Data monetization is promised to be the next big thing. Analysts and consultants are promising hundreds of billions in revenue (e.g., McKinsey 2016). Her excellence the German Chancellor, Angela Merkel, is addressing the downside, sternly warning German industry to catch up: “If we let this element of value creation be taken out of our hands, then it will be a rude awakening for Germany as an industrial country” (Merkel 2019, link, at 13:17).
Yet, today, most companies are busy spending money on data – not making money with it. Most companies are spending big bucks on data storage, creating vast data lakes. Why? Because influential academics, such as Michael Porter, say so (Porter & Heppelmann 2015); and your own data scientists are always asking for more data. Yet, if you ask how much more data … then … well … it gets complicated. And this is where data monetarization gets stuck right at the beginning. We don’t even know how to measure data quantities properly. So, we asked leading data experts; and this is what they answered:
Figure: How to measure the size of big data?
Unfortunately, it seems, there is no easy answer, which translates into a big management challenge: How do you manage something that you cannot even measure? Peter Drucker, the father of modern management, had established this management rule many decades ago. With data and data science, we cannot even measure quantities properly.
McKinsey & Company. 2016. Monetizing car data. Advanced Industries Report (September), link
Merkel, A. 2019. Speech at Digital Gipfel (2019-11-29), link
Porter, M. E., and J. E. Heppelmann. 2015. How Smart, Connected Products Are Transforming Companies. Harvard Business Review (October), link
Schlueter Langdon, C.,2018-2019, Survey of data experts in business – not academia, Peter Drucker School, Claremont Graduate University, link