The Great Value of Knowing the Achievability

I have heard people say “Don’t tell me this is achievable. Tell me how to achieve.” So is it useless to know the achievability while not knowing how to? Not really. Knowing how to achieve will definitely make things more straightforward, but when you don’t know how to, there is still a great value to know the achievability.

Jared Diamond, in his book “Guns, Germs, and Steel: The Fates of Human Societies”, said that in the history, there were two ways how a society learned skills (e.g. grow wheat, tame cows, etc.) from another society in a nearby region:

  1. They learned the skills directly.
  2. They didn’t learned the skills directly, but they learned the achievability of certain things, then figured out the exact method by themselves.

For example, a society learned from a nearby society that cows are tamable and make good milk. They probably didn’t get to learn the exact method of domesticating cows from the nearby society, due to the language barrier, the nearby society’s unwillingness to share knowledge in order to keep competitive advantages, or whatever reasons. But having seen that the nearby society has successfully domesticated cows gave them the faith that cows are tamable and conviction to search for ways to do it. Also, this society wouldn’t potentially waste time trying to tame zebra or antelope. Jared pointed out that knowing which way is a dead end vs. which way can go through helped a lot of societies significantly shorten the time it took for them to advance their developments.

Knowing the achievability has great value in software engineering as well.

Speaking from my own experience. In my current group, a full test pass have about 4,000 test cases in total. When I joined, it took more than 24 hours to run and had only 80%-90% passing rate during most part of a release cycle. People were not happy with it but most of them seemed to think that’s just how it supposed to be. I told them no, it definitely can be much better. I told them that when I joined my prior group, things were in bad shape, too: it took >24 hours to run 12,000 test cases and similarly had only 80%-90% rate, but later we fixed it: the test duration shortened to sub-day (somewhere around 16-18 hours) and the failure rate dropped to low single digit %. I kept repeating this to everybody, telling them that since it was achieved in my prior group, we must be able to achieve it here as well. I also told them to have the right expectation of time: in my prior group, it took more than a year to fix it, so we should also anticipate similar amount of time to fix it here.

Knowing the achievability helped. Knowing approximately how long it will take to get there also helped. My team committed to improve the test efficiency and agility and made small and big investments one after another. After about 15 months, we were able to finish the same full test pass in just 7.5 hours. After about 2 years since we started the endeavor, 98-99% passing rate has become the norm. Had we not known the achievability, my team probably would have hesitated to make the investment, or pulled some resource out in the middle of the endeavor, due to having not (yet) seen the light of the end of the tunnel.

One Comment

  1. […] my previous team, as we made the automated tests faster, we found that now the long pole became the time human spent to make sense of the test result. So […]


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