As your organizations catches analytics fever—and as vendors hype analytics seemingly without constraint—it’s good to remember that information is not inherently valuable. In fact, without the requisite thoughtfulness and wisdom, analytics can actually drive people to do exactly what they shouldn’t do.
Here are four analytics-related errors that have become especially common and pernicious:
Some data merely appears useful—but isn’t. A classic example is call center talk-time. Call switching systems capture lots of data about caller and agent behaviors. Unfortunately, this has led some call center managers to obsess about talk-times as an indicator of staff productivity.
This can be a fatal metric. When you incentivize operators to wrap up calls quickly, you also incentivize them to deliver bad Customer experiences by ending calls prematurely. The result: Customers leave you for your more helpful competitors, and your productivity goes down as operators take second and third calls about issues that should have been resolved the first time.
Similar mistakes are now being made in DevOps environments, where managers are obsessing over metrics such as re-work. But re-work can be good if it’s driven by Customer feedback—and if it happens sooner, rather than later.
Takeaway: Make sure your analytics are truly designed to drive the right business behaviors.
IT analytics teams often make the mistake of assuming that analytics themselves will inherently make the correct course of action apparent—especially if the data nicely visualized.
But consider this classic thought experiment. A fleet operator has an equal number of vehicles that get 10 MPG and 20 MPG, respectively. All vehicles travel the same 10,000-mile distance annually. The fleet manager has enough budget to either convert the 10 MPG vehicles into 20 MPG vehicles—or, for the same money, convert the 20 MPG vehicles into 50 MPG vehicles.
Which is the smarter move?
Looking at the typical bar-chart visualization, the 30 MPG savings will look more much impressive. However, the 10-to-20 MPG conversion saves 500 gallons per vehicles—while the 20-to-50 MPG conversion only saves 300.
Do the math if you’re still scratching your head over this one. But the point is this: Accurate analytics and intuitive visualization are often insufficient to drive the right action. Clear analytics can even lead decision-makers down the wrong path.
