Productivity Thwarted by Poor Data Integration — And Business Users Notice

Any time I have to print something on deadline, I wonder if I’d be better off with a typewriter. Inevitably, the printer will not work, and a lot of swearing and frustration will be involved.

I’m not alone in thinking that. Technology is a lot of work — yes, even Apples — and some days you spend more time trying to get the technology to function than you spend working.

In the past, this kind of time suck was primarily caused by hardware or software problems, but it’s quickly becoming a data problem as well, as data stores grow.

CIOs know this, but sometimes it’s worth noting that end users are aware of the problem, too.

Accenture recently took a look at how this issue is affecting 559 commercial insurance underwriters in the U.S. It turns out, like most of us, underwriters invest in technology because they believe it will help them do better work, with 93 percent saying technology is the best way to improve quality.

Overall, they think it has, too. Two-thirds of respondents said technology has significantly improved underwriting performance.

All well and good — until you get to this: 54 percent said technology has increased their workload.

Why?

• 81 percent blame a lack of data integration across their company as the problem.
• 67 percent cite a lack of process integration.

Yet — it’s still an uphill battle to convince organizations to really invest in a coherent enterprise-wise data integration plan, according to Gartner.

“Addressing requirements early with the business is crucial, because it is easier to architect than to retrofit characteristics that must be present in an architecture for a multimode, multipurpose data integration environment that flexibly operates beyond conventional bulk/batch movements, to include non-bulk approaches for replication, federation and message-based integration,” Gartner states in its recent Magic Quadrant for Data Integration Tools.

Data integration will continue to be a barrier to productivity and efficiency as long as it continues to be an afterthought. Changing that will be key to removing data problems as a barrier to worker productivity.