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Blog November 23, 2017


Enfo's Johan Ripgården participates to Gartner Data & Analytics Summit in Frankfurt 20.-21.11.2017. In his blog post Johan share's insight from the second inspirational day!

Here we go again, here are a few observations from Gartner Data & Analytics Summit in Frankfurt, day 2:

AI, IoT, Machine Learning, RPA…. - It is about time we get started people!

Listen – if you attend an event like this or read any business- or technology newspaper on a regular basis you are most likely overwhelmed by the hype around artificial intelligence, internet of things and machine learning. And, it has already been going on for a while by now. So, what is different now?

The simple answer is that the technologies have matured and are just waiting to get deployed! And, there are plenty of documented success stories to get inspired by.

But wait – do we have the skills and organization in place?

One of the main obstacles is that organizations lack the appropriate skills. After all data scientists aren’t easy to come by. But, before that becomes an issue, you need someone to drive these initiatives. Gartner have been predicting the need for CDOs, Chief Data Officers or CAOs, Chief Analytics Officers for years by now (and still do…).

After all, if data is the new oil someone must make sure to drill for it. It is apparent that there are still very few CDOs and CAOs around. This will most certainly have to change for any organization that want to remain competitive in this digital era. 

And is our current analytics solution really doing its’ job?

I was pleased to see that one of Gartner’s sessions focused on how to “Make Your Metrics Meaningful” (James Laurence Richardson). He presented studies that showed that 80% of existing analytics solution content consists of lagging indicators. A lagging indicator is a metric that is descriptive, it represents history. It will help us understand our business but is reactive and will have limited effect on behavior improvements (=change). A leading indicator on the other hand is proactive, it measures (and therefore promotes) a desired behavior that we know will lead to satisfactory results.

So, if we struggle with defining leading indicators it is understandable that we struggle with predictive- and prescriptive analytics. But defining a leading indicator is usually not that hard as long as you know what drives your business.

Johan Ripgården, 

Analytics Advisor