The blind watchmaker and why sales tasks should not be automated

The Blind Watchmaker

Richard Dawkins revised William Paley’s idea of a watchmaker as evidence of a divine creator in The Blind Watchmaker.

I’ve always found that idea particularly evocative and, strangely enough, applicable to sales.

Dawkins explained that given a remarkably simple set of rules (and enough time) incredible complexity could (and does) emerge without the input of a creator.

But, enough on evolutionary biology!

A common problem I’ve encountered in sales environments is the desire of management (and software companies) to enforce a fixed workflow on sales. (Or, on Opportunity Prosecution, to be more precise.)

I can understand that this may appear to make sense because the imposition of a deterministic workflow has paid dividends in production environments.

But, of course, sales is not a deterministic environment. The prosecution of a sales opportunity is a decidedly stochastic process.

This means that management should NOT attempt to impose a fixed sequence of tasks upon salespeople. An attempt to do so will decrease salespeople’s productivity and damage the integrity of information ultimately extracted from CRM.

In this context, a production environment is not a good analog for a sales environment. (Which is certainly not the case in many other contexts!)

A more appropriate analog is required, which returns us to our Blind Watchmaker, and a thought experiment.

Imagine, if you will, a blind watchmaker, charged with the responsibility for assembling a watch from a pile of parts, and motivated to complete this task in the shortest span of time possible.

We should assume that this watchmaker understands the basic structure of a watch but does not possess an intimate knowledge of every part in the pile in front of him (there are a lot of parts after all).

What we’ll, no doubt, observe as our watchmaker goes to work is a process that looks like the assembly of a small but incredibly complex three-dimensional crossword puzzle.

He will grasp a couple of parts at a time and attempt to fit them together. The process will be entirely random to begin with, but as time progresses, we will probably see him sort parts into categories to impose some crude order onto his work.

If he works like this long enough, he will eventually have a breakthrough. This is when he manages to assemble a set of parts into a sub-assembly. Not the finished watch but an internally-consistent component of the finished watch.

This is a breakthrough because the parts that make up this sub-assembly have now been removed from the parts pile, meaning that there’s been a step-change (for the better) in the complexity of his mission.

Though we may wish it weren’t so, this is very much what sales is like.

The salesperson has a bunch of tasks (parts) at their disposal. Their job is to perform these tasks repetitively, influenced to a great degree by trial and error until they achieve a breakthrough.

In a sales environment, a Stage is an analog to a sub-assembly. A stage is a step-change in the likelihood of a win that occurs when a prospective customer makes a commitment to a particularly meaningful task. (For example, in a major-sales environment, a prospect might agree to purchase a Solution Design Workshop).

Now salespeople are not literally blind, but they do have a limited view of their workspace. The nature of sales is that buyers will always disclose information to sellers selectively.

The lesson here for management (and technology companies) is that we should not attempt to plan sales at a level of granularity below Stages (understanding that stages are tied to particularly meaningful tasks).

We should not push tasks to salespeople. We should equip salespeople with a sensibly-sized basket of opportunities and a pile of parts (task types) and let them use their ingenuity to progress those opportunities, as best they can, from one Stage to the next.

Software can help, obviously. But the developers and implementers of software must understand the dynamics of the environments they are automating.

Automating a deterministic workflow makes total sense. Attempting to impose a deterministic workflow on a stochastic environment definitely does not!

* * * *

Now, you may have sensed a flaw in this reasoning. Couldn’t a robot equipped with some natural-learning algorithm outperform our blind watchmaker, and, by extension, our salesperson?

Well, it’s here that our analogy breaks down. You see, our blind watchmaker gets to play with his pile of parts until all have been assembled successfully into a working watch.

However, opportunities from our salesperson’s basket disappear suddenly after an indeterminate number of tasks have been performed against them. So, no, this is not a process that that’s quite so easy to brute-force with a clever algorithm!

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