Goals are not rocket science, right? Just make sure they are SMART, confirm the specific objective value, and get yourself busy, striving to get there before the deadline is due, correct?

In fact, many do just that. I find it an equivalent of brute force approach - no brains, just sheer power (and endurance, and grit, and luck). Effect to effort ratio? Questionable, but suboptimal for sure.

My advice is to apply Systems' Theory (ST) to understand how the (measurable) goals work. Sorry, I'm not going to cover the basics of ST in this post - you either have to reach out to my archives (e.g., here) or external resources (like that one). To be frank, I won't even try proposing a complete system for goals and their dynamics (aka flows). My ambition for this post is only to emphasize a few fundamentally different "natures" of goals, just to prove that having a single approach to meeting all the possible objectives is a naivety mixed with a lack of imagination.

Let's start with something obvious. The necessary condition for the goal to make sense (in the context of your person/team/unit) is that you have an actual IMPACT on that goal.

But, not every impact is alike. In some cases, you have a potential positive impact (you can boost the positive growth of the measurable metric behind the goal). In other cases, you can only reduce the negative impact (by pr0-actively preventing something from happening).

Let's consider the goal of having X windows cleaned.

Being a cleaner is an excellent example of the 1st case mentioned above. The more time and effort you spend cleaning, the more windows are clean. When it comes to the 2nd case, imagine someone whose job is to provide you the cleaning agents - they can't make you clean more than your max cleaning capacity, but they can impair your work with a shortage of supply (you'd like to clean, but you lack detergent).

That was the type of effect one's activities can have. But what about how the effect could be applied (scales) towards the goal? There are three basic models: constant, linear, accelerating:

  • in the constant model, nearly any effort provides the same, static effect; think about having a bucket (to keep cleaning water) - there's no cleaning w/o it, but having ten buckets won't help you in any way, you still have only 2 hands
  • in the linear model, your activity translates into some direct effect - that is a bread and butter of window cleaning, isn't it?
  • in the accelerating model, your activity has a direct effect on a trend of the measured metric (it's an equivalent of contributing to the flywheel effect); e.g., you improve the detergent formula, so from now on cleaning a window requires less rubbing and takes less time

That model is still too simple. Let's add a few more elements:

  1. Not all activities aimed to help you meet the goal bring an immediate effect - typically, the accelerating models bring substantial value over a more extended period.
  2. Some goals (at least partially) "achieve themselves" (will be met even w/o your input) - due to the environment's impact (other people's work or some earlier effort). Examples? A good product's sale metrics benefit from so-called word-of-mouth marketing.
  3. Metrics can have "glass-ceiling"-style boundaries (constraints of the market, economy, target segment, etc.) - there's a certain number of windows in the area you can clean ;P
  4. Certain activities fall under the law of diminishing returns - the more you try them, the less effective they are; E.g., training the employee in new window cleaning techniques can be initially very effective, but only once or twice ...

OK, enough.

My point is that to approach the goal correctly, you need to have a perfect understanding of the nature of your potential impact on the metric(s) measured (that represent the goal). I mean the entire qualification and quantification using the criteria from the list described above.

Why is it so crucial? Because context is (as always) the king. We tend to oversimplify our thinking by favoring the most straightforward approach:

  • looking for potential positive impact
  • in a linear model
  • with a near-instantaneous effect
  • w/o considering eventual boundaries/constraints

It's only because it's the most intuitive one, but also because it's so visible. Even if you fail, no one will say you haven't tried. You've put in a real effort. Apparently stupidly, but you tried hard. Sounds like a perfect alibi, right?

It's even more ridiculous when your job/role specifics favor a diametrically different approach. In such cases, we still tend to invent strategies that do not make any practical sense but fit perfectly the straightforward model described above. Instead of providing effectively MUCH MORE value by adopting the strategy that matches our role/specialty/skills/position, etc.

That's neither intelligent nor motivating (especially long-term).

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