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Business Intelligence: Outsource With Control

Whether you choose to farm out all or part of your business intelligence, you need to make sure the quality of your data won't suffer.
 

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October 06, 2003 (Computerworld) -- Business intelligence -- the collection and analysis of a company's most valuable data -- seems an unlikely task to farm out to contractors. But some companies are doing exactly that. Why? Because they lack the in-house skills needed to perform statistical analysis or maintain a data warehouse. And if you want to turn BI over to the experts, there are more options than ever -- along with the same big worry: losing control of your data quality.
At Canon Information Technology Services in Chesapeake, Va., the technical support subsidiary of Canon Inc., the decision to outsource data mining and analytics was simply a case of finding people with the right expertise at the right cost.
"I had been doing [basic] analyses on Excel spreadsheets of our customer feedback data," says Mike Larson, assistant director of product and process quality at Canon ITS. But he wanted more power to do full-fledged data mining and the ability to give support managers online access to reports.
"Our analytic expertise, when it comes to slicing and dicing information, is just not that deep," Larson says. So that left him with two options: buy packaged analytic software or outsource.
After looking at what it would cost to buy the applications and infrastructure and hire additional staff, Larson explains, Canon ITS concluded that it would cost at least twice as much to do the work in-house as it would to hire CustomerSat Inc., an application service provider in Mountain View, Calif. The ASP's clients pay annual hosting fees of about $100,000 on average, according to a CustomerSat spokesman. Canon ITS signed a one-year contract in April, and the service went live in June.
Each night, CustomerSat uploads data from Canon ITS's two CRM systems, which handle phone and e-mail support. A typical data set includes items such as customer name, description of problem, product purchased and type of interface employed.
"Data quality is a very hot issue for us," says Larson. "The data we export to CustomerSat is just part of a bigger initiative" that involves taking responsibility for data quality across the multiple in-house customer databases. "We screen for things such as duplicate names and bad e-mail addresses," he says. And Larson does some tweaking on his own, such as setting up business rules to ensure data quality.
CustomerSat generates daily, in-depth questionnaires that go out to a random sampling of Canon ITS customers, and Larson keeps an eye on the process and sample sizes.

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