[HN Gopher] Velocity vs. Impact
       ___________________________________________________________________
        
       Velocity vs. Impact
        
       Author : kiyanwang
       Score  : 20 points
       Date   : 2023-02-17 09:31 UTC (13 hours ago)
        
 (HTM) web link (itamargilad.com)
 (TXT) w3m dump (itamargilad.com)
        
       | maximilianroos wrote:
       | This makes a strawman of "Velocity"
       | 
       | The purpose of Velocity is not to ship mediocre things quickly.
       | It's to figure out if you're building something people want, by
       | showing it to them and seeing if they use it.
       | 
       | Maybe you can introspect what will have impact? Great if you can!
       | But generally folks are overconfident in their beliefs &
       | underconfident in their actions, and so ship far too slowly.
        
       | vlovich123 wrote:
       | One limitation of this is when you do "no impact" work in year 1
       | and 2 that's high value impact work in year 3. Sure, if
       | everything is low hanging fruit go for it. But sometimes it can
       | take longer to build something that has 10x impact. eg teams A,
       | B, and C hit a wall because all their time is spent fighting
       | fires because they didn't invest in getting ahead of tech debt /
       | product growth. Of course, it's hard to make the case that that's
       | the case and you can be very wrong in which case you waste a lot
       | of time. But making sure that you are managing smoldering fires
       | and preventing them from becoming infernos is high impact
       | "invisible" work - did you prevent the inferno or was it unlikely
       | to ever catch in the first place". The usual approach is to let
       | things start tipping and hope you have enough lead time between
       | "this is starting to become a problem" and "product growth has to
       | cease and we have to start shedding customers"
        
       | Jtsummers wrote:
       | What a long article to ultimately get to the realization (but
       | fail to state it): If you pick a quantitative measure and
       | optimize for it as a target, that's what you get.
       | 
       | If you optimize for "velocity" (# of changes, here) then you get
       | velocity, a lot of changes. If you optimize for "high impact"
       | changes then you get high impact changes. This is not shocking.
       | What also shouldn't be shocking is that if the two are only
       | poorly correlated then you'll end up not getting meaningful
       | improvements in the other measure, and may in fact reduce the
       | other if there is a conflict between them.
       | 
       | The bigger problem is that most organizations don't know what
       | they want to optimize or how to measure the things they want to
       | optimize. So they find proxies like "velocity" or "impact" and
       | end up optimizing for them instead of what they actually want.
       | 
       | In other words, Goodhart's Law.
        
       ___________________________________________________________________
       (page generated 2023-02-17 23:00 UTC)