8 keys to a successful BI strategy
Brian Jackson, CIO of Texas Tech Credit Union, wants to boost the amount of data being used by employees to make decisions.
As such, Jackson continues to fine-tune the organization’s business intelligence (BI) strategy, which launched in 2014 with its initial implementation of BI tools.
Over the interceding eight years, Jackson has worked with his peer executives to mature the program. They’ve upgraded to a new BI platform from software maker Domo, trained more workers on the tool, and developed a plan for advancing the use of data and intelligence even further.
Such moves, he says, have helped the credit union leverage data more often and more effectively throughout the organization, noting that a “game-changer for us” has been getting workers to query the data by phrasing requests as actual business-oriented questions.
Jackson is hardly alone in his attention to data, as organizations of all kinds prioritize data projects. Yet even as companies look to advanced data-fueled technologies such as automation and artificial intelligence, organizations still find significant value in well-run BI programs.
A recent survey of more than 700 business leaders conducted by analytics tech company Unsupervised found that 71% of businesses have implemented a BI strategy, with the desire to forecast business, improve customer experience, gain a competitive advantage, speed up data analysis, and make more data-driven decisions being the top reasons for a BI program.
And their BI investments are paying off, according to the survey data. It showed that 94% saw their company’s revenue increase post-implementation.
Survey respondents listed increased revenue, increased sales volume, improved customer service, increased productivity, and more new customers as the top five benefits they derived from their BI use. Better supply chain management, increased employee satisfaction, and increased customer retention were the next three benefits cited.
Yet business leaders also acknowledged challenges to their BI programs. According to the survey, top 10 roadblocks to BI success include software-related issues, lack of adequate budget, lack of training and expertise, lack of strategy, unclear strategy goals, and lack of companywide adoption.
Those findings show, and Jackson’s comments illustrate, that a successful BI program is about more than just technology. Here are 12 essential elements that can help overcome those challenges to create a successful BI strategy.
Ashley Fitzgerald, senior director for data science and analytics at Appnovation, a digital consultancy, once worked with a client who had purchased a multimillion-dollar BI package that couldn’t connect to the company databases, even via APIs.
Rather, the company had to build integration tools to enable the flow of data. Essentially, Fitzgerald says, “We had to build a tool on top of the tool they bought.”
That extra technology added unnecessary cost and complexity to the product, which could have been avoided by being more attentive to the existing infrastructure, the BI software available, the limitations of each and how those would impact deployment, she adds.
Jackson agrees, saying that the credit union once had a BI application that was difficult to scale and required hard-to-find specialized tech skills. So when the organization sought out a new solution, “finding the best solution we could leverage with the existing infrastructure we had in place was top of mind for us.”
IT infrastructure requirements should not be the only requirement influencing BI tool selection, says Sri Manchala, CEO of Trianz, an IT service management company. The CIO and the IT procurement staff should solicit the workers who will be using the software to understand what kind of questions they’re seeking to answer and how they want to receive answers to those questions.
