Are You a Business Intelligence Avoider?

From six different studies we can conclude that approximately only 5% of employees use BI tools to perform Analytics effectively.

I think this is in part related to the fact that except for folks with backgrounds in science, engineering, economics or finance; many people across the company do not feel too comfortable around numbers, math or logic functions.  I've observed this during years of training corporate employees on the strategic use of Business Intelligence and Analytics.

This is how the numbers work: close to 50% of employees have access to BI tools, about 20% of them actually use BI, and about half of them (5%) are in the analytical / power user categories.

Despite recent inroads of the more user friendly BI visualization tools of the last few years, the BI Scorecard’s annual survey of users, administrators, and directors reports flat utilization rate since 2006.

If you were to plot a histogram showing only those 20% actual BI users in an organization, it would probably approach a normal distribution (bell shape curve) consisting of the following categories, where close to two thirds of the users would fall in buckets 3 and 4.

1) Non Users: Run canned reports once a quarter or less frequently. These are people who are either math averse; do not like computers, or are executives that have their assistants run and print static reports for them.

2) Infrequent Report Users: Run canned reports about once a month.

3) Frequent Report Users: Run canned reports on a weekly or daily basis.

4) Analytic Users: Modify static reports and OLAP cube views by grouping, sorting, formatting as well as changing some dimensions and measures. These folks save their new customized reports for future use.

5) Power BI Users: Create new ad-hoc reports from scratch applying multiple dimensions, measures and using grouping, sorting and filters. These users travel interactive dashboards and OLAP cubes from corner to corner using drill down, drill through, and most of the available custom features in search of the root causes of both: problems and opportunities.  Power users create and share reports, dashboards and visualizations with folks in the same department.

6) Expert Analysts: Search find and provide new data bases, blend disparate data, design and build customized cubes, pivot tables and dashboards, perform statistical, financial or marketing analyses and usually export results to MS Excel to complete the last analytical mile.  Expert analysts create and share reports, dashboards, visualizations and analyses with management across the organization.

Buckets 4, 5 and 6 represent the 5% of employees that use BI tools to perform analytics effectively.   When it comes to Advanced Analytics (statistics, predictive modeling, data mining, etc.), data scientists or statisticians are probably close to 10% of that number or just about 0.5%.

To become a true analytic competitor, the company has to change the culture so everybody, not just the experts, thinks and acts based on facts and understands the drivers that support strategy and sustainable profitability. 

While this isn't easy, it’s possible.  I've seen it quite a few times.  It requires long term commitment from top management, adequate training, data structured to be business-intuitive and an interactive visual analytic software tool configured in an extremely user-friendly manner so all types of users can perform analytics with virtually no help from IT, analysts or even spreadsheets. 

In my experience, the organization improves its financial results through this implementation as people gradually advance to the next level, leaving buckets 1, 2 and 3 practically empty. 

Which buckets is your organization using most?