Iterative Planning
Planning as recurring sensemaking—updating direction as reality changes rather than treating plans as fixed commitments.
What is this practice?
Iterative planning is the practice of planning in short cycles, using what has been learned to update priorities, scope, and approach.
Instead of assuming the future can be known in detail, teams plan enough to move, then revisit plans as new information and constraints appear.
Why does this matter in this transformation?
In a cloud migration, dependencies, risks, and constraints surface over time. Plans made too far in advance often become outdated, creating friction and rework.
Iterative planning supports the transformation by keeping direction aligned with reality, enabling teams to adapt without losing coherence across boundaries.
What does “good” look like?
When iterative planning is working well, teams revisit priorities regularly and can explain why changes were made. Work stays aligned to current constraints and goals, and surprises are surfaced early rather than deferred.
Planning conversations become clearer and less adversarial because uncertainty is expected and handled openly.
What gets in the way?
Common challenges include pressure to lock commitments too early, planning done in isolation from dependent teams, and the belief that changing a plan is a failure rather than a response to learning.
Teams may also confuse iterative planning with lack of discipline, when it actually requires steady cadence and clear decision-making.
How might someone begin?
Many teams begin by shortening their planning horizon and establishing a regular cadence to revisit priorities using fresh information.
Starting with one team’s planning cycle and then adding lightweight cross-team touchpoints can improve alignment without requiring a full process redesign.
Explore deeper with your AI assistant
Use your AI assistant to reason through this practice in your own context.
Prompt:
I’m exploring the practice of iterative planning in the context of a cloud migration and broader organizational change.
Help me reason through this practice by:
- explaining it in plain language without assuming specific tools or frameworks
- highlighting the tradeoffs and tensions it introduces
- describing what “good” tends to look like in real teams
- calling out common failure modes or misunderstandings
- suggesting small, low-risk ways teams often begin experimenting
- articulating who are the vendor-neutral thought leaders in the space
Please keep the discussion exploratory and context-aware rather than prescriptive.