We should come up with a unit for cognitive effort. Like in information science you have a “bit” (binary digit that stores information). That concept was made famous by Claude Shannon who is considered as “the father of information theory”.
Here, I’m arguing a metric like “bit” should be developed for measuring cognitive effort of work tasks and individuals. Let’s call this hypothetical metric a “surge”.
So, a simple task would maybe take “5 surges” whereas a medium complex task would take “50 surges” and highly complex task could take “500 surges”. The relationship between different tasks and scale of surges is an empirical question, but I’m thinking the relationship might not be linear but geometric (because cognitive effort required by more complex tasks grows exponentially).
And a person, every one of us, has a certain inventory of surges per day. Like, let’s say Individual A has 10,000 surges because he ranks high on cognitive capacity. Another one, Individual B has only 5,000 surges, relating from poorer cognitive capacity. It’s important to acknowledge that while people differ biologically in terms of their cognitive skills, Individual A doesn’t necessarily perform better than Individual B. In contrary, Individual B can learn to better manage his surges, allocating them in the most optimal way to achieve his or her personal goals.
So, being aware of your “surge inventory” matters, as you can just as easily deplete your surges doing less meaningful tasks (from point of view of your professional or personal goals) or using them in a focused manner to spend less cognitive effort while still achieving the results. Thus, using mental energy becomes a “strategic game”. I believe many successful people already apply this method of sparingly allocating their cognitive effort, without necessarily being aware of it or being able to exactly quantify the process.
Quantifying cognitive effort is important because
- user tasks vary by how much cognitive effort (how many surges) they take on average
- individuals vary by how much it takes from them to complete the same task
- individuals vary by how many surges they have in their “inventory” per day (variation in biological and learned cognitive capacity)
A, b, can c have profound implications both for organizations that want to get things done more efficiently and for individuals that want to develop their skills in more efficiently handling work tasks.
Quantifying cognitive effort as “surges” and then measuring different tasks and individuals would help planning how to allocate resources for both organizations and individuals.
For example, if an organization wants to achieve a Goal X that comprises Tasks 1…n, and we know how many surges each task takes on average and how many surges our people have per day, we can calculate how many days it takes. This could be useful for startups, new product development organizations, or virtually anything. In my experience, currently the work efforts are specified in haphazard ways with very little systematic methodology. This can be one root cause as to why many development projects end up failing.
For individuals, quantifying cognitive effort helps systematically develop productive work habits by letting them evaluate the work effort (in cognitive, not temporal) terms before taking on work tasks. Stress and unrealistic expectations can be managed more efficiently this way, as one knows “I have only 500 surges left but my Tasks 1…n would require 2000 surges… I better acknowledge my limitations and choose to work on Task 2 that requires an estimate of 500 surges, leaving the rest for other days.”
(Some of the best workers I’ve seen are good because they can realistically evaluate the effort needed and don’t take on more they can handle — so, they are already subconsciously doing this.)
Finally, moving from “hours worked” to “cognitive effort taken” makes sense for modern knowledge-based work.
For modern knowledge-based work, time is a poor metric, since tasks vary so strongly by the effort they require. A 2 two-hour intensive session working on a problem is equivalent to 4 hours of simple routine task from a cognitive point of view, maybe even more.
In addition, for personal development of individuals, systematic understanding of where one’s “surge efficiency” is the highest would help reach better efficiency outcomes that would benefit both the workers and the employing organizations.
Some limitations of this thinking:
What’s the relationship between surges and success given the unpredicable nature of creativity in some work tasks? For example, highly complex scientific problems might see a lot of surges being spent on them without any visible result. I wouldn’t still say it’s a lost effort, as payoffs of this kind take the “hockey stick” shape — for a very long time, nothing. Then, an “overnight explosion”. Given this unpredictable nature of innovation, relying too strictly on measures such as “surges” would be counterproductive and wrong.
Let me know if any thoughts!