(2017-07-17) Gilad Why Impact Effort Prioritization Doesnt Work

Itamar Gilad: Why Impact/Effort Prioritization Doesn’t Work. Effort can be stated in man/weeks or simply has high/medium/low. Impact can be graded on a scale, for example 1–5, 5 being the highest, or again as high/medium/low. Once you have the numbers in place, it’s a matter of picking the features that give you the best bang for the buck

Impact/Effort Matrix

As with most models, the idea is compellingly simple — dividing the space into four quadrants (2x2) helps us see how projects stack up

As straightforward as this all seems, there are major problems with Impact/Effort prioritization that cause us to pick the wrong winners

Most importantly Impact/Effort analysis requires us to make somewhat reliable predictions on future events

Once systematic measurements of success/failure are in place we get a clear, and very sobering picture of how little we can predict impact

Overlaying the projects on this updated matrix tells a new, and less optimistic story.

Five ways to make Impact/Effort prioritization work

First you should come to grips with the fact that 60–90% of the projects in your product backlog are not worth doing

Prioritization and experimentation are needed to find those few gems that are worth doing

1. Do back-of-the-envelope impact calculations

break them into their parts and placing guesstimates on the subparts

2. Use available data or new data

comparing to something very similar that we already launched.

3. Think of low-cost ways to validate your assumptions

For bigger projects

4. Factor in Confidence

5. A/B tests

A/B thus allow us to make big bets with relatively low risk. (You still have the build cost, which is the biggest reason for prioritizing.)

(the problem is accurately defined, but poorly improved/solved)