Costco Toilet Paper is Soft on the Math

Bathroom. By Dean Hochman.
Bathroom. Photo courtesy of Dean Hochman.

Denominators make everything feel better, including toilet paper.  A really good denominator can help you figure out that you should not buy the bulk package of toilet paper from Costco.  That’s because the real estate you are storing it on is way too expensive.

To understand this, consider your cost of housing.  If you haven’t done so already, you should probably figure out how much you’re paying every month for each square foot of living space in your home.  For example, if your living expenses are $3,000 per month on 1,500 square feet, you’re spending $2 per month for each square foot.

The bulk package of toilet paper occupies four square feet of floor area, which represents $8 per month of storage costs.  The package costs $20 for 30 rolls that will last a family of four about two months.  That’s $10 per month for toilet paper, which seems like a bargain compared to about $15 per month you would pay for the package at a regular grocery store.  But your $5 of savings is sitting on top of $8 worth of real estate.  The unit-cost savings is less than the cost of real estate that it’s occupying.  The Costco toilet paper is just too expensive to forgive real estate cost that it’s imposing on you.

So, how does this relate to workforce analytics?

Appropriate Denominators in Workforce Analytics

Throughout the analysis of the value of your workforce, it is common to talk in numerators.  Number of people.  Salaries.  Benefits costs.  But what is usually more meaningful is to match up the numerators with appropriate denominators.  Number of people this year divided by number of people ten years ago (it’s usually not what you think).  Salaries per month during unfilled vacancies (actually a lot of money).  Executive compensation divided by organizational revenues (a drop in the bucket).  Numerators become more meaningful when you divide them by the right denominator.  And you must experiment and choose wisely.

With truly strategic business analytics, the biggest opportunity for novel insights is the blending of numbers from different strategic pillars.  You could have a finance metric divided by a human resources metric, such as capital invested per employee.  You could take a sales and marketing metric and divide it by people, such as revenues per salesperson.  Ratios from within a VP portfolio are often really easy to pull together because you can usually get them from a single database.  Once you have those easier in-house numbers figured out, it’s vital to get into the difficult metrics.

With the toilet paper example, it is the price of consumer goods are familiar to us as shoppers.  Then unit price is the next level of complexity, looking at price-per-roll.  You need to then seek information that is outside of the shop where the question was first posed, and in this example it’s housing cost.

The Story Changes When Better Denominators Are Chosen

One of my favorite experiences was a health & safety statistic about back injuries from over-exertion.  We knew that a large number of men over age 55 were pulling their backs from over-exertion.  But we discovered that there was a larger denominator of men over age 55, and that their percentage frequency of injury was lower than expected.  By contrast, those entering middle-age at age 45-54 had the highest frequency of these types of injuries.

When I was helping the client figure this out, I had personally pulled my own back at the gym at the age of 46.  I was in defiance about the fact that I was getting older, and trying to prove myself by lifting something that I should not.  I proposed to the client that those age 55+ are too wise for such foolishness, and those under age 45 can handle the challenge because they’re younger, fitter, happier.  I proposed a new interpretation; over-exertions are not about stand-alone physical vulnerability, they are about the disconnect between actual ability and self image, particularly in the social context.  The client liked it.

In order to rock it, each database had to be high quality, allow apples-to-apples comparisons, and have enough fields to break out the data by ten-year age cohorts.  These are critical intermediate steps, and not every organization is there yet.  What is important to notice is that as you improve your numbers, opportunities abound.  You can get stronger each time.  Nothing is so trivial that you can’t make it better with analytics.  And yes, you can afford the good stuff.  If you earn it.

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