Perspective

Dysfunctional Analytics

How do you know if your analytics is failing

Dominic Vincent Ligot

2 November 2018

How do you know if your company's analytics is failing? And if you find out, how do you fix the problem? Dysfunctional analytics can either be an obvious or latent condition depending on the situation, but executives should be aware when symptoms of dysfunction emerge and move quickly to deal with it. The cost of mis-informed decisions can be greater than the opportunity loss of having no information to begin with.

5 Dysfunctions Book

5 Dysfunctions of a Team


One management book I love re-reading is Patrick Lencioni’s Five Dysfunctions Of A Team. The book details five common causes of team dysfunction, the likely behavioral root causes, and ways to deal with them. I’ve personally used the framework in effectively managing small and large teams, and I also find them useful taken in the context of analytics.

Symptoms of Dysfunction:

Behavioral Causes:

Competing on Analytics Book

Competing on Analytics


Any management framework like Patrick’s 5 dysfunctions is only as good as the users of the framework. The key is not just proactively spotting the symptoms early enough, but also moving quickly and decisively to address them. Of the symptoms, reporting errors and delays are the first things to spot, but they don’t necessarily denote any real dysfunction since these things will happen over the course of time. What should cause concern is if the problems in the way a company generates information and insight keep coming back or no clear course of action to resolve them seems to be evident. Worst of all: if no one appears to care about it.

Team Dysfunctions Hinder Analytical Competitiveness

Continued prevalence of dysfunction may also indicate a problem in how analytics is viewed by the company. In Competing On Analytics, Tom Davenport and Jeanne Harris shared four (4) clear pillars common among analytically competitive companies. If and when symptoms of dysfunctional analytics emerge, I find it useful to start asking questions around these pillars to help spot the underlying root-causes of the problem:

Although based on Harris and Davenport’s research, the presence of all four pillars above indicate a company that is analytically competitive – I also believe when one or more of the pillars above do not yet exist in a company – that absence can be the breeding ground for the dysfunctions to occur.

Happy team

Happy teams produce better work


Analytical Leadership

Going back to Lencioni’s framework, there are also five paths to resolving dysfunction. They appear simple, but also taken against the four pillars above, they are very straightforward ways to achieve competitive advantage through analytics:

At the core of it, the symptoms, root causes, and solutions to dysfunctional analytics is the same as that of dysfunctional teams. On the other hand, a healthy team culture also reinforces a healthy analytical culture and vice-versa. As companies move forward in this era of big data they will have more to gain from driving better analytics, and also a lot to lose by not encouraging it.


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Dominic Vincent Ligot
Doc is the founder and CTO of CirroLytix where he helps companies understand and adopt big data analytics to drive business value. Great analytics requires good data and great people and Doc is passionate about both.

This article first appeared on Linked-in.


 
 

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