A few years back, the core banking solution (CBS) used by
Centurion Bank of Punjab (CBoP), one of the leading private sector
banks in India, didn’t have any provision for recording the
date of birth of the bank’s retail customers. Then in 2006
CBoP switched to a more advanced core banking platform and also
decided to go in for a business intelligence (BI) implementation to
meet various business objectives.
But after putting in a data warehousing architecture with new
parameters, and consolidating the customer databases residing in
various silo applications as well as all transaction data in the
data warehouse, the bank noticed a snag—the birth dates of at
least half of its 5.7 million customers were missing.
The absence of this data—traced back to the legacy
CBS—made reconciliation and elimination of duplicate entries
a mammoth problem. Says Sanjay Narkar, CTO, CBoP, “A major
issue with all banks is legacy data. The quality of this data is
poor. At the same time, 100 percent data quality is an unrealistic
target.”
The good news is that post-consolidation, CBoP managed to reconcile
data issues to the extent of 3.6 million customers. The remaining
2.1 million customers were discovered to be different entries
posted by the same customers, but as gathering customer information
is still in the happening phase, it will be a while before BI
begins to deliver complete value.
It’s not only the financial sector that is grappling with
data quality. Bajaj Auto still faces somechallenges while
collecting disparate data from various sources even after three
years of SAP Business Information Warehouse (BW) deployment.
“We still face the challenge of data inconsistency but it has
improved to a great extent. Our SAP is an integrated ERP
(enterprise resource planning) system where the data is collected
at the point of transaction itself. Also, the material and
financial accounting system enable data accuracy,” notes
Rajib Kumar Jena, senior manager for MIS at the company.
Drivers of adoption BI applications have been around for nearly two
decades, but of late they have caught the fancy of organizations
which want to derive value out of their accumulated data as a
result of automating their business processes through applications
like ERP and customer relationship management (CRM). According to a
Gartner forecast, the BI platform software market in India is
expected to reach $50.8 million by 2011.
There is no doubt that BI has become more pervasive. Competition
and compliance have been the primary drivers for its wide-scale
adoption. BI is transcending organizational hierarchies and
penetrating various levels of operational and tactical
decision-making in the organization. It is also morphing from query
and reporting tools into areas that include customer management,
risk, and product management.
Yet data consistency seems a distant dream. Issues like name and
address mismatch, missing fields and inconsistent data formats are
some of the common pains in customer data integration across
verticals. “No matter what you do, it is tough to address the
issue of data management. The reason is the dynamism in
business,” comments Sanjay Deshmukh, country manager, India
and Saarc, Business Objects.
Many businesses today are on the path of inorganic growth. Apart
from mergers and acquisitions, the addition of new applications,
databases, regulations and access points for data only add to the
information and hence create new challenges with regard to data
quality.
Organizations forget this when they make a beeline for BI. They
wrongly assume that having enterprise systems like ERP and CRM
automatically ensures data quality and consistency. However,
automation of business processes is a pre-requisite for BI
implementation; it is a critical component of the overall BI
infrastructure.
“For banks, BI wouldn’t make sense unless they have in
place a robust core banking system that records transactions.
Operational systems that have gone through the right maturity cycle
are ideal candidates for BI. What matters is not the amount of
information a user receives with BI but how much of exception
reporting he gets with it,” says Sudipta K Sen, CEO and
managing director of SAS.
The transactions that enterprise applications (such as ERP) record
need to be analyzed for things like trends and performance
improvement aspects, and this is where BI comes into play. It can
help enterprises understand the return on income (RoI) from these
deployments.
For example, with ERP, the time required to shift products out of
the factory could have reduced by two hours, and the time for
printing the delivery slip and ship the goods could have decreased
by an hour. But have these yielded any business benefits for the
CEO and business users?
“Anyone who has implemented ERP is struggling with
information. The reporting system or information delivery system of
any ERP is not good, and that’s why it is a compelling reason
to invest in BI. This is because the information that business
users need for decision making has still not reached them and lies
in the ERP,” explains Deshmukh.
Once these applications get stabilized users start looking for data
that is cross-functional because they want to have a holistic view
of the data that resides across all the applications in the
enterprise. That’s where the other equally important
component of BI infrastructure—data warehousing—comes
into play.
“Data warehousing is a better option because if a user has
SAP he will query the SAP database directly, or if he has an Oracle
he will query the Oracle database. This creates problems because
you are upgrading and querying at the same time. Also, since you
need one version of the truth, you do not want to reconcile the
data between all the different applications that you have,”
says Bhavish Sood, principal analyst, software markets, technology
and service provider research, Gartner.
According to a Gartner report, 60-70 percent of the BI challenge is
about cleansing the data, getting it out, transforming it
correctly, and storing it in a properly designed warehouse.
“We are seeing very strong data warehouse adoption among all
top SAP customers. At least 70-80 percent of them are having BW
projects; if an organization has 500 ERP users the BW users could
be around 2,000,” estimates Atul Sareen, VP, overlay sales,
SAP India.
According to Sareen, most of SAP’s customers are looking at
analyzing operational data gleaned from their ERP systems to do
things like making intelligent decisions, checking out which
customer or region is more profitable, performing simulations, and
finding out the impact of a variable on the company’s top and
bottom lines.
The prime driver for BI users is the gain that they realize by
having a single coherent view of data across the organization.
Also, with the nature of tools available today, most BI
implementations find that users can easily perform their own
analysis and essentially break actions down to simple decisions.
Also, as interactions between organizations and their customers
evolve, having a common view of historical data has become a
necessity.
“Solution providers can build the best systems but if an
organization hasn’t got the skill sets to analyze the data
and execute on that analysis, and hasn’t got the business
processes to utilize that analysis, it is ineffective,” says
Dennis Samuel, area VP, South East Asia and India, Teradata (a
division of NCR).
According to industry opinion, it is essential that organizations
have a mature and stable IT system. There must be a need for
analysis and the users must be prepared to adopt the system. Also,
a proper online transaction processing system should be in place so
that the given data can be pooled in systematically.
“However, the ability to scale BI operations across more
users, and the latency of information available for BI-based
analytics, is still a hindrance for many users. A large number of
BI implementations still load their data once a week or once a
month, which has a negative effect on decision making,” says
Arun Ramachandran, director, technical, Sybase.
Also, it is imperative to have a dedicated analytics server to
handle data warehousing requirements with ease for faster and
optimized query performance. Another common challenge for
enterprises is the lack of clarity of specification requirements
and lack of ISVs skilled in implementing BI in a cost-effective
way.
“Often there are changes in user requirements during the
deployment phase. Incorporating these changes on the go needs a
dynamic implementation of BI to fulfill user requirements,”
says Pallavi Kathuria, director, server business group, Microsoft
India.
As organizations extend BI tools to more users within the
organization, they will also have to prepare the end-users to use
these tools. What if a successful BI project delivered a churn
rating for a customer but the input was not used by the concerned
department within the organization? The value made by the correct
delivery of information will never be realized, and hence deliver a
negative return.
Jena recollects that getting users to use the information was
another challenge which Bajaj Auto had to face. “Now we are
in the process of creating personalized Web-based reporting
irrespective of the levels in the company. As a result, instead of
asking for reports, users can themselves access reports, select key
performance indicators, define thresholds values, and drill down on
issues.”