RAP for organisational productivity: Relearning, Allocation, Parallel bets

Jason Yip
3 min readJan 4, 2023

Some individual and team productivity practices also translate to the organizational level

Organisational productivity has factors that overlap with both team productivity and individual productivity:

  • Increasing focus;
  • Frequent customer feedback;
  • Reducing friction;
  • Watching the work product, not the workers;
  • Frequent integration

However, organisational productivity goes beyond just a translation of individual and team productivity practices:

  • Reducing relearning;
  • Improving effort allocation;
  • Taking parallel bets

Learning is good; relearning is waste

Relearning refers to reinventing lessons whether about product, ways of working, or technology.

Two columns marked with a smiley face and a frowning face. Under smiley face: Learning new things; Building new, useful things. Under frowning face: Reinventing lessons because we don’t share knowledge; Rebuilding something because we don’t know that it already exists
Learning vs relearning

Addressing relearning is about knowledge management and platformisation.

Throughput doesn’t matter if it’s mostly on low-value things

Product capabilities exist within a life cycle.

Graph of product life cycle stages. X-axis time, y-axis revenue. Stage 1: market development with no or low revenue; Stage 2: Growth with rapidly increasing revenue; Stage 3: Maturity with still increasing revenue but slowing; Stage 4: Decline with decreasing revenue
Product life cycle stages

Let’s imagine two different organisations: A and B. A completes tasks more efficiently than B, but A’s efforts are mostly on commodity capabilities, while B’s efforts are mostly on differentiating capabilities.

Throughput of A is twice that of B. Differentiating features are worth 5 times commodity improvements. A mostly works on commodity; B mostly works on differentiating. A produces more stuff; B is actually more productive.
A has more throughput; B is more productive

A is more “productive” than B but most of their capacity is allocated to low-value capabilities… which means B might actually be more productive from an organisational perspective (value out divided by effort in).

Or course, ideally, we’d want an organisation C that is both higher throughput and better at allocating efforts to higher value activities, but the point is that improving effort allocation also effectively improves overall organisational productivity.

A potential advantage of larger organizations is the ability to take parallel bets

Let’s imagine we have a number of ideas to explore and only some of them will end up being valuable. We take a bet on the most promising one and proceed in an iterative, incremental fashion. Unfortunately, we bet wrong, and we have to abandon the idea and choose the next most promising one.

Idea backlog (we can’t see which ones are dead ends). Take a bet on what seems most promising and iterate… But we bet wrong… so we have to start over.
Serial iteration

Now let’s imagine that instead of taking each bet one after another, we take multiple, parallel bets. We’ve almost guaranteed that some of the bets we’ve taken will fail BUT the winning bets will succeed much faster than the previous serial approach.

Idea backlog (we can’t see which ones are dead ends). Take parallel bets. Some bets will fail but some will succeed.
Parallel bets

This parallel bet approach is the advantage a larger organization with a lot of resources has over a smaller one IF the larger organization is smart enough to exploit it.

See also set-based concurrent engineering.

See also



Jason Yip

Senior Manager Product Engineering at Grainger. Extreme Programming, Agile, Lean guy. Ex-Spotify, ex-ThoughtWorks, ex-CruiseControl