Purpose Driven Analytics

Focusing on the highest priority goal will yield dazzling results

Purpose Driven.  It sounds simple, so obvious.  It's the foundation of all plans... purpose, goals, objectives, expected results, etc.  The returns and benefits of a well executed Analytics program are proven and well documented.  It can produce dazzling results, improvements in business performance, fantastic rewards and ROI.

And yet when it comes to moving forward with the building of an Analytics system many companies stall.  Most companies are barely scratching the surface of understanding what's possible with Analytics.  Why?

Overwhelmed or stymied as to what to do, the decision to engage is pushed off.  Procrastination sets in.  Resistance to change results in sticking with what's comfortable.  Part of the problem is the complexity of Analytics, there is too much stuff to consider so hardly anything gets done.

What to do?  Commit to Purpose Driven Analytics.  Purpose Driven means focus...  designing a program to accomplish the highest priority objective.  Learning and understanding how to utilize the available data and analytics resources to accomplish that objective.  Focus on the prize. (actionable insight, acquiring customers, campaigns that over-perform, beating the competition).  What is the single most important thing that needs to be achieved?

This single focus enables creating a project that can actually be implemented, measured, and will accomplish the defined goals.  It's still going to be a complex process.  All five Pillars of Analytics: Data, Cloud, Processing, Analytics and Delivery must be addressed.  Diluting any part of the system creates a high risk of failure.  But so does trying to do too much.  Having too many goals makes it impossible to implement successfully.  Develop a high impact plan and execute:

- Purpose - clearly defined needs, problems, purpose, goals to be achieved

- Plan - how Analytics contributes or provides the solution

- Automate - it's Big Data, so it can't be done manually, it must be automated

- Understand the system - All Five Pillars must be executed well

- Implement well, especially end-user involvement.  It's the key to success.

- Measure - how's it working, what's the ROI, what needs to be corrected, how can it be made to work better

As an example, consider Customer Intelligence.  It's everything related to the customer and customer performance.  Customer spend, frequency, profitability, LTV, interests, wants/needs, sentiment, actions, predictive behavior, micro segmentation, conversions, retention and more.  An Analytics system can provide total understanding of customer intelligence in real time.

Data can be collected, numbers crunched, interpretive analysis performed and insight or Conditions of Interest delivered.  Success of the Analytics program comes down to addressing one question really well... what happens when the actionable insight is delivered?  Focus on the goal.  Support the decision management needed to meet the goal.  It's a way of simplifying the process and improving the probability of achieving great results and ROI with Analytics.