Experts: Technology Is Not To Blame For Data Warehouse Failures
Despite reported failure rates as high as 90 percent for data warehousing projects, a panel of experts here said the technology is sound and that many common problems associated with such projects can be avoided.
The panelists attributed many of the failures to corporate culture and other human factors that conspire to hinder or stop data warehousing projects. The remarks came as part of a session entitled “Preventing a Data Warehouse Catastrophe,” during the TechDec Exposition and Conference held here from October 7 through October 9.
A data warehouse is company-wide database that brings together data from disparate units or operations to support marketing and other decision-making in an organization. When the database is organized for a single business unit within an organization, it may be referred to as a “data mart.”
“Despite the high failure rates for data warehousing, people still want to do it,” stated panelist Seth Rachlin, co-founder, president and CEO of New York-based Connect Systems, Inc.
“Data warehousing can deliver significant return on investment across the enterprise,” said Rachlin. “This is true in many industries and it is particularly true in insurance. I still haven’t seen the insurance sector embrace these kinds of technologies the way industries like publishing and telecommunications have,” he added, “but there’s certainly a lot of interest there.”
Rachlin also maintained that data warehousing technologies have matured significantly. “The technologies out there are pretty good,” he observed. “It’s been out for a while and people know how to do it.”
He added that recent development of Web-hosted technologies have made data warehousing accessible to more end users. “From a technology standpoint,” said Rachlin, “implementing a data warehouse is not that difficult.”
According to Rachlin, the principal reason so many data warehousing projects still fail is that “companies are not good at running projects at an enterprise level.
“Particularly within the insurance sector, there is a product or functional focus versus an enterprise perspective,” he continued. “They understand everything there is to know about a particular product they’re selling. They see themselves as completely tied to that product.”
Another reason for data warehouse development failures is that different business units within the same company will have different definitions of common terms, such as “premium” and “agent,” said Rachlin. This complicates the process of working with data from the various business units.
Executives can also get territorial when it comes to ownership of the data between business units, Rachlin noted. Claims of ownership may also extend to distribution networks and to the customers themselves.
Another consideration, according to Rachlin, is that while “data warehouses do great things, they also unsettle people and make them nervous.” The creation of a data warehouse can change the way a company typically does business, he noted, and as a result some shifts in corporate power may take place.
“It does threaten people,” said Rachlin of the data warehouse concept. He added that those who take on data warehouse projects “need to recognize that not everyone is your friend.”