Before you jump down my throat, pointing out my words elsewhere that praise thorough data collection and analysis, let me ‘splain.
No, there is too much. Let me sum up.
When I taught physics labs, the first class of the year was an introduction to data collection and analysis. The lab manual provided a rather intricate experiment that required a variety of data analyses to be performed — with several of those analyses appearing perhaps once more over the course of the semester.
Not only was arriving at the data set a contrived process, the various data descriptors tended to overlap. Some were outright useless in standard settings.
What did I do? I completely reworked the experiment. I threw out the analysis techniques that appeared only in that experiment. I taught the calculations and methods that needed to be taught (since they were going to be used most weeks), and gave an experiment that made use of them without confusing my first-week students.
It worked very well, if I say so myself, and it was much more engaging for the students than the lab manual’s experiment.
The point of the story?
I’ll be the first to say that data collection and analysis are essential for the success of any employee-focused program. Whether it’s how many employees participate in the monthly lunch-and-learn, the progress of employees’ waistlines, or the total sick days taken by your office over the course of the year, having a strong knowledge of employee trends is a good thing.
However, even if you have all the data in the world, trying to measure everything is an exercise in utter futility.
Some wellness vendors and wellness programs like data a little too much for it to be optimally useful. I understand wanting to keep tabs on employee health metrics. Really, I do. But keeping a record of blood pressure, total weight, BMI, total cholesterol, resting heart rate, 2-hour fasting glucose, HRA responses, and/or anything else — and then performing analyses on each metric over the entire organization — is just too much.
The same goes for the various technological gadgets many companies use. Remember Aetna’s data tracking app? Yeah, it can keep track of prescriptions, cholesterol readings, blood pressure readings, the distance you ran this morning, how much time you spent on the elliptical yesterday… you get the idea. But ultimately, what’s the use of all of that data?
In my opinion, not much. Quality trumps quantity. Waist circumference correlates excellently with indicators of heart disease, obesity, diabetes, blood pressure, and more. The best part? It takes about ten seconds to measure. Boom. Done. (Of course, you can also go for a full lipid profile – HDL, triglycerides, LDL-C, LDL-P, etc. – if you want a better idea of your heart health.)
Similarly, activities in the workplace can be measured easily: how many people show up? If it’s below a certain percentage, do something different. If the same people show up time after time, go to the ones that stay away and see what they might like. Send a survey around if you want.
Tracking employee health and well-being shouldn’t devolve into interminable number crunching. Don’t let it happen to you. A lot of this stuff can be done in-house, without vendors, without expensive web platforms and portals, and without a team of coaches and consultants.
Don’t be seduced by a full suite of analytics, where everything from lunch-and-learn participation to resting heart rate to pedometer steps are analyzed. At the same time, don’t settle for bare-bones analytics, where you only look at one or two pieces of the puzzle. Find a sweet spot in the middle that fits your organization.
What do you think? How often does analysis cause companies to lose the forest for the trees?