Organizations looking to get on board with the big data movement are hiring the best and brightest to analyze and influence business decisions. Data scientists, architects and business intelligence professionals can get expensive. After hiring the best people and selecting state-of-the-art tools, the failure rate, according to Gartner, is more than 70 percent. For mathematicians reading this, that leaves a mere 30 percent success rate for analytics programs. What gives? You just hired the best talent outside of the organization to change the way you operate, so why can’t they do it?
You brought in a group of outsiders to crunch numbers and show other professionals in your organization how to do their job better through analytics. See the problem? You alienated the very professionals that you brought in to change the organization. These intelligent individuals will soon know how it feels to change the direction of a speeding locomotive – they can’t.
Given the constraints listed above, how do you create success in an analytics program? The solution might sound simple: gain inertia through enabling the experienced professionals by enabling them with analytics tools and knowledge making them more secure in their jobs.
Do not tell the workforce what to do and how to do it. Enable each and every department to make their own analysis, come to their own conclusions and make their own decisions. Empower them!
This solution may not work if some common barriers are not removed.
By removing barriers and enabling a workforce, analysts within the organization will earn a spot as trusted advisors that are enabling success – rather than individuals pointing out how others should best do their jobs. Organizations that do not focus on removing barriers and enabling their staff will be just another statistic in failed analytics projects.