Data management has become a strategic issue for organisations. A phenomenon accentuated by the rapid advances of Big Data and the Internet of Things. Nicolas Glady, Executive Vice-President of ESSEC Business School and Doctor of Econometrics takes stock of this new data economy and the challenges that arise from it.
How would you outline the meaning behind the term “data economy”?
Nicolas Glady: This term encompasses the use of data by companies with two main purposes. Firstly, front office uses, such as customer recommendation for designing new products and services. Secondly, back office uses, for example optimising processes in a supply chain. The data economy is also born from “pure players” such as the GAFA web giants who successfully built their business model through monetising activity data.
On the tools side, the adoption of Big Data technologies and the Internet of Things is opening up new market segments. A typical example? Smart cars and manufacturing components within engines to save energy.
How is managing data a strategic priority for organisations?
N. G.: Put simply, first of all it enables companies to target consumers better, by offering a distinctive advantage over a competitor: to send out the right message or the right offer on the right channel, in the right format and at the right time. It is then an important lever for analysing the company’s activity in order to reduce its operational costs.
Data itself has a commercial value. It is a real asset for a company when it is sold to third parties. Unlike oil, when we use – or share – data, it does not “run out”. But beware; if everyone ends up having the same data (especially competitors), it will lose its differentiating value and competitive advantage. And today we’re facing another problem: it’s difficult to estimate the value of a database, because we don’t know the quality of the data before buying it. Research is currently underway – for example at the ESSEC – to produce more accurate data valuation models.
So the data in circulation has very different values?
N. G.: It all depends on the type of company exploiting the data, the target audience etc. The data is not objectively and globally quantifiable. The very fine data when it comes to the gender of a segment can be very relevant for a fashion retailer, less so for selling a video game.
One thing is certain: it’s important to pay close attention to the data generated by users – user generated content – via social media, comments etc. Here the source is no longer the company but the users themselves. Texts, photos, videos etc … an unprecedented volume of data is available reflecting the customer’s behaviour. This poses certain technical challenges, namely how to structure it, which requires image recognition technology etc. Taking full advantage of Big Data means including this user generated content and associating it with already massively structured data that comes from customer journeys for example.
The data economy is also bringing forth new players dedicated to analytics…
N. G.: Data analysis has become a widespread concern. Many different companies support their customers over their data: big manufacturers, consulting firms and of course start-ups. In fact we work with Digital & Ethics in our data exploitation business models. The same applies to data as any business activity: if it is a company’s core business, it will internalise its resources. For all others, calling on experts to optimise a support function or side activity is the preferred solution.