Forecast PRO TRAC budgeting and forecasting Software
Forecast Pro Trac is the latest version of the Forecast Pro family and it's ideal for demand forecasting, demand planning, demand management, sales forecasting, item level planning, sku forecasting. Easy to use, light years more advanced than spreadsheets and enjoys award winning status for its statistical forecasting accuracy and is much less expensive than many of the alternatives.
MXI Forecast PRO UK combines forecasting, management reporting, graphing, reporting and adjustment capabilities as found in Forecast PRO unlimited. However Forecast PRO TRAC also provides easy to understand data graphics business intelligence that concentrate attention on the MAPE to drive forecasting accuracy improvement.
Forecast PRO uses will be able to select non performing forecasts and specifically concentrate attention on forecast accuracy. For example a specific exception report in the business intelligence selector allows users to select forecasts which are greater than 50% out against actuals and concentrate on them.
Forecast Pro TRAC allows you to view your data and forecasts in as many units of measure as you need. A drop down menu lets you select for example.
Rearrange your hierarchies.
With Forecast Pro TRAC's powerful "shuffling" capability, you can rearrange hierarchies with just a couple of clicks. Generate reports showing product-level forecasts broken out by customer and the
Forecast Accuracy, Identify SKU, pruduct groups which need attention
With Forecast Pro TRAC's flexible exception reporting, you can automatically flag exceptions, saving you from having to manually review a long list of items
Statistical forecasting accuracy improvement
Forecast Pro TRAC maintains an archive of your previous forecasts (both statistically-generated and adjusted forecasts) so that you can compare and contrast previous forecasts to what actually happened.
Consolidate your team's forecasts.
Forecast Pro TRAC breaks large forecasting projects into smaller pieces that can be worked on separately and then reassembled into consolidated forecasts. For example, if three demand planners are responsible for forecasting three different geographical territories, they can work on their forecasts separately; after they're done, their consolidated forecast can be further manipulated.
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