Current increments vs known future
Hello,
At the bottom of our Backlog there was an entitiy versioning feature. This was known from the begining as required to the project but the team argued that we should consider it when it will be coming to the top of the backlog "because the backlog may change and we don't work in waterfall". Eventually that leads to huge changes at the end because the "big picture" was not considered.
As we know the Backlog may constantly change regarding the value which we need to provide to our customers. But we also got some things which we certainly would need because they already proven its value or they are a base for a value-adding features.
Another words I met the behaviour that "this code is not needed for current sprint" but it would be 95% needed for the future PBIs and it would be better to prepare now for the known, certain future.
Now I see that I should insist Product Owner to put the versioning to the top of the Backlog on the begining of the project.
I would like to ask how to advocate for:
* preparing in current Sprints for future PBI
* how to order the known certain non-complex things in the Backlog
* generally how to fit Big Picture into work on shippable product increments
Thanks,
Artur
It’s up to the Product Owner to decide how to best order the Product Backlog, and no-one should “insist” on a particular ordering or apply undue pressure.
Irrespective of how the Product Owner chooses to order items, do the team believe that Product Backlog refinement is being conducted appropriately, and that their current approach to refinement is fit for purpose?
Hi Ian, thanks for your answer.
After some time it turned out that the problem was in not using thin vertical slices in PBI. So we were developing the data ingress not thinking about how that data would be read. If that would be defined as Store and query Item Basic Properties and Store and query Item Advanced Properties then we would have a complete image (in thin slices) which would allow to select a proven solution for whole slice. Rather than implementing the naive solution for data storage and hoping that it would need huge refactors allow effective query later.