Risk is lost in the discussion but very relevant to management.
In theory, in the most productive engineering organization, each person is the expert at what they're doing and work is factored to avoid overlap. This happens somewhat naturally as people silo (to avoid conflict and preserve flexibility). This is actually the perfect system, if your people are perfect: their incentives are aligned, they're working with goodwill, etc.
But that makes every person critical, few people can operate at that level all the time, and fewer still want to work alone doing the same thing ad infinitum. Also, needs change, re-factors work and its mapping to workers.
So then you expand the scope to productivity over time with accommodation for change - i.e., capacity.
But by definition, capacity far exceeds output, and is thus unobservable and unmeasurable.
So instead you experiment and measure: switch roles, re-organize work, address new kinds of problems and prototype new kinds of solutions, bounded by reasonably anticipated product needs.
And to inject this uncertainty, you actually have to inject a lot of countervailing positivity, to deflect the fear of measurement or failure, to encourage sharing, etc.
Unfortunately, these experiments and freedom from consequences is pretty indistinguishable from the bureaucratic games and padding that productivity measures are designed to limit.
In theory, in the most productive engineering organization, each person is the expert at what they're doing and work is factored to avoid overlap. This happens somewhat naturally as people silo (to avoid conflict and preserve flexibility). This is actually the perfect system, if your people are perfect: their incentives are aligned, they're working with goodwill, etc.
But that makes every person critical, few people can operate at that level all the time, and fewer still want to work alone doing the same thing ad infinitum. Also, needs change, re-factors work and its mapping to workers.
So then you expand the scope to productivity over time with accommodation for change - i.e., capacity.
But by definition, capacity far exceeds output, and is thus unobservable and unmeasurable.
So instead you experiment and measure: switch roles, re-organize work, address new kinds of problems and prototype new kinds of solutions, bounded by reasonably anticipated product needs.
And to inject this uncertainty, you actually have to inject a lot of countervailing positivity, to deflect the fear of measurement or failure, to encourage sharing, etc.
Unfortunately, these experiments and freedom from consequences is pretty indistinguishable from the bureaucratic games and padding that productivity measures are designed to limit.