I have some favorite phrases that I’ve been picking up for years.
- “Eh, voila!” universal for “eh, voila!”
- “Ah, asodeska” Japanese for “I understand” (sp?)
- “Bo ko dien” is Taiwanese for highly unlikely or that’s ridiculous. (sp?)
- “Oh shiitake” (shitzu is also appropriate), is an imperfectly polite way of saying “oh &#!+”
Basically, these are phrases that i love, but at least the latter two are meaningless to most people i say them to. I could of course go to Japan and most people will know what I’m talking about when i tell them I understand them, but they will then look at me funny when i exclaim in the name of a mushroom in anger.
We face the same problems when we talk about data calculations in HR. The most common of which is the simple headcount calculation. “Simple?” you ask. I mean, how hard can it be to count a bunch of head that are working in the organization on any particular day, right? The smart data guys out there are scoffing at me at this very moment.
First, we put on the finance hat. Exactly how many heads is a part time person? HR exclaims that is why we have headcount versus FTE. But finance does not really care, and they are going to run a headcount using a fraction either way.
Second, we put on our function and division hat. Every division seems to want to run the calc in a different way. And then there are realistic considerations to be made, such as the one country out there that outsources payroll, and does not have a field to differentiate a PT versus FT person. or the country that has a mess of contractors on payroll, and can’t sort them out.
Then you put on the analytics hat, and realize that when you integrated everything into your hypothetical data warehouse, the definitions for other fields have not been standardized around the organization, and you can’t get good head counts of specific populations like managers, executives, and diversity. I mean, is a someone in management a director and above? Or is she jut a people manager? How many people does she have to manage to be in management? Are we diverse as an organization simply because we have a headcount that says we are more than 50% people of color even though 2000 of those people are in Japan where the population is so homogenous that any talk of non Japanese minorities is simply silly?
Then you put on your math hat and some statistician in the organization tells you that you can’t average an average, or some nonsense like that.
So the Board of Directors comes to HR and asks what the headcount of the organization is. You tell them that you have 100,000 employees, plus or minus 10%. Yep, that’s going to go over really well.
I’m not saying its an easy discussion, but all it really takes is getting everyone into the same room one (OK, maybe over the course of a couple of weeks) to get this figured out. I’ve rarely seen an organization that is so vested in their own headcount method that they can’t see the benefits of a standardized calculation. I fact, most of the segments within are usually clamoring for this and we just have not gotten around to it yet, or we think they are resistant. In the end, it’s really not so hard, and we should just get to it.
Asodeska?
5 responses to “Commonizing Meaning”
An advantage of modern reporting systems is that you don’t need to only have one way of reporting people employed. We’ve built clients dashboards where they can switch definitions literally at the touch of an on-screen button whether to report FTEs or Headcount and then all (relevant) displays will this definition. As long as the data is consistent in the background (and has sufficient detail) then how it is presented shouldn’t matter.
What does matter is that we know which form is being presented. Reporting needs to fit (and inform) individuals’ mental models, it doesn’t need to present the underlying data structure.
An advantage of modern reporting systems is that you don’t need to only have one way of reporting people employed. We’ve built clients dashboards where they can switch definitions literally at the touch of an on-screen button whether to report FTEs or Headcount and then all (relevant) displays will this definition. As long as the data is consistent in the background (and has sufficient detail) then how it is presented shouldn’t matter.
What does matter is that we know which form is being presented. Reporting needs to fit (and inform) individuals’ mental models, it doesn’t need to present the underlying data structure.
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Andrew – you are totally right on this one. The conversation about headcount numbers should be “what is the headcount based on XYZ parameters?” Unfortunately most conversations seem to be, “why am I getting 3 different headcount numbers?” and nobody can tell the exec the actual reasons behind the discrepancy.
I will also say, based on our semi-frequent web conversations, that I would bet anything that your analytic practice is 10 times more developed than the average in the marketplace.
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