Defining Analytics for the Industrial Internet of Things - Part 1 of 4

Industry Trends

I believe it was Tom Davenport who first proposed three categories to describe different classes of analytics:  Descriptive, Predictive, and Prescriptive.  That framework has been valuable to help people understand where they currently stand with analytics, and what they might be able to achieve in the future.  However, time and technology inexorably move on.  In the two years since the framework was first proposed, demand for visual data discovery tools, such as TIBCO Spotfire, Qlik and Tableau (in particular) has been strong. 

As a result, at ARC advisory I've found it helpful to extend Professor Davenport's framework to accommodate emerging technologies. I use four categories in my discussions with clients (see diagram below).

Image removed. 

I'm not sure this Venn diagram style graphic is ultimately going to be the best visual for this approach.  But, it's the best I have so far because:

  • It shows there is some degree of overlap between the various categories.  I find this useful, especially as the boundaries between categories blurs over time as software vendors develop and enhance their solutions.  In reality, that overlap between categories is really a spectrum as I'll explain in my next blog.  But, that hasn't seemed to be an issue so far.
  • I can vary the area of the ovals to emphasize different variables to suit the situation. For example, I can use the size of the ovals to approximate relative presence of the different types of technologies within a particular industry.  I can also use the overlap between ovals to show how much the boundaries between the categories has blurred as solutions have matured.

In the rest of this blog series, I'll look at each of these categories in turn, provide practical examples of each to help understanding, and discuss the role that each category may have to play in the emerging Industrial Internet of Things.

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