Companies are now looking exclusively at business outcomes

Are we seeing the emergence of converged solutions with

BI, analytics and DSS meshed together?



One of the big areas we are focusing on is making it very easy to insert

scoring, predictive models and decision making into real-time business

processes. For example, to have a process to open a new credit card account or

file an insurance claim, that enables you to get real-time risk scores on those

accounts or claims based on predictive models. We want to make it extremely

straightforward to insert that piece into the business processes so you make

more intelligent decisions. It is really where we are going from a technology

standpoint. The point is, to make the decision support technology pervasive, so

it is no longer just the realm of statisticians and IT analysts.

Tell us about your approach in the business analytics market and its key

differentiators?



We provide the most sophisticated businesses and IT capabilities to clients

that help them manage, capture, integrate, analyze and predict on the widest

range of information within and outside their organization. We have done

fourteen acquisitions since 2005 to further extend our business analytics

portfolio. Moreover, a significant part of IBMs $6 bn investment in R&D is

focused on driving innovation around business analytics. As per our estimates,

the opportunity for business analytics today is $100 bn (hardware, software and

services) and growing at 8% annually, faster than the overall IT marketplace.

How does one arrive at an optimized business outcome?



You could make decisions just in the context of information available from

ERP or CRM systems; but IBM believes relevant data resides in a lot of different

places. Social networking and web 2.0 style applications, for example, are

leaving tonnes of clues behind as to what people are thinking. You can also do

surveys to develop attitudinal data. In the consumer packaged goods space, they

do focus groups and scientific research on emotional reactions to products. IBM

can pull data together from a lot of sourcesstructured and unstructured, within

the enterprise and outside the enterpriseto make the model even more accurate.

That offers advantages that are greater than what you can learn by focusing on

data within a particular application silo.

Is recession acting as a catalyst for the business analytics market?



A lot of companies are now looking exclusively at business outcomes. Yes,

you need technology and speed and feed to deliver a business outcome; but

companies are very focused on the end game. They will say, "Were a telco and we

need to reduce customer churn. How do we do that?" Or "Im a police chief and I

need to do smart things to reduce crime in my area." IBMs Smarter Planet

strategy is all about taking the petabytes of new data that gets created every

day and mining that for insights to build competitive advantages. Here SPSS fits

in really well because it comes at that challenge from the angle of

understanding social behavior. If we have a data-rich environment, we can build

a model that can predict what the outcome is likely to be.

Is business analytics getting verticalized, specifically for the needs of

verticals like financial services, manufacturing, etc?



We are headed in that direction, and we believe that you can have

accelerators and prebuilt models that can significantly reduce the time to

value. We see models as something that companies will view as the source of

their competitive advantage. There are certain things that are common to all

companies within a specific industry, but the company-specific insights that you

can add to a model can be a differentiator. A model built for one insurance

client may not apply to another. You have to look at the customers data and

then build multiple models using multiple statistical techniques. You also need

an on-going feedback loop to ensure the accuracy of your model. That means you

keep a track of accuracy using champion and challenger models.

Shrikanth G



shrikanthg@cybermedia.co.in