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Rajgopal Kishore

Welcome to my blog. I wish to share best practices, insights and trends on business intelligence (BI). To me BI is about measuring your business, discovering performance levers and enhancing business performance. Effective BI is a closed-loop feedback system that learns constantly and is reoriented based on performance improvements.

Tools and technology are part of the solution but are not the solution in themselves. Too many organizations have all the right tools, technologies and technical skill sets but still fall short of effecting performance improvement.

This blog is about the problem-solving approach required to make BI impact business performance. My blogs share my personal insight gleaned by consulting with Fortune 1000 organizations and creating world-class SI practices. Some of the themes I write about include:

  • Gaps in current tools and technologies
  • Suggestions around organizational structures and skills
  • Making IT successful in BI
  • Client experiences - both good and bad

Join me in this endeavor.

About the author >

Rajgopal Kishore is an accomplished industry leader with more than 20 years of experience. He consults with Fortune 1000 clients around IT and BI strategy. He has jumpstarted and scaled IT/BI consulting practices at top-five outsourcing/system integration companies. His personal passion is to help clients realize business value from technology and outsourcing decisions. Over the last decade, Kishore has consulted on enterprise architecture, IT optimization, architecting complex transaction systems, performance assessments, IT strategy and BI strategy. While building consulting and solution delivery organizations, Kishore has relentlessly focused on listening to clients and providing solutions to real client needs as opposed to articulated requirements. In his last stint at a major IT outsourcer, Kishore felt a need to reorient team members to consultative engagements and, as a result, he created a game-based and case study-based consulting workshop. You can contact him at

February 2010 Archives


Sure you have spent several years on developing your datawarehouse, data models, ETLs, and reports. I understand it is hard work. Sure your programs are regarded as IT successes.

But are they also regarded as business successes?

I have been speaking to many IT and business leaders anchoring large BI and analytics programs. Most seem to get this immediately.

Have you measured the business value of your BI/Analytics program?

You offer to measure and help improve business performance (that is my definition of BI). However... 

Have you done BI on your BI?


Let us get more specific.

  • Which reports were accessed, how often? By whom?
  • What do business users actually look for when they read each of your reports?
  • What conclusions and insights have they gotten from each report? 
  • Do they continue to glean such conclusions repeatedly over time?
  • What action have they taken after viewing your reports?
  • What performance levers /casual factors did they discover when using your analytics?
  • What impact did those actions have on specific business KPIs (WIP inventory, markdowns, backhauls, churn, CSAT are some)
  • What behavior change did your reports occasion? (for example, do despatchers now routinely look for backhaul optimization?)


These are hard questions. And often so enormous that we are afraid to confront them. We prefer the comfort of technology - it seems more tractable.


However, when we choose to confront this Gordian Knot, the answers can be pleasant. We can create BI and analytics programs that deliver more business value, at a lesser cost, in shorter time frames.


Here is some guidance I can provide from my experience:

  • Begin with the resolve to address 2-3 specific business pain points
  • Obtain full buy-in of business stakeholders to address the aforesaid pain points
  • Start with a sub-set of data available that is trusted by business
  • Start with a small set of dashboards that capture metrics and KPIs that link to the business pains
  • Link every report or dashboard to possible insights and actions
  • Provide ways to explore data. If a report cannot lead to insights, question its value
  • Do not look to bring all data into the datawarehouse. It is OK to use SOA - Data as a service to perform some parts of exploration
  • Seek to understand the conclusions and insights business users are looking for - and seek to automate the discovery of those insights
  • Business never worries about the norm, but looks for exceptions. Seek to understand the exceptions business is looking for and figure out ways to alert them of the same
  • Bring close-looped-ness into BI - your BI program needs to learn with every iteration
  • Explore ways to loop-back conclusions of BI into transactional systems - "automation of action on insights!"






Posted February 7, 2010 1:59 AM
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