1
Discovery call
We discuss the business context, what is being forecast today, where the friction is, and whether the problem is narrow enough to assess quickly.
Simple engagement model
How the work is structured
The process is designed to move from an initial planning problem to a justified implementation decision without unnecessary complexity.
2
Forecasting audit
We review the current process, the data that exists, the likely quality constraints, and the decision points the forecast needs to support.
3
Pilot
If the audit supports it, we test one well-defined use case with a realistic baseline, candidate approaches, and business-facing evaluation.
4
Production rollout
Only after a successful pilot do we define how outputs would be operationalized, monitored, and owned inside the business.
What clients usually need to provide
- A clear description of the planning decision to improve
- Historical data or exported reports that influence the forecast
- Context on seasonality, business rules, and operational constraints
- Access to the people who use the forecast day to day
What the process is meant to avoid
- Open-ended discovery with no clear outcome
- Jumping into model work before understanding the workflow
- Buying tools or infrastructure before feasibility is established
- Calling a pilot successful without a useful business comparison
Good fit signals
Planning matters
The forecast affects staffing, stock, service, or workload decisions.
Data exists
There is enough historical information to at least assess feasibility.
Decision-makers are engaged
The team wants a real go / no-go answer, not a generic AI presentation.