How important is analytics in decision-making?

A new IBM study was released today about how successful companies utilize analytics.  They conclude that, “many enterprises are operating with blind spots and without management systems for effectively putting information into action.”  Read the full reports here.  In short, great companies make great decisions through the support of great analytics.

Among the most interesting differentiators between top performers and bottom performers:

• 15:1 | Top-performing companies were 15 times more likely to apply analytics to strategic decisions than their underperforming peers.
• 6:1 | Top performers were six times more likely to entrust a broader base of employees with greater authority to make decisions and act on insights
• 3:1 | By a factor of three to one, the study found that top performers were much more sophisticated in their approach to governing organizational information relative to lower performing companies
• One of the key attributes of top performing companies is the ability to empower its employees, giving them authority to use information, make decisions, and act upon their insights.

Of course, most manufacturing executives probably knew that this would be the case intuitively.  The more interesting question is this: what’s stopping us from implementing this type of open, data-driven culture?  Typically, the barriers are two-fold: structure and culture.

Changing the Culture

Culture has to do with the incentives, the unwritten rules, and the behavior of the organization.  When friends ask your employees, “how would you describe the culture of your organization?”, how do you think they’d respond?  While some would argue that there are as many cultures in an organization as there are bosses, I’d be willing to bet that you would see some common themes across the board.  I will leave culture change to change management experts at Harvard, which you can read here.  In summary, it usually starts from the top.

Changing the Structure

On the other hand, structure has to do with processes/systems;  in some sense, this is the easier aspect to address.  Are your people set up with the tools they need to access the data?   Is there a clearly defined process for obtaining key metrics and for identifying/solving problems that arise?

Far too often in our experience, we’ve seen boatloads of the brightest problem solvers, engineers, and scientists begging for an opportunity to attack a difficult problem, but they lack access to crucial data.  Usually, the data sits on some hard-to-maintain, harder-to-use system that only 1 (unlucky) guy knows how to use.  (side note: this is why we created ZOOMS for those of you who wish you could access PI data).  This is not just a painful bottleneck in the analytics process, but also a job dissatisfier for the best people in your organization.  This is a structural barrier that also turns into a cultural one.

Take the time in 2010 to survey your best problem-solvers.  What’s the one tool they wish they had to do their jobs better?   What’s the one aspect of your company culture that they wish could be changed?  Yes, these are dangerous questions.  But the data is in: great companies empower their people with great data.