Optimisation of production planning
How a monthly sales forecast with an 18 month rolling horizon let a manufacturer plan production against expected demand, cutting delivery bottlenecks by 73 percent while average inventory came down 2 percent. Prospero does not name the manufacturer.
Forecast first, then plan against the forecast
Sales forecasting and production planning were not co-ordinated, which showed up as volatility in the plant and as long lead times to the customer. The work put a forecast in front of the planning rather than beside it.
At a glance
- Sector
- Manufacturing
- Solution
- DetectX® Business Monitoring
- Customer
- Not published
- Location and date
- Not published
The story, as Prospero publishes it
The business challenge
Volatile production, long lead times, two plans that did not meet
- A manufacturer was experiencing high production volatilities and long lead times due to challenges with the co-ordination of sales forecasting and production planning.
The solution
A sales forecast model, run monthly, 18 months ahead
- A new sales forecast model was built using DetectX® Business Monitoring and the underlying predictive analytics capability of the DetectX® platform. Prospero were able to create predictive models that forecast sales volumes based on sales history data and external market data. Based on global sales data, this model is run on a monthly basis, providing an 18 month rolling sales forecast.
The results
Bottlenecks down 73 percent, and inventory down with them
- Based on the new forecasting model the manufacturer was able to optimise production planning. This reduced delivery bottlenecks by 73 percent while at the same time reducing average inventory by 2 percent. The source states why that balance is the point: high stock levels can improve lead times but they tie up liquidity, so the challenge is to keep inventory low while still improving delivery lead times to customers.
What the forecast returned
Two results that move in the same direction for opposite reasons, and the horizon the forecast runs to. All three are Prospero's own and none is footnoted.
Published result
73% fewer bottlenecks
The reduction in delivery bottlenecks after production planning was rebuilt around the forecast, as Prospero states it.
2% less inventory
Average inventory fell at the same time. The source calls this the harder half: stock buys lead time at the cost of liquidity, so a reduction alongside fewer bottlenecks is the result rather than a compromise on it.
18 months ahead
The forecast horizon, rolled forward monthly from global sales history and external market data.
There is no customer quotation on this page because the source has none, and no customer name because the source gives none. Both percentages are unattributed and undated, and neither should be read as a benchmark.
Where to look next
The sector page for work outside financial services, the platform the model was built on, and the two other manufacturing studies.
- Beyond financial services
- Where DetectX® is applied outside banking and insurance.
- DetectX® platform
- The predictive analytics layer these models are built on.
- Early detection of delivery delays
- The same module, finding the factors behind late deliveries rather than forecasting demand.
- Process optimisation in aluminium company
- An early warning model on input data measured before the production run.