Pareto triage

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Pareto triage
pəˈreɪtˈəʊ ˈtraɪɪʤ (n.)

A JC coinage to capture management’s slavish devotion to the Pareto rule.

To exercise “Pareto triage” is to move beyond the observation that eighty percent of your revenues tend to come from twenty percent of your clients, and vice versa — which is just one of those unfortunate and immutably brute facts of life, like “Australians are good at cricket” — and to use it as a plan of business action to try to change the immutable facts of the universe.

The logic — if one could call it that — is this: four fifths of our clients provide just one fifth of our revenue. That great remainder — eighty percent of them! — is really not worth the bother. Rather than wasting precious internal resources on the low-yielding mass, we would be better served just foregoing that twenty percent of revenue or, at any rate, pay not the blindest bit of attention to maintaining it — and instead concentrate on that lovely twenty percent segment who bring all the rest of our income.

Here is a variation on the same argument, rendered in more plainly averagarianist terms:

“Half our clients generate more revenue than the other half. We should therefore ditch the lower-revenue generating half.”

Unless your client base is entirely homogeneous — that is, identical, and while the gormless denizens of data modernity urges us on, we’re not there yet — it is statistically certain that one half of your clients buy more of your goods and services than than the other. This is no wondrous insight into the citadels of homo sapiens, but a simple property of a group of different numbers. You can arrange any group of random number into groups such that one will have a greater average than another. This unremarkable fact happens to be true of client revenues, too. It would be extraordinary if it were not true, every year, every month and every day of “the client base” in general but not of any clients specifically.

The average of a group is an emergent property of all members of the group. The property for bit being to any given member. This is the logical error of jobsworthism. It is to mistake a mathematical property of variable set of data for a hard, determinate, property of artefacts in the real world.

Pareto triage doesn’t look like averagarianism, but it is. It is arbitrarily to divide a group into uneven portions by reference to the average emerging from each portion. The average drives selection for the group, not vice versa. The tail wags the dog.

That a group can be sorted according to the Pareto rule is a property of the variance of that group. Variance is another emergent property. It has no meaning at an individual level. It changes depending on who else is in the group.

The “eighty” and the “twenty” segments of your client base are no more homogeneous then the whole. The Pareto rule will apply equally to each of them.

That Pareto principle is, therefore fractal. It scales down and up. If you cut off the “bad bit”, you will see, to your horror, your new, concentrated, high-value, but radically down-sized “good bit” still requires Pareto triage: there are still twenty percent of its population generating eighty percent of the revenue. The revenue pot is just smaller, that’s all.

This is Xeno’s paradox for our age: If we chase a Pareto triage we will end up with 20 percent of nothing.

Time

Nor does Pareto triage tell you anything about the forward value of your client base. Whatever period it covers, your data is a historical, averaged, snapshot: it will tell you nothing about the development of client data over the sample period. We are prone to averagarianism here, too. A client whose revenue has increased exponentially over a decade will, thanks the the Bill Gates on a bus effect, that revenue averaged over the decade will seem tepid. A client whose revenue has recently fallen off a cliff will look heroic.

And even if you can see that historical trend, of itself it doesn’t tell you anything. Remember the compliance refrain: past performance is not a reliable guide to future return .

There are any number of reasons a client’s revenue profile might change. They may be internal to the client, a function of market, a reflection of your product, or a result of poor sales coverage. It may be harder work than crunching a spreadsheet, but looking into why a specific client is not buying much product it will give much better basis to make the decision to terminate it.

See also

• System redundancy
• Data modernism
• Jobsworthism
• Averagarianism
• Pareto rule