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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


Analytics is the application of mathematical modeling & optimization methods coupled with appropriate visualization, to enterprise and extra-prise information, leading to behavior change amongst business users and consequently, enhanced business outcomes for the enterprise. The early success in analytics has been seen in areas such as marketing optimization (better targeting of direct mailers or e-mails), attrition analysis in Telecom and markdown optimization in Retail.

I submit most large System Integrators (SIs) do not “get” analytics.

One definition of strategy is the positioning one creates by solving a fundamental human problem. I do not see the seminal thinking, building of foundations and the fundamental shifts being attempted by SIs to address the challenge of creating competitive advantage from information. What most SIs do instead is to model data, move data, massage data and report data.  They have built up large revenues and head-count focused on ETL, building/ maintaining datawarehouses, and building/maintaining reports. With scant regards to behavior change caused and business outcomes occasioned. SIs rarely look “inside” data.

The KPO units have done better. They look “inside” data. They house mathematical modeling skills; they engage with business stakeholders at the client; they speak in terms of business KPIs. For various reasons, they often get clubbed under BPO – even though their culture and brief is different. I submit even the KPOs have not moved the needle enough. Often they focus on scaling, automating and cost-effectively executing client-established analytical functions.

Why do SIs not get “analytics”?

Vision and leadership - The role models in analytics – such as Marriott, CapitalOne, JCPenney, Amazon, Netflix  and Harrah’s  – have all had visionary leaders – who saw the potential of analytics to create a competitive advantage. They clearly the set the agenda and vision for the organization. Programs were carved out, organization structures were refocused, and priorities were indicated. The discipline of collecting and housing clean data was established in a sound way.  Board level commitments were made for business results.

Why should it be any different for SIs? If you need to service an analytical enterprise, you'd better also be a believer and a champion. 

Mental model - I got to learn that, at a large SI, the proposal for acquisition of an analytics start-up was shot down because the decision makers did not see it as “IT” work. Our mental model seems to be constraining what and how we service our clients. This was tested in early 2000s when business consulting came into SIs. We suddenly saw people amongst our midst who did not necessarily have an engineering degree, did not code, did not understand web “post” and “get”. It took us several years to accept and leverage the folks with a business background. To me it looks like we are in a similar situation in analytics. We are not sure where this belongs.

Analytics start-ups that get acquired are faced with management who are unsure how to leverage them. Often they are construed as KPO and merged into the BPO business – something I have a problem with.

To compound the problem, analytics is the knotty area that requires collaboration between 4 orthogonal disciplines – business, math, visualization and IT.   If any one of the above 4 attempts analytics by themselves, the results are far short of the full potential – “using information to enhance business outcomes”.

Branding and gumption - Few SIs have the branding, gumption and the inclination to engage on business outcomes. Even during conversations around ERP or CRM implementations (and I hope one implements ERP to further business outcomes!) SIs comfortably lapse to a conversation around budgets, project schedules and project success as opposed to business measures. Analytics without a conversation on business KPIs lapses into outsourcing of data preparation, cleansing, SAS or SPSS programming and reporting. Little surprise that one of the first to set up a Social Intelligence practice is McKinsey.

Measurement and organization structure - I do not pretend to have cracked this one. But the issue here is very simple. If you measure an early stage practice or idea the same way you measure an established practice or unit (say, your BFSI unit), you have setup the early stage idea for an uphill climb, and for possible early failure. If you have an “analytics” unit (and I am not saying that it is the best way to organize analytics in an SI), the revenues from the unit are likely a small fraction of the total.  One way to solve it is to associate this with a “mass” offering, such as business intelligence and datawarehousing. Another is to conceive of other measures – such as “influence revenues” or large deals occasioned.  Quite another is change the structure to embed analytics into each industry vertical unit – a move which probably should be examined 3-4 years down the line when analytics is more mature (remember the days when “Java” or “.net” was a practice on its own?). Either way, there is no substitute to vision and sponsorship from leadership – if the chief does not believe in the analytical enterprise, you cannot go very far.


In summary – clearly start-ups have been successful in creating viable revenues streams around analytics. We now have got to a point where start-ups cannot flourish further without a larger eco-system. Larger organizations are trying to create analytics practices. Their success is limited because I feel they have not understood the challenge at hand. In order to be successful they need to address the issues of

  • Vision and leadership – that understands how they can service or enable an analytical enterprise
  • Mental model – that breaks away from the current business model – and that can accommodate the 4 areas needed to address analytics
  • Gumption – to engage with clients on business outcomes
  • Measurement and organization structures – to house analytics and acknowledge that it can have an impact disproportional to the revenues it brings.

Posted August 6, 2010 8:09 AM
Permalink | 10 Comments |



I completely agree with you that SIs rarely focus on business outcomes of their projects.

As somebody running an Analytics team in a Retail organization I can tell you that the opposite is equally true. Analytics folks are so much 'in' their data, they rarely attempt to understand how that data was created or reported in the first place.

For e.g., one of my guys was working on a pricing problem and after a week of effort, did not know that we don't actually capture the 'price' in our dw. We capture the sales dollars and units, and price is a derived function. (sales/units).

The mental model of analytics folks is similar to the IT folks you mention. The analytics folks believe they need not understand the structure of the datawarehouse. THey go about building reports that can be easily automated using BI tools because they don't understand these tools either.

There's something about us humans that we prefer our silos.

Kishore, I too completely agree with you.

I see Performance management and advanced analytics is the key service line business for the large SIs as part of their "BI Portfolio of services"; but the revenue is less than 1% (of the BI revenue) what I believe.

While large SIs are busy building large number of ETL and reporting (not analytical) jobs, their focus is mininal for the neglible/minimal revenue coming from analytical pieces. Second part is the cost of investment on high end statistical/business analysis folks & tools/technology.

One of large MNC SI in India has 700-800 folks in their analytics team ; 90% of the team busy with using Base SAS and MS Excelsheet doing internal supply chain analysis without understanding the datawarehouse concepts, business outcomes and advanced tools.

The SIs should focus on the customer's business outcomes, build experienced talented team with business domain knowledge, advanced tools and data analysis expertise to enable them to get into analytical business. And this service should be part of operational BI (real time).


I totally agree with you and a great post. To your point and to Kiran Kulkarni's - one more company which 'gets' analytics and 'applies' the same is 'Netflix'.

Not only they invented a new business model, but continue to drive lot of value out of 'data' to bring Netflix where it is today.


Excellent observation and viewpoint! I think this is a mere case of the analytics that SI's themselves look at. SI's are driven by sheer growth of revenue and margin and the market has been good to them. They are more focused on these KPI's rather than raising the bar in consulting where the SI's themselves become true partners for their customers and start engaging in solving the customer's core business issues. The short term goals take precedence. In the long term, when this feasting slows down, clearly the last man standing will be the SI that has invested heavily in the business consulting will end up being the clear winners.

An analogy to this is Apple which is perceived as an OEM but yet does not itself do the manufacturing. The core Apple engineers only focus on solving their customers key issues and envisioning brillant products that can be built and assembled by the numerous suppliers/factories. Its time the SI's modelled their structures around this. Maybe its time the BPO's and KPO's take centerstage and IT services takes a backseat to them.

Nice Thought process and well said. I think now bigger companies are actually behind analytics. They get in various forms, feedback's, competitor sales etc.
I think bigger companies should actually go down to very low level of analytics like.

1. How many times a particular product lets say garment was picked up before being bought at store.
2. How many times customer returned the product etc
3. How many times the product was scanned for price
3. How many times the product was left/passed over the counter.

Now having said that each product will tell its own story and when we collate it corporates can make a better decision.

Hi Kishore,
Your post clearly captures the problem in the way SI’s are approaching the analytics business.

From my experience I would like to share some of the challenges faced by SIs –

1.Large or Medium sizes SIs are following analytics business purely through IT lense.
If one looks closely at analytics business, it has always been around and delivered by pure play consulting firms in the form of projects or programs like Six Sigma implementation. Six Sigma looks at critical business problems statistically/Analytically to identify the root cause of the problem and solve the same. There are some firms who have integrated Balanced Scorecard with Project Management to leverage the strength of performance management in project portfolio optimization and monitoring.
The major disadvantage that these consulting firms face without IT is ability to scale and integrate

2.SIs (Mostly Indian companies) also are facing brand issue:
I was in US last year and travelled across US and met number of customers in different verticals, we had then chalked out an effective presentation to showcase power of analytics and how it can be of immense use to business when coupled with Performance Management. However the problem we faced in most of the places was – brand image, Indian IT companies have built such a strong brand image in AMS kind of work that it surprise and confuses client when you start talking the analytics in business context

3.Back end delivery capability:
Most of the SIs have successfully learnt the art of selling this integrated offering – Analytics with Performance Management, however most of them also lag the required though leadership behind the subject and relevant skills in delivery which can keep the excitement generated in sales pitch through delivery. ( Bunch of BAs in practice does not guarantee the required consulting skills in this line of business)

4.Top Management mindset:
Analytics and Performance management is a value business and not volume. This is major mind set which the top management needs to understand and appreciate. In most of the SIs , though they have started talking about Analytics business, mindset still has remained volume business, which eventually directly or indirectly kills the importance of these offerings in the organizations
To Summarize:
1.There is definitely an immense opportunity for IT companies /SIs in this field, given the fact that scalability in these offering can only come from IT offerings / teams

2.There are many internal challenges to accept and overcome along with major brand re-positioning required

A practical thought around defining Analytics 'analytics is the knotty area that requires collaboration between 4 orthogonal disciplines – business, math, visualization and IT '
Many organisations still treat analytics as a silo discipline or a combination of one or two of the above. Probably this is driven by more from a commercial model than a value driven. May be it’s easy to avoid the challenges of integrating the four directional disciplines!!
In main stream IT we still observe a gap between business and IT, though it’s narrowing over a period of time. Probably the same rule applies to analytics -We may have to wait till then or the ‘mindset’.

Hi Kishore Sir,

I had a smile when I read this blog of yours as it reminds some of my own experiences, and I couldn't resist myself from responding.

"Analyzing the business data is right of a business user." This is something which is generally found missing in the central idea when such SIs plan to provide a so called "Business Intelligence Solution". What I've observed in such cases is that "you please provide me the sample data and the explain solutions which you want to see, I'll make them available for you as a POC." At the end of such dull process a business user only gets a few reports and fancy dashboards and he ends up thinking that "Oh my god!!! I can do it with my Excel. Why do I need this buddy with a company logo and bundles of RFPs, to create these reports??" In this way perception of the Analytics becomes totally opposite of its real meaning.

As said by Kishore Sir that this is a combo of 4 pillars- business, math, visualization and IT. The SIs I am talking about here were able to think only two of above which are - visualization and IT.
In my opinion the idea of Analytics reaches the level beyond any budget and resources when I think from the "Business Perspective". When you start thinking in partnering way to provide the beneficial ideas to the business users first you have to realize yourself at the front seat. But unfortunately a few not more think from the other side of the table. And above mentioned in my response is the real life "start-up" scenario which I've faced.
As far as my experience goes about Analytics, it is not about selling the BI tools, perhaps it is presenting multiple possible ways of solving the same business problem and leave the last decision to the business user to decide which way to go.

Varun Gaur

Hi Kishore,

Very well said and this is indeed fact about Analytics. My two cents would be that many SIs are in the race and feeling lots of pressure on margin/utilization/revenue and struglling within these parameters, though many of them have started building analytics in many areas, but few of them have realized why it is needed and how value can be handed over to business.

In near future, this will be the Hot spot for every SI and also mindset has to be changed in terms of difference in Reports and Analytics which are two different thing.

Keep blogging..



Very interesting thoughts. Most of the SI have evolved as wholsale providers of cheap programmers to build the applications that every business in the world needed them. However, that need has changed with time, but the leadership that you find in most SI today has not. They still see their customer as IT of a business rather than business that needs to leverage information for higher performance.

SI have a choice to make - Continue to be a cheaper IT services provider or move up the customer value chain.

Analytics is a subject of business and not of technology and SI simply dont have that workforce or in such limited numbers that their voice is never heard.

I had written a while back about what SI can do to move up the value chain.....again only those that are interested in moving up the customer value chain. There is a lot that an SI must do to be called an SI....Have we all heard of celebrating 5 years of partnerships and then the customer still not become a reference??

Here is the link in case someone is interested

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