The app automatically generates a sales forecast for every single item at every location and does so at the beginning of every month. Forecasts are based on monthly sales history and influenced by your forecasting settings.

All items are not alike, so it follows that not all sales forecasts should be alike either. That is why the app uses a variety of algorithms to tailor forecasts across your product range. Key to this is how the app categorises monthly sales history independently for each item at each location. We call this the Demand Type.

You can see the Demand Type on the Inquiry page above the mini demand chart.

Below, you'll find an explanation of each Demand Type, what kind of forecast is generated and some tips about managing items in these categories.

An item with no sales history will attract a forecast of zero. The example in the graphic represents an item with month-to-date sales only. If an item has no sales, there will be no lines in the graph at all. Keep an eye on the Top New items on your dashboard. These may include items that are newly in-stock or on-order which would benefit from your manual forecasts.

Once an item has at least one month of sales history it will be considered Young instead and start to attract an automatic forecast.

Tip: “Supersessions” can be used to generate a forecast for brand new items that are replacing existing items (the sales history of related superseded items will be included during forecasting).

A Young item has limited sales history. Limited in this sense means that it has only been a few months since the first recorded sale (or since the item first became available should the app be receiving such dates). Young items will attract a forecast based on a weighted moving average of the sales history.

These forecasts are based on limited information so you may like to pay a little more attention to these items and add your own manual forecasts where beneficial.

A Slow Mover item averages a very low quantity of sales per month with no seasonality. Slow Movers will attract a forecast based on a moving average of the sales history.

Slow movers can be difficult to forecast accurately and in some cases may benefit from minimum stock levels.

A Sporadic item doesn’t sell every month and may be characterised by just a few high volume (non-seasonal) transactions throughout the year. Sporadic items will attract a forecast based on a moving average of the sales history.

Although it might be reasonable to expect the sporadic sales peaks to continue, a smoothed forecast is generally a more reliable foundation on which to base order recommendations.

Sporadic items are perhaps the most difficult of all to forecast and may benefit from your attention. Manual forecasts, customer orders taken in advance of your supplier lead time and/or minimum stock levels can help.

A Seasonal item is one which exhibits a reasonably consistent monthly pattern across multiple years of sales history. For example, an item which sold best in December over the last three years would probably be identified as seasonal.

The app automatically tests for seasonality against a threshold based on your Seasonality setting. An item that passes the test will attract a seasonal forecast which may also include a detectable growth or decline trend.

A Linear Trend item is one that exhibits steady growth or decline over many months. These items will attract a forecast that extends that growth or decline into the future.

Items that do not meet the criteria for any of the other Demand Types are known as No Trend, No Seasonality. These will tend to be established regular selling items with no clear pattern of seasonality, growth or decline. These items will attract a forecast based on a weighted moving average of the sales history.

In addition to the main Demand Types described above, there are a few others which can apply in specific situations.

Sum of Locations may apply to items in a “region” location created in the app. It indicates that the region’s forecasts have been aggregated (summed) from its source locations rather than generated afresh.

Seasonal Group is a special category that may apply if the Advanced Forecasting Module is enabled and a Seasonal Group has been selected. It indicates that the seasonal profile from a group of related items has been applied to the individual item.