Collecting the right data and combining it in the right way has allowed digital frontrunners to unlock exponentially increasing value. But how do they do it?
Historically, companies have only had access to relatively limited data, either generated by internal operations or collected through surveys, focus groups, research etc. Now the situation is radically different. Companies can collect staggering quantities of data from the products themselves and external sources.
The data may come in a wide variety of formats, which conventional approaches to data aggregation and analysis are ill suited to manage. To unearth insights from this wide array of data, you can create a “data lake”, a repository in which disparate data streams can be stored in their native formats. From there they can be studied with a set of new data analytics tools. These tools fall into four categories: descriptive, diagnostic, predictive and prescriptive.
Individual products can apply simple analytics to their own data to reveal basic insights. Deeper insights can be made on the “lake” of pooled enterprise, product and external data.
The model is illustrated below.
Based on Michal E. Porter and James E. Heppelmann: How Smart Connected Products are Transforming Companies, Harvard Business Reviews, October 2015
We believe companies that manage data in this way have got it right. How do you do it?
“How Smart, Connected Products Are Transforming Companies”, Porter and Heppelmann, HBR October 2015.
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