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Forecast Analysis

Updated

Summary

The Forecast Analysis screen allows you to see forecast information in various grid views that can be sorted, filtered, graphed, and pivoted in various ways.

It is accessible through the Forecast --> Forecast Analysis screen.

There are three tabs of information, each of which is laid out similarly for Item-Site level forecast data, Item-Site-Forecast-Group level information, and Forecast info summed by a hierarchy level you select.

IMPORTANT: The forecast analysis is typically refreshed only once per day.  If you make a lot of forecast changes, you can click the "Refresh" button in the Forecast Analysis screen to have the forecast analysis data refreshed without waiting for a StockIQ refresh.

There are two types of displays for the Forecast Analysis, which you can select using the Display Options (see below):

  • Pivot - This is the default layout, with a pivot grid at top for moving your data around, and a chart which is bound to the pivot, so that as you change your pivot grid, your chart will update accordingly as well.
  • Grid - This provides a flat grid of data with a matching chart in which you can pick a series to chart over time from the Display Options.

Layout 

In each tab, there is a grid, a chart, and a pivot table.  Keep in mind the grid view may be hidden by the Display.

The grid contains the forecasted quantity, COGS, Revenue, and margin for the period listed, e.g. the month or week in question.

You can use the filters button to filter this down to certain subsets of data, as well as use the grid to further filter down the data that is displayed in the grid.  

NOTE: If you have filters applied and you are in the "By Hierarchy Level" tab, those filters will still apply, e.g. things will be removed from those hierarchy totals.

Display Options

As with other screens in StockIQ, the display button contains options for controlling the display of data.  This can be especially useful in the "By Hierarchy" tab if you wish to customize the format of the chart.  For example, select a monthly chart interval with "Stacked Bar", raise the max number of series to as many hierarchy items as you possibly wish to see (beyond 30 the chart can become difficult to read), and change the chart measure to a value-based measurement like Revenue or Margin.  Use the "Hierarchy Level" select box to move the level of aggregation up and down your forecasting hierarchy.

  • Chart Measure - What do you want charted on the grid-associated chart?
  • Time Interval - What time interval do you want the forecast analysis data presented in? Weekly/Monthly/Quaterly/Annual Rollup
  • Chart Type - What type of chart for the grid-associated chart?
  • Max # of Series - Max number of series to go on any one chart.
  • Hierarchy Level - What level of the hierarchy do you want to see in the "By Hierarchy Level" tab?
  • Demand Forecast Series - Since this is the forecast analysis screen, which series do you want shown - your operational forecast, a budget forecast, etc?
  • Layout - Panel Type - Do you want to see the "Grid" style layout, or the "Pivot" style layout with the chart bound to the pivot as you change?

 

Grid Column & Pivot Field Values

Various columns of data are shown, which are common across the various tabs of information.   Some of the shared data:

  • Date - The forecast date in question, e.g. the month period identifier or start-of-week date
  • Forecast Qty - The forecast quantity in place.  This includes the effects of any events or part replacements that may exist.
  • COGS - Cost of goods sold or forecasted cost-of-goods-to-sell.
    • At the bottom level of your hierarchy, this is determined by multiplying the quantity by an average unit cost value calculated by StockIQ.  See Average Price and Cost calculations topic.
    • At higher, non-leaf levels of the hierarchy, COGS is calculated by summing COGS from lower-level hierarchy nodes, and the average unit cost value is in turn derived by dividing COGS and units.
  • Revenue - Historical or future prediction of revenue based on the forecasted value.
    • At the bottom level of your hierarchy, this is determined by multiplying the quantity by an average unit price value calculated by StockIQ.  See Average Cost And Price calculations topic.
    • At higher, non-leaf levels of the hierarchy, Revenue is calculated by summing Revenue from lower-level hierarchy nodes, and the average unit price value is in turn derived by dividing revenue and units.
  • Margin - Historical or future prediction of margin, based on the forecast quantity.
    • At the bottom level of your hierarchy, this is determined by multiplying the quantity by an average cost and price value calculated by StockIQ.  See Average Cost And Price calculations topic.
    • At higher, non-leaf levels of the hierarchy, Revenue is calculated by summing Revenue from lower-level hierarchy nodes, and the average unit price value is in turn derived by dividing revenue and units.
  • Projected On Hand $ - If available, projected on-hand value for this item as of that date
  • Actuals - Actual demand history for this period
  • Actual COGS - Actual COGS for this period, using the same average cost and price hierarchy as above.
  • Actual Revenue - actual revenue recorded on sales orders, using the same fallback average cost and price hierarchy if necessary
  • Actual Margin - Actual margin
  • Forecast Error % - Percent error of your forecast versus actuals in this period (this is not an average error)
  • Forecast Error Units - Units of error of your forecast quantity vs actuals in this period
  • Forecast Error (Value) - Value in terms of currency (e.g. $) of your forecast error for this period
  • Bias (forecast bias) - A positive bias means you are over-forecasting consistently, whereas a negative bias means you are under-forecasting consistently.   (Sum of Forecast) / (Sum of Sales)

Exporting Data

As with other screens in StockIQ, you can export the grid and pivot.  Also, if you have your system configured to read in data exports from StockIQ via dedicated output tables, you can click the "Export" button, and it will re-run whatever pre-configured process you have for exporting the data to an external system, such as your ERP or a data warehouse.

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