The problem this solves
Go-live gets treated as the finish line when it is the start of the risky part. Everyone gets access on the same day, support means pinging whoever built the thing, usage drops after the novelty week, and nobody defined what good adoption looks like, so the decline goes unnoticed until a renewal or board question forces the issue. Shadow spreadsheets follow shortly after.
How we work
We design the rollout sequence for your context: pilot group selection with a clear statement of what the pilot must prove, phased versus full launch, and the criteria for advancing from one phase to the next rather than advancing on calendar momentum.
Adoption gets defined in measurable terms per role: records maintained, pipelines updated, sequences run, tickets worked, whatever reflects the real work the system must hold. We set baselines, targets, and a review rhythm, and we design the support model: who answers questions, how issues escalate, and how feedback turns into fixes.
The plan ends with hypercare: a deliberately intense support and iteration period after each launch wave, with explicit exit criteria into steady state instead of an indefinite emergency.
Deliverables
- Rollout sequencing plan with phase advancement criteria
- Pilot design with success criteria
- Adoption metric definitions per role, with baselines and targets
- Support and escalation model
- Hypercare plan with exit criteria
- Risk and rollback considerations
What buyers ask before scoping.
How does this differ from Change Strategy & Approach Design?
Change strategy picks the overall approach and sponsorship model; this module makes it operational: dates, groups, metrics, owners, support flows. If you have skipped the strategy layer and the rollout is modest, we make the necessary approach calls inside this module and note them explicitly.
Which adoption metrics actually matter?
The ones tied to work you need the system to hold. Logins are vanity; a pipeline that reflects reality, contact records that stay complete, and sequences actually running are adoption. We define a small set per role so the metrics get looked at instead of archived.
How long should hypercare last?
Long enough that support volume and adoption metrics stabilize, and no longer. We define exit criteria rather than a fixed number of weeks, because the honest answer depends on rollout size and how much process change rode along with the system. Exiting on evidence beats exiting on exhaustion.
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Sounds like your situation?
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