What Kills Analytics?

j0443263Failure is, unfortunately, an option in the world of high-tech, high-touch solution roll-outs.  We’ve all been there.  The best laid plans of IT and management spiral into a morass of useless data, pointless reports, and unused technology.  How, as technologists, do we best learn from mistakes to ensure successful technology implementations?  In a word, research.  We must look at all data points available to us and leverage all useful bits of information to ensure a successful rollout.

 This thinking was key to us in reading this article on BeyeNetwork which points out the five factors that kill analytic implementations for two-thirds of the large companies in the United States and the United Kingdom.  Pay attention here folks.  This article is written by the CEO of Accenture Information Management Services – ensuring successful technology rollouts is what these folks do for a living:

Five Factors Killing Analytics:

  1. Management Fails to Embrace – management must support and embrace using analytics to better the business.
  2. Failures in Data Quality Assurance – very simply, garbage in garbage out
  3. Unstructured Data – voice, video, and other unstructured data – organizations need a plan for unstructured data as part of an analytics implementation, it is often overlooked
  4. Legacy Systems – as part of a new rollout, which legacy systems to keep and includes, which to modify and which to end-of-life
  5. An Inability to Decide What “Success” Is – What’s the goal(s) of the analytics project?  Tied very closely back to factor number one in this list; without agreeing to the success metrics before starting, there is no tangible way to determine success

If you are considering an analytics rollout, have you considered these factors?  Are there others that you’ve discovered? If you have executed an analytics rollout, did you hit any of these factors along the way?  If so, how did you resolve them?

Bill Peterson
Spotfire Blogging Team

Image Credit: Microsoft Office Clip Art