digital Transformation

Why should future managers invest in Data Science ?

Managers to be had better invest time in Data Science. The Business Analytics Institute will once again be hosting its Summer School in Data Science for Management in Bayonne, France from July 2 to 11 2018.  In this exclusive five-part series, we will explore the BAI’s unique value proposition around improving managerial decision-making.

Why should future managers invest in Data Science ?

managers data science
Why should future managers invest in Data Science ?

Ever since the Harvard Business Review declared a few years back that Data Science was the “sexiest job on Earth”, students have flocked by the thousands in pursuit of degrees in the field. Recent estimates suggest that there are roughly fifteen thousand qualified data scientists working today – a pale comparison to the eighty-one thousand openings for data scientists on LinkedIn this week.

Alphabet’s Eric Schmidt recently summed up the situation, “a basic understanding of data analytics is incredibly important for this next generation of young people…”As a future manager, why should you seize this opportunity by enrolling in BAI’s Summer School on Data Science for Management?

Why are companies so interested in data?

Klaus Schwab suggests that data and analytics have provided the foundations of a Fourth Industrial Revolution.  Statista’s figures back up this claim – the data centric GAFA corporations accounted for $229 billion of revenue in 2017.The European Commission estimates that the value of personalized data will reach 1 trillion euros by 2020, almost 8% of the EU’s GDP.[v] Cap Gemini’s survey of corporate business executives found that 61% of the respondents “acknowledge that big data is becoming as valuable to their businesses as their existing products and services.Given that the volume of data companies capture grows by an average of 40% a year, it is not surprising that Data Scientists are in such high demand..

Why some much fuss about data?

Data is no longer a simple by-product of a business process, it has become the lifeblood of modern enterprise.  Riley Newman of Wave Capital reminds us that data isn’t just data — it is an imperfect mirror of our customer conversations. If captured and nurtured correctly, data reflects our understanding of current economic realities, and help us predict and influence how consumers will value their experiences over time. Data in itself has no intrinsic value, value is produced in the platforms, processes, and mindsets we put in place to capture and influence customer experiences. Unlike investments in capital goods, the value of these “intangible” digital properties grows over time through network effects as more and more people use them.

What is Data Science?

Data Science is less about theory than it is about practice, integrating these decision-making fundamentals into the way we work.  Data Science is less concerned with what we do (descriptive) than what we could (predictive) or should do (prescriptive analytics). Today, organizations are looking for data scientists in industries ranging from the health sciences to finance, IT, and the media and public service. The scarcity of specialists to fill these openings is largely because Data Science is marketed as a mashup of analytical, business, and technical skills that are rarely found in any one profile. The only common denominator is a universal vocation of using data to learn about real life business challenges.  

Why study Digital Economics?

If you skim through your activity streams in WhatsApp and LinkedIn, it is difficult to imagine anyone would pay tens of billions of dollars for either company. The financial evaluation of these data-driven organizations wasn’t based on the quantity of the data, but on the quality of their digital assets. The worth of organizations today isn’t tied to the quantities of data they collect, but on their abilities to leverage open data and on-demand applications to provide personalized customer experiences. The concept of “digital economics” evokes these inter-relationships between data, business models and managerial decision making.

What will you learn at the Business Analytics Institute?

BAI’s Summer School and Exec Ed conferences are built around a unique four-step analytical process designed to help management students make better decisions in the context of their work. To begin with participants practice scanning their environment (physical and digital) to understand the nature of the business challenges they trying to solve. The second step explores the quality of the data at hand. The third step applies the correct methodology to ideate solutions to the types of problems we are trying to solve. Finally, participants learn to transform the data into stories that will motivate their teams and communities to act.
Data driven manager
Using real-life examples and case studies in the health and life sciences, participants in this year’s BAI Summer School will discuss how digital economics has changed the mechanics of the markets for goods and services. Participants will explore the real costs and benefits associated with nurturing the digital platforms, processes and mindsets that constitute an organization’s digital properties. They will analyze how data shapes and customer and employee perceptions of the value of a company’s product offer. Most importantly, they will practice how future managers can leverage Data Science to improve their own market value and future careers.

The BAI Summer School on Data Science for Management

The Business Analytics Institute Summer School in Data Science for Management in Bayonne, France will be held from July 2 to 11 2018. This university and corporate accredited program targets senior and graduate management students who want to understand how data science can enhance both their jobs and their future careers. The session will be facilitated by internationally recognized professors and practitioners on digital economics, managerial decision-making, machine learning and artificial intelligence, and data storytelling. Detailed information on the program, social activities, student testimony, and university accreditation/professional certification can be found at
Lee Schlenker is a Professor of Business Analytics and Community Management, and a Principal in the Business Analytics Institute His LinkedIn profile can be viewed at You can follow us on Twitter at


Further Reading from BAI
What do we really need to know about Data?
Analytics 4.0: it’s all about taking better decisions
Data Science’s Dirty Little Secrets
What are the Key Skills in Data Science?



[i] Davenport, T. and Patil, D.J., (2012) , Data Scientist, the sexiest job of the 21rst Century, HBR
[ii] Quora, How many data scientists (by any name) are there today?, Oct. 2015
[iii] Ward, M. (2017), Google billionaire Eric Schmidt says this is the skill employers will look for in the future, CNBC
[iv] Boittiaux, P (2018), Les revenus mirobolants des GAFAM
[v] European Commission, (2017), Fact Sheet — Data Protection Reform Package
[vi] Cap Gemini, (2015), Big & Fast Data: the rise of the insight-driven business
[vii] Newman, Riley, (2015), How we scaled data science to all sides of Airbnb over 5 years of hypergrowth, Venture Beat

Yann Gourvennec
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Yann Gourvennec

Yann Gourvennec created in 1996. He is a speaker and author of 6 books. In 2014 he went from intrapreneur to entrepreneur, when he created his digital marketing agency. ———————————————————— Yann Gourvennec a créé en 1996. Il est conférencier et auteur de 6 livres. En 2014, il est passé d'intrapreneur à entrepreneur en créant son agence de marketing numérique. More »
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