Advanced Reordering Overview - Reorder Calculation

Advanced Reordering uses your historical sales to forecast future demand, then calculates how much stock you need to order so you don’t fall below your minimum stock level.

For each item, the system will:

• Analyse past sales over a defined analysis period.
• Forecast future demand using either Linear Regression or Fitter Curve
• Compare this forecast to your current and expected stock.
• Suggest an order quantity to keep you at or above your minimum (including backorders, if configured).

Where you control Advanced Reorder settings:

1. IN Module Control > Defaults tab.  Set the system‑wide Advanced Reorder details including 
   1. Historical analysis period
   2. Default forecasting method (Linear Regression or Fitted Curve)
2. Analysis Code Maintenance.  
   1. Optionally override the system‑wide forecasting method for specific analysis codes
3. Inventory Item Maintenance > Defaults tab
   1. Optionally override the forecasting method for individual items

Use IN Module Control for your default (global) setup and only use Analysis Code or Inventory Item defaults when specific groups or items need different methods.

How the forecast is calculated:

For each inventory item included in the reorder run, the system will:

1. Build sales history and averages
   1. All sales transactions are grouped into historical periods based on your Advanced Reorder settings.
   2. The system calculates the average sales for each period.
2. Apply a forecasting method
   1. Linear Regression: projects a straight-line trend using the sales history.
   2. Fitted Curve: models repeating, cyclical patterns using a wave average
3. Calculate variation (standard deviation)
   1. Linear Regression: standard deviation is based on the sales history.
   2. Fitted Curve: it’s based on the wave average.
4. Project future on‑hand stock. For each forecast period, the system will:
   1. Subtracts forecast sales.
   2. Adds expected purchase order deliveries, using expected delivery dates for outstanding order lines.
5. Include backorders in your minimum (if enabled)
   1. If your settings include backorders in the minimum, current backorder quantities are added to the minimum quantity so suggested order quantities at least cover existing backorders.
6. Calculate the suggested reorder quantity
   1. The suggested quantity is the difference between:
      1. Your forecasted inventory holding (after expected sales and deliveries), and
      2. The minimum quantity you want to hold.
   2. This restores stock to at least the minimum and covers expected demand to the end of the prediction period.
7. Adjust for EOQ (Economic Order Quantity)
   1. If an EOQ factor is set in Supplier Maintenance, the suggested quantity is rounded up to the nearest EOQ multiple.

How the prediction period works

The system predicts inventory requirements over a specific period:

1. It starts at the planned delivery time for the current purchase order (if one exists).
2. It ends at the expected delivery time for the next order.
3. These dates have come from:
   1. The order cycle‑time, and
   2. The lead time for the delivery method.

Throughout the prediction period:

1. Expected sales reduce your projected inventory holding.
2. Expected deliveries increase it.
3. If the predicted holding drops below your nominated minimum quantity (including backorders if configured), the system recommends an order that:
   1. Brings stock back up to at least the minimum, and
   2. Covers expected sales through to the end of the prediction period.

Sales Weighting and confidence

Because forecasts are based on statistics, they’re not 100% accurate. Advanced Reorder uses a 90% confidence interval for predicted sales.

The Sales Weighting setting controls where within this range the forecast sits:

1. Range: 0 to 100.
2. Effect of different settings:
   1. 50–100 (higher weighting):
      1. Biases the forecast towards higher demand.
      2. Reduces the chance of stock‑outs
      3. Typically increases stock on hand.
   2. 0–50 (lower weighting):
      1. Biases the forecast towards lower demand.
      2. Reduces stock on hand
      3. Increases the risk of stock‑outs.

1. Use this to choose whether you want to prioritise:
   1. Availability: more stock, fewer stock‑outs or
   2. Lean inventory: lower stock, higher risk of running out.

Theoretical Principles

Advanced Reordering uses standard statistical techniques (linear regression and cyclical curve fitting) to predict future sales and recommended order quantities. Once a trend line has been established for future sales, the system takes the current inventory holding and moves forward through time, subtracting expected sales and adding expected deliveries.

The prediction period runs from the planned delivery time for the current purchase order (if one exists) to the expected delivery time for the next order, based on the order cycle‑time and the lead time of the delivery method. As sales diminish the inventory holding, if the predicted holding falls below a nominated minimum quantity (including backorders), the system suggests an order quantity that restores inventory back up to at least the minimum and covers expected sales to the end of the prediction period.

Using the 90% confidence interval, the Sales Weighting factor (0–100) lets you shift the forecast within this range to either minimise stock‑outs (50–100) or minimise inventory levels (0–50).