What does it take to achieve analytics maturity?  Earlier this week, Dave Stodder and I hosted a webcast with a panel of vendor experts from Cloudera, Microstrategy, and Tableau.  These three companies are all sponsors of the Analytics Maturity Model; an analytics assessment tool that measures where your organization stands relative to its peers in terms of analytics maturity.

There were many good points made during the discussion.  A few particularly caught my attention, because they focused on the organizational aspects of analytics maturity, which are often the most daunting.

Crawl, Walk, Run:  TJ Laher, from Cloudera, pointed out that their customers often a crawl, walk, and then run to analytics. I’ve said before that there is no silver bullet for analytics.  TJ stressed the need for organizations to have a clear vision of strategic objectives and to start off with some early projects that might take place over a six month time frame.   He spoke about going deep with the use cases that you have and then becoming more advanced, such as in bringing in new data types. Cloudera has observed that success in these early projects often helps to facilitate the walking and then, ultimately the running (i.e., becoming more sophisticated) with analytics.

Short term victories have long term implications:  Vijay Anand from Microstategy also touched upon idea of early wins and pointed out that these can have long term implications.  He pointed out that it is important to think about these early victories in terms of what is down the road.  For instance, say the business implements a quick BI solution.  That’s great.  However,  business and IT need to work together to build a certified environment to avoid conflicting and non-standardized information.  It is important to think it through.

IT builds the car and business drives it.  Ian Coe, from Tableau, also talked about IT and the business working together.  He said that organizations achieve success and become mature when teams work together collaboratively on a number of prototypes using an Agile approach.   The over the wall, waterfall approach used by IT in the past won’t cut it because moving forward with analytics involves people and rapidly changing questions.  Tableau believes that the ideal model for empowering users involves a self-service BI approach. Business people are responsible for doing analysis. IT is responsible for managing and securing data.  This elevates IT from the role of dashboard factory to architect and steward of the company’s assets.   IT can work in quick cycles to give business what they need and check in with business regularly.

Of course, each expert came to the discussion table with their own point of view.  And, these are just some of the insights that the panel provided.  The webcast is available on demand.   I encourage you to listen to it and, of course, take the assessment!

AMMA_Stages

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One thought

  1. I think a lot of people expect to “run” right out of the gate and then get frustrated with their BI system isn’t exactly what they wanted. But every new project comes with a learning curve and you have to be patient and really learn how to use the tool in the right way so you get what you want out of it.

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