Report: 25% of Critical Data is Flawed
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Many major companies are making crucial business decisions based on flawed data, according to a new study from Gartner Inc.
More than 25 percent of critical data within Fortune 1,000 companies is incomplete and inaccurate, say analysts from Gartner, a major industry research firm based in Stamford, Conn. Although many executives aren't even aware that they're working with flawed data, the ones that do often reach for the wrong technology to fix the situation, reports Ted Friedman, principal analyst for Gartner.
''Most enterprises don't fathom the magnitude of the impact that data quality problems can have,'' says Friedman. '' These problems cause wasted labor and lost productivity that directly affect profitability.''
Friedman also notes that executives are mistaken when they look for a quick fix. They look to technology to resolve data quality problems, without focusing on the human and business side of the process first.
''It's important that before a business worries about how many terabytes of storage they need that they figure out what kind of data and how much data is going to be useful to their business,'' says Haff. ''Not everybody is going to benefit from a Wal-Mart level data warehouse or a an Amazon.com level CRM system. It needs to be appropriate to the scale and the type of business.''
Don't misunderstand. Haff says the technology will be critical. But cool tools will do no good if the data is inaccurate, incomplete or inappropriate going in.
''There's applications and hardware available out there,'' he adds. ''And they're not perfect, but there is fundamental technology available to put very efficient customer relationship management or supply chain management systems out there. But before anybody does that it would, be a good idea to assess the business needs. It's an upper-level management question and not just an IT management question.''
But flawed data isn't a new problem.
Haff says businesses have been dealing with problem information as long as people have been in business. It's just that today, businesses are much larger, span countries and continents and are capable of collecting mountains and mountains of information -- flaws and all.
Executives are making decisions about expansions, sales, marketing plans and even layoffs based on market share information, who the biggest competitors are, where products are selling the best, where they're not selling and how much money their customers have to spend.
If the information is off, so are the decisions.
''Executives should be able to have a better handle at least on the cut-and-dry facts on their own business,'' says Haff. ''There was a time when many businesses would have had trouble even knowing how many widgets they had sold in the previous quarter. with today's systems, there's fewer and fewer reasons why that data shouldn't be readily available and quite accurate.''
But the data being collected quickly becomes more complex than that.
Business partners need to be taken into account. Corporate divisions are being added and subtracted. New products are being developed and others are being taken off the shelves. Numbers in London may be tabulated differently than they are in Chicago. There's a lot of figuring to do. And there are countless numbers to keep track of.
Haff says the best thing to do when it comes to managing this data is for IT to sit down with business executives and figure out exactly what data is important. From there they can figure out where it needs to be stored and how it needs to be analyzed. Once the process is in place, the technology can be chosen and installed.
''What's causing the flaws in the data is not a computer inaccurately calculating that data,'' says Haff. ''If anything, it's a business process problem. It's typically going to be more an issue of what data is being collected and how it's being collected, as opposed to it being incorrectly processed once it's in the system.''
The only way to deal with that, according to Haff, is for IT and the business suits to work on it together.