Strategy question

You inherit a signed public-sector AI/data deployment that has not reached production three months after contract start. Security accreditation is incomplete, data interfaces are unstable, and the customer has no agreed definition of 'production-ready.' How would you structure the path from contract to production, what milestones would you use, and how would you surface the top risks early enough to change the plan?

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What this question tests

Whether you can bring structure and risk visibility to a stalled, high-stakes public-sector deployment without clear success criteria.

How to approach it

  1. Start by defining 'production-ready' jointly with the customer in writing, since the absence of an agreed definition is itself the root blocker.
  2. Audit the current state across three tracks: security accreditation status, data interface stability, and any remaining functional gaps, each with an owner and a real timeline.
  3. Set milestone-based checkpoints (for example accreditation submission, interface stability testing, user acceptance testing) rather than a single go-live date, so progress is visible in stages.
  4. Surface the top three risks explicitly to your own leadership and the customer early, for example accreditation delay being outside your control, so the plan can be adjusted before it becomes a crisis.
  5. Build a weekly risk and status review with the customer that shows real progress against milestones, rebuilding trust through visible, incremental delivery.
  6. Escalate internally for resourcing help on the highest-risk track, likely accreditation, since that is often the longest and least controllable dependency.

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