A signed agreement can trigger a welcome email, a project board, and a kickoff invitation while the delivery team is still missing the information it needs. Automating those actions does not establish that the project is ready.
A more useful starting point is to define readiness. What must be known, accepted, assigned, or available before someone commits delivery capacity? The example below describes a possible service-business workflow, not a measured client result.
Define the condition for starting
Write down the minimum requirements for the first deliverable. They might include an accepted scope, a named delivery owner, usable access, required client material, and an agreed first milestone. The requirements should change with the service; they should not become a universal form that collects everything.
For each requirement, distinguish received from verified. An uploaded file may be incomplete. Credentials may not work. A proposed date may not be accepted. Store the evidence and the person responsible for checking it.
Give the handoff an owner
Sales can initiate the handoff, but the receiving team should accept it. Until that acceptance, someone must remain responsible for resolving the gap. Otherwise, a completed sales task can coexist with an unowned delivery problem.
Keep one authoritative readiness record and link to the underlying material. Do not require the same scope, dates, and contact details to be manually maintained in a document, a CRM, and a project board. Where systems must copy information, define which source wins when values disagree.
| State | Condition for leaving it |
|---|---|
| Awaiting information | Required inputs are received |
| Under review | Inputs, access, and scope are verified |
| Ready for delivery | A delivery owner accepts the handoff |
| In delivery | The agreed first activity has started |
Make blocked work explicit
Record the missing item, its owner, and the next decision needed. A generic blocked label tells a manager little about what to do. An exception might require a client answer, an internal approval, or a decision to change the scope.
Choose reminder timing according to the commitment and the cost of delay. Repeated messages are not a substitute for escalation. If the date is at risk, route that decision to the person who can renegotiate it.
Keep manual exceptions possible, but record who accepted the risk and what follow-up is required. Do not make the system look complete by hiding incomplete work.
Use AI where interpretation helps
An AI-assisted step could extract candidate requirements from a statement of work, compare incoming material against a checklist, or draft a question about a conflict. A person can confirm the interpretation before it changes the readiness record.
Use ordinary validation for explicit conditions: a missing owner, an absent approval, or an invalid date does not need a model. Keep client-facing commitments and consequential scope changes behind the appropriate approval.
Google’s SRE writing distinguishes recurring, automatable work from engineering that produces a lasting improvement. Applied here, that suggests redesigning the repeated chase before merely making each reminder easier to send.
Reference: Google SRE: Eliminating Toil
Measure the handoff rather than the activity
Start with the time from agreement to accepted readiness, the age of unresolved blockers, and the frequency of rejected handoffs. Review actual cases to understand why a number changed. Faster onboarding is not an improvement if incomplete inputs are being waved through.
Separate waiting on the client from waiting inside your own team. Track time spent checking and correcting the workflow as well as time saved on administration. Use observed baselines instead of assumed savings.
Implement this in the tools the team already maintains where possible. The deliverable is a clear readiness rule and a reliable handoff, not another dashboard that needs an owner.
Sources
The distinction between repetitive work and lasting systems improvement. The onboarding model is a proposed application, not a Google case study.
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