How to address data and architecture standards in agile development

Making time to plan for standard practices pays off in the long term

One challenge agile leaders and teams face is how to define and follow data and architectural patterns and standards in agile development. There’s a belief that it’s hard to drive data and technical standards because agile teams work in sprints that are usually two to four weeks long, and product owners generally overbook the backlog with prioritized features. Standards take time to develop; following them requires teams to have sufficient time to plan technical implementations.

Agile teams that execute in one sprint and plan only the next one will have a hard time using standards to formulate their development plans. If documented standards aren’t easy to follow or reference, then teams are less efficient, and it’s harder to train new developers on best architecture and data practices. It’s like a team wandering in the forest without a map or a GPS; they might be able to get to the next trailhead but they won’t know if they’re heading down an optimal path to get back to town.

What data and architecture problems need attention

It might help to put data and architecture standards in two categories:

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