Not necessarily limited "intellect", but rather limited background knowledge.
Deming requires quite a bit of knowledge and understanding in failure/success modes. The core tenet of Deming is that every output is a result of some process and, therefore, output is controlled by controlling* the process itself. Look at your process and tackle failure modes in this priority list.
Drucker, on the other hand, puts the process under the fog of war and basically says deploy pressure on process outputs and let the process adjust itself. It requires much less understanding behind the processes to make sense.
* - Process control in Deming is mostly about variability.
Obviously the truth is messier than that, and it's worth noting that Drucker later recognised the toxicity of Management by Objectives and disavowed it. Quite a bit of OKR literature is devoted to avoiding it becoming its progenitor, MBO.
Worth adding that Deming (after Shewhart) recognised two kinds of variation: special cause (specific the work item in question) and common cause (an artifact of the process). That knowledge work involves a lot more of the former than does manufacturing does not excuse inattention to the latter.
> Drucker later recognised the toxicity of Management by Objectives and disavowed it.
Reminds me of a seminal treatise for Waterfall by Royce[0], where he basically says it’s fraught with issues, but can be coerced into something semi-usable. Not exactly a ringing endorsement. I think that paper is used as the template for all Waterfall work.
Obviously maths is going to be involved to do the subject justice. These recommendations are more about applied statistics, but that's the foundation. From there it is a small transition to statistical process control.
> Where Deming reads like a science paper, Drucker reads like an installation guide.
If you are looking for "do this" then Deming is not your person. If you seek understanding that drives transformation (knowing what to do in your context based on a broadly applicable value system), then Deming's system can deliver.
Lessons from the Red Bead Experiment include the fallacy of rating people and ranking them in order of performance for next year (based on previous performance), as well as attributing the performance of the system to the performance of the “willing workers” in this simulation of an organization governed by what Dr. Deming referred to as the “prevailing system of management.”
that kind of ties in with the article's thesis; deming's approach is more scientific in the classic sense of taking observations and using those to build up your mental models, whereas drucker proposes a one size fits all recipe for managing roadmaps.
Where Deming reads like a science paper, Drucker reads like an installation guide.