Experts: Technology Is Not To Blame For Data Warehouse Failures

Rachlin also pointed to the challenge of setting priorities in terms of what gets done first in a data warehousing project. Having a method and process to determine those priorities is “very critical,” he stated.

What can be done to overcome some of these obstacles and meet the challenges? Rachlin said getting high-level commitment within an organization is a key factor, along with encouraging broad participation in the project within the organization. “You can’t do this kind of thing on the stealth,” he observed.

One way of encouraging participation is to regularly communicate the status and progress of the data warehousing project to everyone concerned, said Rachlin. He pointed out that “cleaning up hundreds of years of data problems” and setting up the project takes time, energy and effort. This part of the project “doesn’t appear to have immediate results,” so it is important to communicate frequently, he added.

Successfully developing a data warehouse involves “changing the culture, not just the systems,” said Rachlin. There is a need to “broker consensus” from all those involved, particularly in terms of “what things mean and how they will be reconciled,” he continued.

Getting consensus doesn’t necessarily mean “someone wins,” Rachlin noted. “It may mean you have to tolerate and live with four different definitions of ‘premium.’”

Rachlin also recommended “federated ownership and governance” of data warehouse projects, rather than having one small group in control.

Yet another way to help ensure success is to “tie funding to specific deliverables, and to specific lines of business,” said Rachlin. “That’s the surest way to make sure [budgets] are not cut.”

Another panelist, Mike Heilman a business technology consultant at Nationwide Insurance Company, Columbus, Ohio, agreed on the importance of finding an “executive sponsor” for a data warehousing project. “If you don’t get that commitment, you will not succeed,” he asserted.

Heilman also agreed that establishing data definitions is a key to success in data warehousing projects, as well as aligning the project’s goals with the company’s key business drivers, such as profitability.

In addition, Heilman emphasized that “project management skills are the single most important technology resource that comes to play on data warehouse development.” Such skills involve management of technology, people and processes, he explained. “You must balance all three. Any failure in an area means failure of the project.”

Panelist Bill Sinn, director of financial services marketing for Dayton, Ohio-based Teradata, provided a laundry list of reasons for data warehousing project failures. These included: the project being too overwhelming; difficulty in quantifying return on investment; lack of IT proficiency with data warehousing initiatives; the scope being too limited; poor data quality; the project being too expensive, and not having sufficient time.

The key to overcoming such challenges is to commit to necessary changes, said Sinn. “Technology is usually the scapegoat [for project failure], but the technology is proven,” he noted. “It’s really about culture change. It’s pretty threatening to have your job changed.”

Sinn called on those who would manage data warehousing projects to be “champions” of change.

“Data warehousing is an instrument of change, but not an engine of change,” said Sinn. “People are the drivers.”

Reproduced from National Underwriter Life & Health/Financial Services Edition, November 5, 2001. Copyright 2001 by The National Underwriter Company in the serial publication. All rights reserved.Copyright in this article as an independent work may be held by the author.

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