Demand Forecasting and Planning
Forecasts that planners trust enough to act on.
- Typical duration
- 6 to 10 weeks
- Deliverables
- 5 core artifacts
Overview
Forecast accuracy is a means, not an end. The question that matters is whether the forecast changes a decision: how much to buy, how much to build, how much capacity to hold. We build forecasting systems around those decisions and measure them by the cost of the errors they produce, not by accuracy percentage alone.
That means hierarchical models that reconcile across item, location, and channel, explicit handling of promotions, seasonality, and new product introductions, and probabilistic output so downstream inventory and capacity decisions can price uncertainty instead of ignoring it.
What you get out of it
- Measurable accuracy lift over the current statistical and consensus baseline
- Probabilistic forecasts that feed inventory policy directly
- Segmented approach so effort follows value and volatility
- Bias and value add diagnostics on every step of the consensus process
Capabilities
What the work actually involves.
Hierarchical forecasting
Coherent forecasts across product, location, customer, and time hierarchies using reconciliation methods rather than manual top down disaggregation.
Causal and promotional modeling
Price, promotion, weather, holidays, and marketing spend modeled explicitly, with lift and cannibalization separated rather than blended into the base.
Intermittent and long tail demand
Croston family, bootstrapping, and count based models for the slow movers that traditional exponential smoothing handles badly and that dominate most item counts.
New product introduction
Analog based launch curves with structured attribute matching, plus disciplined phase in and phase out logic so successor items do not inherit a dead predecessor history.
Forecast value add
Instrumentation that shows whether each human touch improves or degrades the statistical baseline, by planner, by segment, and over time.
Questions
Things people ask first.
- Will this replace our planners?
- No. It moves them off the large share of items where the statistical model already beats a manual override, so their judgment lands on the items where it actually adds value.
- Does it need to run inside our planning system?
- It usually runs alongside it. We produce the forecast in a pipeline you control and publish it into the planning system, which avoids being constrained by the vendor model library.
Next step
Have a forecasting question?
Send the decision you are facing. A first conversation is a working session, and it usually clarifies scope more than a proposal would.