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Digital Economics

In producing the content for a poster for our 2018 summer school courses on business analytics, I suggested the term “digital economics” as the title of our introductory course on the primacy of data in modern economies. 

It is of little wonder that four of the five most valuable companies on the planet today specialize in information processing (Apple, Alphabet, Microsoft, and Facebook), while the fifth (Amazon) leverages data in the very heart of its business model.[1] For those practicing management, the concept of “digital economics” evokes the inter-relationships between data, business value and managerial decision making. Let’s take a quick look at what digital economics is all about, and its impact on both organizations and markets.

One of the defining characteristics of modern economies is that value is an attribute of user experience rather than a supplier’s products or services. The globalization of value chains pushes economic agents towards more profitable activities, both upstream and downstream of production. If Daniel Bell foresaw that modern enterprise would move from assembling products to aggregating services, PIne and Gilmore underlined the subsequent shift of business value from organizational services to customer experiences.[i] Value today is seen as a synonym of the quality of our consumer experience, whether it be in leisure time or professional activities. At the heart of our perceptions is data in context, which we use to quality our physical, augmented, or virtual realities.

Data provides a proxy of these human experiences. Though data is nothing new, it is increasingly ubiquitous — more data will be created this year than in the previous 5000 years of recorded history.[ii] Data is at the heart of the Fourth Industrial Revolution — advances in internet technologies and business analytics are the current foundations of sustainable competitive advantage.[iii] Digital strategies stretch beyond websites to an Internet of Things designed to capture consumer preferences, actions, and motivations. If data has no intrinsic value, our ability to transform data into individual and/or collective action has become the fulcrum of both business and society.

The ubiquity of data has changed the way we look at value. Data isn’t collected to simply describe physical objects, but to feed multi-purpose algorithms that condition the way we model the world around us. Data Science is less concerned with what we do (descriptive) than what we could (predictive) or should do (prescriptive analytics). Business information systems are no longer designed to track tangible goods, but to provide horizontal platforms that leverage the intangible assets of what we as consumers have, know, and do. Data isn’t just data, it has become the lifeblood of modern enterprise.

The lessons of digital economics cover much more than a review of hardware, software, and automation. Digital technologies don’t magically produce decisions that transform data into action, people do. Kahneman and Tversky’s work on Prospect Theory has provided a powerful demonstration of how human bias and perception influence how we look at the data.[iv] Machine learning at best can contribute to our perceptions of value. Data Science involves understanding the nature of the problem to be solved, the quality of the data at hand, applying the appropriate methodologies, and transforming the data into action. The impact of digital economics won’t depend on producing more data, but on promoting the quality of human decision-making.

The study of digital economics is at the heart of the Business Analytics Institute. In our Summer School in Bayonne, as well as in our Master Classes in Europe, we put analytics to work for you and for your organization. The Institute focuses on five applications of data science for managers: : digital economics, data-driven decision making, machine learning, community management, and visual communications. Improving managerial decision making can make difference in your future work and career.

Originally published on Medium

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Lee Schlenker is a Professor at ESC Pau, and a Principal in the Business Analytics Institute http://baieurope.com. His LinkedIn profile can be viewed at www.linkedin.com/in/leeschlenker. You can follow us on Twitter at https://twitter.com/DSign4Analytics

[i] Pine, B. and Gilmore, J. (1999). The Experience Economy. St. Paul, Minn.: HighBridge Co.

[ii] … (2016), [ii] A better way to Valuate Companies in a Digital World, Knowledge@Wharton,

[iii] Schwab, K. (2017). The Fourth Industrial Revolution. 1st ed. Random House Inc.

[iv] Kahneman, D.; Tversky, A. (1979). “Prospect Theory: An Analysis of Decision under Risk”. Econometrica.