Implementation worksheet · 2 min read
A next-best-action decision log template
A next-best-action log records what the system knew, which actions were eligible, why it selected one and what happened afterward. Preserve decision time separately from outcome time. This makes an automated lifecycle action explainable and helps distinguish a poor decision from stale data, failed delivery or missing measurement.
Imagine an account that has not completed setup. The system could offer help, send a reminder or do nothing because the account recently contacted support. The log should expose those alternatives and constraints without copying unnecessary customer data into a broadly shared report.
Put it into practice
1. Capture the decision context
Record the account identifier, decision timestamp, policy version and a reference to the input snapshot. Include freshness and missing-data flags. A decision cannot be evaluated fairly using information that arrived later.
2. List eligible actions
Record the candidate actions and exclusions applied to each. Include ‘no action’ as a real option. Consent, frequency, support status and eligibility constraints should be visible rather than hidden inside an unexplained score.
3. Record selection rationale
Store the chosen action, policy or model version and a concise reason code. Distinguish a rule-driven decision from a model score. Avoid treating a generated explanation as proof of the model's internal reasoning.
4. Track execution separately
Link the decision to approval, dispatch and delivery records. Record failures and fallbacks. A selected action that never executes is an operations issue, not evidence that the intervention failed to influence the customer.
5. Attach outcome evaluation
Join the outcome using the predefined event and window. Include holdout assignment where relevant. Review a sample of decisions against the policy and investigate repeated missing-data or exclusion failures.
Decision log fields
Copy this structure into your review document and record your observed result for each row.
| Stage | Fields | Question answered |
|---|---|---|
| Context | Timestamp, snapshot, freshness | What was known? |
| Eligibility | Candidates and exclusions | What was allowed? |
| Selection | Action and policy version | What was chosen? |
| Execution | Dispatch, delivery, failure | Did it happen? |
| Evaluation | Outcome and experiment group | What followed? |
A failure worth checking
An outcome observed after an action is not automatically caused by that action. Keep operational tracing and causal measurement separate. The log enables investigation; an appropriate experiment supports an incremental-effect claim.
Common questions
Should the log contain full customer profiles?
Usually no. Prefer stable references and the minimum fields needed to reconstruct the decision in approved systems.
Can no action be the best action?
Yes. Recent contact, missing evidence, a support incident or a frequency limit may make doing nothing the appropriate decision.
Basis and scope
This is a proposed implementation method using illustrative examples, not a measured benchmark or a customer case study. Prepared with AI assistance. Validate product-specific behavior against current documentation and your own test environment.