CIO Challenge: Grow the Business While Cutting Costs
It looks as if business conditions are starting to change for the better, which brings with it a whole other set of challenges.
The new reality is that CIOs must think about data quality's impact on the whole organization. But something that's not often discussed is how bad data quality might be impacting IT itself.
Of course, it's common knowledge that data quality problems costs businesses, big time. Ovum estimated that bad data quality leads to inefficiencies and lost customers, effectively costing U.S. businesses $700 billion a year.
We often talk about the business impact of bad data quality, but using unreliable, outdated data also creates problems for IT, according to Nucleus Research. And that, in turn, creates more problems for the company at large.
How bad is it? The average company's data is only 55 percent accurate and more than 14 months old.
Fourteen months old? SRSLY?
As you might expect, that's not the kind of stats you want to see when you're about to invest big bucks in a technology solution.
What's more, the report found that this use of outdated, inaccurate data is lowering productivity across the board, raising operational costs and creating higher IT risks.
"As a result, IT departments are using outdated [data] that affect their enterprise IT landscape, including architecture, applications, integration technologies, business capabilities, and business processes," states a press release on the report issued by alfabet, which sells IT planning and management software. "Reliance on such outdated and inaccurate information introduces the potential for significant harm to the business by creating compliance risk, draining productivity and adding unnecessary costs."
The report is only available to clients, but the summary does offer some advice about how to fix the problem:
Analysts found that those who implemented planning IT to manage and monitor asset data achieved an immediate increase in accuracy to 88 percent. Those that adjusted their internal processes to fully adopt planning IT improved data accuracy to 95 percent or higher; many indicated they reached 100 percent accuracy.
It seems IT may have found a good pilot project for data quality: Technician, cleanse thyself.