According to Gartner, BI (business intelligence) and analytics will remain a top focus for CIOs through 2017, with companies spending millions on traditional BI software, cloud BI services, and now mobile apps and even social BI. However, as the type and number of BI solutions has grown, so too has the possibility of failure, of picking the wrong business intelligence software for your business problem or problems or of having end users not understand or properly use the solution.
To help you avoid a potential costly mistake, and get the most out of your BI software investment, CIO.com has put together a list of nine most common mistakes organizations make in regard to selecting and implementing a business intelligence software solution -- and how you can avoid these mistakes.
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Mistake 1: Not defining the business problem(s) you are trying to solve. "Companies [should] not rush into leveraging any BI tools unless they have a distinct business case," says Scott Schlesinger, senior vice president and head of Business Information Management, North America, Capgemini, a provider of consulting, technology, and outsourcing.
"One of the biggest [mistakes in] pursuing an analytics initiative is jumping in too soon without clearly defining what it is the company wants to accomplish," Schlesinger says. "Companies will not be able to generate any real ROI if they don't outline the business case first and determine why and where leveraging big data makes the most sense in their operations."
"One of the biggest mistakes is buying for 'general capability' vs. solving a defined problem," says Charles Caldwell, director of Solutions Engineering and principal solutions architect at Logi Analytics, a business intelligence company.
"Too many folks look for the one silver bullet tool that will solve all analytics problems they'll ever have without fully defining the immediate problem to solve. And that is why so many BI projects fail," Caldwell says. Instead, "start with the business problem to be solved, understand the specific capabilities required to solve those problems, and then purchase the BI tool(s) that meet those specific needs."
Mistake 2: Not getting buy-in from end users (before you choose your BI solution) "IT has a tendency to purchase BI tools in a vacuum without first getting buy-in from the people ultimately expected to use them," says Joanna Schloss, business intelligence and analytics evangelist, Dell Software. But "assuming employees will use newly purchased BI technologies simply because the organization is standardizing on them is a mistake," she continues.
"Even the best BI tools are ineffective if they're not utilized, and no amount of training or standardizing will convince people to use technology they don't feel benefits them personally," she explains. The solution: "Instead of telling employees they have to use something, help them clearly understand why they'll want to use it. Clearly articulate the value proposition and adoption will follow."