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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 rkishore9@gmail.com.

 

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!"

 

Cheers!

 

 

 


Posted February 7, 2010 1:59 AM
Permalink | 3 Comments |

3 Comments

Thanks for the insights Kishore…
I posting these words as an understanding of your blog and also sharing some info that I have gained thru experience. The comments have been divided into 3 parts
1. WHAT to do
2. HOW to do.
3. Conclusion

Section 1: WHAT TO DO
The Simple cycle of following 4 steps are a part of any project / activity and business problem solving .
Step 1: Identify
Step 2: Plan
Step 3: Act
Step 4: Measure
STEP 5: GO BACK TO STEP 1 TO Improvise / Correct / Re-plan

The true value that we add as a consulting partners ARE NOT in STEP 1- 4 but ONLY when we iteratively go to STEP 5.

This is very well put across in your blog when you stated
Quote
• “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)
Unquote

Section 2: HOW TO DO
Another challenge that is commonly faced is “From where to start?”
The favorite point will be to initiate a balanced Score card for the Business and then seek the Priority from the stakeholders of the business within the 4 perspectives of
a)"Financial",
b)"Customer",
c)"Internal Business Processes", and
d)"Learning & Growth")..
The next step will be to minutely dissect it further to align it to SPECIFIC Business pain points and converting them into Measureable performance indicators.
It will be advisable to have a dash board which represents these pain points and highlight it.
This has been captured in the points as stated below
Quote
• 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
Unquote

CONCLUSION:
THE SYNCH BETWEEN WHAT TO DO AND HOW TO DO:

The best results of the business are derived when the sections mentioned above” WHAT TO DO” and “HOW TO DO” are synchronised and then monitored closely.
The points provided by you are thought provoking in their own self. I am reproducing it again to reemphasize on synching.
Quote
• 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!"
Unquote

cheers

Really a very thougtfull suggestion.

The deployment of BI application should be seen as a 'half time' in any sporting event and not as 'the end' of a movie. As BI is not just about converting data into information, it is about converting data into ACTION (ideal it should be dollars!!). I think process engineering and change management should be an integral part of any BI initiative, and entity such BICC can play a very important role over here.

As technology improved, service providers became ambassadors of product vendors, and business case was forgotten. I see a recent change in this trend. ( On a different note, there are customers these days, who want to use white board instead of power point presentation to avoid being carried away by flashy colors. ) 'Build small' approach is also being increasingly adopted by BI leaders these days ( in fact, this is just a repetition of history and we could not forget the Kimball- Inmon stories of building information warehouses).
Real clash is when the long terms goals fall out of phase with immediate goals technically. Can it clash? Yes, it can. And industry does not have an answer for this yet. Say we build something real small to address one or two pain points. Yes that will work for the time being. The moment business wants to see the universal customer base for the business across different lines of businesses, you need an enterprise approach. That is exactly when we will see what we built as small goes through a large amount of rebuild to accommodate master reference data.
Inmon suggested in his CIF a federated approach for building information warehouses. Still I do not think that as a solution, but more of a framework. Real issue is to justify our timelines &cost for futuristic harvest, taking a big approach today. So by and large, it is true that 'build small' works, unless someone does not count on the throw away, as the enterprise grows and becomes more information centric.
My response to the situation in hand would be to harvest on hosted solutions. Can a congregation of service providers come forward and absorb the cost of building a solution (with their intelligent business sensing ability), and charge the enterprise on usage basis? I understand it is quite risky (still the issues of security and compliance hanging around). But unless we do something radical about this 'big vs. small' approach, history will keep repeating because the question is ageold 'how to prove RoI quickly on BI solutions?'. And the hybrid approach keeps riding as always. BI has conceptually developed so much and technologies more so. But the question we have seems basic, and implies the IT industry’s lack of maturity in advancing business solutions to next level. So yes, this blog goes to the basic and gets it correctly. But I think we need something more radical. Close looping is an essential element in proving RoI as the blog suggests, but challenge remains there as well, once we adopt enterprise wide approach.

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