The IMA toolkit comprises of 3 fully integrated modules designed to help the client
maximise their investment in inventory.
For those clients needing to address a specific business opportunity each module can
be implemented independantly
- It is a truism that forecasts drive the business
- We all claim to be customer oriented. But there is one factor more than any other that keeps the customers happy – having what he wants in stock when he wants it. The more accurate our forecasting, the happier are our customers
- The prime cost of holding stock to meet customer demand is the cost of stock itself. Added to this is the cost of potential obsolescence. The more accurate our forecasts the less we have of both stock and obsolescence
- It is generally realised that achieving forecast accuracy is a win/win situation; service is enhanced while stock is reduced. In addition in a period of constrained cash flow the reduction in investment in stock achieved by enhanced forecast accuracy can be vital to business survival
- Then there is the competitive advantage of accurate forecasting. The prime reason customers change supplier is cost but the second is the supplier’s ability to meet customer demand. A proven ability to supply arising from more accurate forecasting is a key competitive advantage
- In terms of KPIs relating to forecast the most essential one is Forecast Accuracy
But there is another KPIs that is also important but rather more difficult to define. Forecasting takes time – often lots of it when you consider the spreadsheets, the accumulation of these spreadsheets, and the endless meetings which try to make sense of them. The question is – is this time worth the results it achieves and some measure of this is well worth considering.
As an example, from a recent study we conducted, a company had their 10 sales people fill in forecasting spreadsheets for each key product for each of their customers. It took quite a time each month. We compared these with a simple average of past demand. The total of the sales peoples’ forecasts turned out to be 20% too high when compared with the actual while the total of the averages was 4% too low. In addition the sales peoples’ forecasts were more accurate in 42% of cases while the average was more accurate 58% of the time. Was it time well spent? This finding, in our experience, is not at all unusual.
A very simple KPI is to compare the sales forecasts with a simple mechanically generated forecast to gauge the worth of the sales forecasting exercise.
These two KPIs give a measure of the worth of the forecasting process and they can also be used to constantly improve forecasting.
Here are some of the issues existing clients have addressed with IMA's demand forecasting:
- New product launches
- Long inbound product lead times servicing short customer despatch lead times
- Capacity and resource planning
- Improved visibility of business trends
- Stock outs of critical parts causing service level issues
IMA's demand forecasting provides extensive functionality including:
- Simple data interfaces to the host business system
- Ability to forecast at ‘key’ customer level
- 15 forecast algorithms for the experienced forecaster
- Optimal Fit technology for clients who prefer the software to determine ‘best fit’
- Market knowledge over-ride capability & monitoring of effectiveness
- Projected Inventory status
- New product launch control
- End of product life control
- Demand or seasonal view of sales history
- Tabular & graphical display of combined historical & forecast data
- Macro to micro view of key data via one-click
- Extensive reporting of ‘key’ data
- Forecasts viewable in either value or quantity formats