I have an amazing coffee maker. The Capresso C1000 was one of the original kitchen robots; it makes coffee from beans and water. The output is a creamy concoction that rivals the best espresso you can find in the nichey-est local coffee shop in San Francisco.
What seemed like an outrageous investment ($900 at the peak of the dot com thing) turned out to be very reasonable when spread over a dozen years. At about $.10/day, the thing brews pleasure every morning. It makes pressure brewed coffee rather than the drip coffee that is the American Standard.
The company behind the machine is the real story. Every four or five years, after I have completely failed to do the proper maintenance, my coffee maker goes on strike. It just refuses to work. I box it up, send it back to kitchen robot heaven and wait about three weeks. (They are long weeks without my morning nectar). Like magic, it turns back up on my doorstep, fresh and ready to go. Great product, great service, great experience.
I have one complaint about the coffee maker.
I’m usually pretty good about doing the maintenance required to keep things running. Oil changes, routine cleaning, laundry and the dishes are things I enjoy. You figure out what’s required; take care of business; and the world operates smoothly.
With the C1000, the front panel is a maze of buttons and lights with ‘intuitive’ labels. Making coffee in the morning means pushing the buttons and making the lights change. It’s reasonably simple to learn.
But, when maintenance is required, all of the lights go off in a visual cacophony. The manual, 20 dense single spaced pages, will tell you want to do if you can wade through the technical material. Since it doesn’t happen very often, each event requires relearning the maintenance manual.
What I really want is one button marked ‘fix everything now’. In lieu of than, I’d like the machine to help me while I fix it.
This is also the problem that plagues most approaches to ‘workforce analytics’. Like my Capresso C1000, analytics generally give you a status report without any guidance for problem solving. While knowing that you have a problem is the first step towards dealing with it, any mediocre consultant can help you notice that things are hinky.
With all of the fuss about the integration of analytics into enterprise HR Systems, it’s pretty hard to tell the difference between what we used to call ‘reports’ and what we now call ‘workforce analytics’. While the reporting is increasingly precise (that means knowing exactly whose butt will be kicked at the next staff meeting and for what reasons), access to the information required to start solving the problem remains a challenge.
It’s as if, while you were listening to the stereo, you needed to get a report about it’s loudness and then go over to the unit to figure out how to turn it down.
Yesterday, I saw a demo from Stepstone Solutions, the global provider of Talent Management Software. As we were digging under the hood, it became clear that Stepstone approaches this question differently. They’ve figured out how to keep the analytics tied to the underlying data in a way that makes problem solving easier.
When you are unhappy with the way the system is operating, you click through the dashboard to the underlying data and start solving problems.
In many organizations, the analytics department is completely detached from the operational HR team. Data analysis is seen as separate from actually doing stuff. Like Quality Control in the days before it was integrated into operations, analytics often act like an audit function.
The Stepstone approach assumes that the user is in the business of continually improving her performance. By making their analytics a gateway to actionable data, they are changing the way that HR learns.
And, I’m going to send them over to Capresso to work on the next generation coffee maker.