Client: A major HVAC company · Role: Short consulting assignment · Period: 2022-2024
Context
The company sells heat pumps, a market largely driven by government subsidies. Forecasts were made in Excel and were unreliable, for two reasons:
- demand for subsidised equipment depended on public decisions the company did not see coming, because it did not take part in the bodies where they were prepared;
- for other items, sales did not contribute to the forecasts.
What I did
- Scoping the need: what to forecast, at what level of detail, to inform which decisions.
- Steering towards a tool that could be used quickly: SKU Science, in SaaS mode, to start light and learn by doing.
- Training the teams in S&OP principles and in the tool.
- Setting up a monthly forecast review in which sales enter their forecasts directly in SKU Science.
- Main recommendation: take part in the industry’s professional bodies, where decisions on subsidies are prepared.
What I take away
The assignment ended before the results could be measured. It illustrates a point I often come across: an S&OP process and a forecasting tool provide a framework, but they are worth nothing without knowledge of what drives the market. Here, the first lever was not the tool but access to information on public subsidies.
Topics: Forecasting · S&OP · SaaS · Heat pumps
Expertise involved
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