Big batches hide a real demand and decrease the throughput of the value

Big batches lock the capacity of a team for a longer time, which renders the team unresponsive for a longer time.

There are two interesting things that happen at that moment:

  1. Clients give up at asking your team for a request, which hides the real demand, or
  2. If they manage to get a hold of the team, they increase the request batch size since they are not sure when is the next time they are going to get a hold of the team and fulfill their needs. And, as you can imagine, this locks the team for even longer periods of time working mostly on low-value stuff. Stuff that clients are not even sure if they will need, which is packed together with a small percent of high-value stuff in that huge batch.

What we, in the end, get is big batches incentivizing hiding of the real demand and ever-lower throughput of the value (ratio between low-value to high-value stuff increases, because of increasing lack of responsiveness).

Small batches will increase the responsiveness of the team, which provides a real picture of the demand, and also clients are not incentivized to prioritize getting low-value stuff in the batch over waiting to see if they will even need it. This, in turn, helps with increasing the throughput of the value of the team.