s are important from a storage and computational point of view, whereas the last V is important from an analytics point of view. 

On the other hand, several people have argued that big data is just a hype that will go away. When we analyze the popularity of the search term “big data” on Google, we find that the usage of “big data” as search term has grown explosively since 2008, but has stabilized since about 2015 (figure 1). Marr (2016) states that the hype around “big data” and the name may disappear, but the phenomenon will stay and only gather momentum. He predicts that data will simply become the “new normal” in a few years’ time when all organizations use data to improve what they do and how they do it. We could not agree more with him.

Big data trends on Google

But, understanding and acting on an increasing volume and variety of data is not obvious. As Dan Ariely of Duke University once put it, “big data is like teenage sex: they all talk about it, they all want to do it, but no one really knows how to do it”. Wedel and Kanan (2016) put it more formally and argue that companies have invested too much in capturing and storing data and too little in the analytics part of it. While big data is on the top of many companies’ agenda’s, few of them are getting value out of it today. Therefore, in this special issue we did not only want to highlight “big data”, but also the “analytics” part of it, as state-of-the-art analytics is necessary to get results from big data. 

We believe that a very basic lesson from “old-fashioned” marketing analytics also applies to the “new world” of big data, but is too often ignored: begin with an end in mind (Andreasen, 1985). If we do not know what decision we are trying to make, big data is not going to solve the problem: we are searching for the needle in a haystack without a needle. As Wedel and Kannan (2016, p115) note, the primary pre-condition for successful implementation of big data analytics is a culture of evidence-based decision making in an organization. Companies that are successful with big data analytics often have a C-level executive who oversees a data analytics center of excellence within the company. In such companies there prevails a culture of evidence-based decision making: instead of asking “what do we think?”, managers in such companies ask “what do we know?” or “what do the data say?” before making an important business decision. The big data analytics movement will also affect us at HEC Paris. We want to highlight three aspects, which are further discussed in this HEC Knowledge special issue. 

First, it will affect the education and training of our students. In this special issue, the article by Daniel Brown discusses several initiatives at HEC Paris regarding the education of our students. Particularly, it highlights a new joint master with Polytechnique on big data integrating topics in statistics/econometrics, computer science, and substantive business areas such as marketing or finance. This new initiative will further extent the course offerings in business analytics that HEC Paris already has.

Second, it will increase the breath of our research. In this special issue, we highlight four recent studies to make that point. The first two studies by Peter Ebbes and Valeria Stourm discuss new developments in the context of marketing analytics. Their studies show how combining a variety of data sources benefits customer relationship management. The next two studies by Mitali Banerjee and Gilles Stoltz’ develop new machine learning algorithms to analyze pictures and to generate forecasts. These two studies show how such algorithms can be used to judge creativity and to aggregate forecasts to help businesses make better decisions. Lastly, David Restrepo Amariles and Xitong Li discuss several issues regarding big data legislation and policies. David shows that big data practices and algorithms are not always compliant with the rule of law, whereas Xitong argues that certain big data requirements in firm financial reporting can make financial reports actually more complex and harder to read. 

Third, it will bring along opportunities for collaboration on problems of big data analytics between companies and researchers at HEC Paris. For empirical researchers at HEC Paris it is of increasing importance to be exposed to current business problems and data. At the same time, companies benefit from a close collaboration with researchers by getting access to state-of-the-art solutions and learning about the latest business analytic approaches in a field that is moving very rapidly. In fact, in several of our own past research studies, we have already successfully collaborated with companies on substantive data problems. Our collaborations have let to actionable insights for the company AND academic publications for the researcher(s), a clear WIN-WIN.

 

With this Knowledge@HEC special issue we highlight some of the exciting initiatives and research studies that are going on at HEC Paris. We hope that it inspires companies and alumni in the HEC Paris network to reach out to any of us with new data opportunities or big data analytics challenges, to further help to expand HEC Paris as a research institution!

Andreasen, A. R. (1985), “Backward” marketing research, Harvard Business Review (May issue) Marr, B. (2016), Big data in practice, Wiley, Chichester Wedel, M., and P. K. Kannan (2016), Marketing analytics for data-rich environments, Journal of Marketing, 80, pp.97—121.

Related content on Data Science

e commerce - vignette

Photo credit: CardMapr.nl 

Data Science

Click, Click, Boom! New Algorithm Set to Boost Revenue for Online Retailers

By Sajjad Najafi

Photo Credit: NaMaKuKi on Adobe Stock

Data Science

How Do Algorithmic Recommendations Lead Consumers to Make Online Purchases?

By Xitong Li

Finance
Why Do We Share Our Personal Data?
Johan Hombert
Johan Hombert
Associate Professor
facial recognition thumbnail
Artificial Intelligence

“A $%^* Sexist Program”: Detecting and Addressing AI Bias

By Christophe Pérignon

Operations Management

How Can We Force Companies To Keep Our Data Safe?

By Ruslan Momot

clicking on news online - thumbnail
Finance

How Big Data Gives Insight Into Investor Uncertainty

By Thierry Foucault