Nearly every midsize and enterprise organization is doing some sort of work on the data front, whether it be projects
around integration, profiling, or quality.
When asked how these efforts work together, however, executives generally don't give much of a response. Indeed, many express no familiarity whatsoever with the notion of data symbiosis -- nor with the possibility that end-user customers could feel the impact of data issues, whether through poor customer service or worse.
There are signs, however, that this is about to change. Realizing that a data quality effort loses much of its impact without a simultaneous data integration push, organizations have broadened the ambition of their data efforts. Merely "cleaning things up" is no longer enough; one-off data projects are now regarded as woefully insufficient.
In the past organizations tended to believe that most integration/profiling/quality efforts have a finite starting and ending point. Never mind that this mind-set didn't exactly gel with reality, which is customers move, products change, and companies merge.
"What companies are starting to understand is that data management is a continual process," said Filip Sanna, director of product solutions at Harte-Hanks' Trillium Software. "I think they realize it's not something you can just slap a Band-Aid on and be done with."
Added Scott Schumacher, senior vice president and chief scientist at Initiate Systems: "Thinking you can get away with worrying about data somewhere down the road is a mistake."
Lining up one's data integration, profiling, and quality efforts obviously takes a bit more than committing to attentive, ongoing data monitoring, however. The first step toward data symbiosis is generally taking in the big picture, then laying out precisely where data exists within the organization and where it actually needs to be. Given the number of companies that started with homegrown systems before migrating over to a hodgepodge of vendor-provided ones, this often proves easier said than done.
From there, securing senior-level buy-in is crucial. Top execs might not respond to theoretical technobabble about data irregularities or inefficiencies. But if a vendor/consultant type is brought in for a two-day "proof of concept" data assessment, during which a business case for more stringent data management can be built, they might better understand its importance.
"If you tell [C-level execs] '50% of the data in this one particular column is null,' they're not going to get it. But if you tell them, 'Because of the way we're set up now, we can't send invoices to our major accounts without manual intervention,' they start to pay attention," said Scott Gidley, cofounder and chief technology officer for DataFlux.
Once upper management (as opposed to the IT department) throws its weight behind a data symbiosis push, many of the people issues -- getting disparate groups within the organization to play together nicely -- tend to sort themselves out. The technology issues often prove a tougher fix: Without a flexible company-wide architecture, most projects are doomed from the get-go. The solution, it seems, is breaking down the walls between departments: Switching or migrating systems may prove to be a short-term hassle, but it streamlines the flow of data throughout the organization.
And that's when data symbiosis becomes quite important. "Think about it," Gidley said. "A company might be spending $10 million to implement SAP or Oracle. The implementation will be a failure if the data to populate the new system isn't worth a salt."
Beyond low ROI on substantial tech investments, the potential consequences of failing to align one's data integration, profiling, and quality efforts range from massive fines (in regulatory-rich industries like financial services) to the inability to take advantage of existent opportunities.
"If your people don't have an effective view of your data, they won't be able to derive much value from it, in terms of things like cross-selling and upselling," noted Don Tirsell, Informatica's senior director of product marketing.
Much more potentially costly are the effects that poor data practices can ultimately have on the customer. Nobody particularly enjoys spending additional time on the phone with customer service—an inevitable upshot when a representative can't find a customer's record, or has multiple records for the same customer.
As for the future of data symbiosis, while few pundits expect data symbiosis to rocket to the top of companies' priority lists, they believe that the process will continue to inch up in importance. "Before, it might have been in the nice-to-have category," Tirsell said. "Now, it's under mandatory-to-have. Given everything we've seen I don't imagine that will change."
Reprinted with permission from 1to1 Media. (c) 2006 Carlson Marketing Worldwide.