The maximum number of offset days an item can receive.

This ensures that safety stock does not become excessively large if an item is heavily under-forecasted.

A common misconception is that limiting the offset days alone will restrict safety stock calculations. However, the risk percentage also plays a significant role in determining safety stock. These two values are calculated independently.

When using these parameters, assess whether the business tends to over- or under-forecast, and whether excess stock or stockouts would cause greater harm.

Changing these global settings may conceal item-level risk variations that would otherwise highlight where investigation and correction are needed.

➜ Refer to this article for a detailed explanation of Forecast Risk and Offset Explained and this article for a detailed explanation of how the The Recommended Order Quantity (ROQ) Calculation Explained.

Let’s look at Maximum (%), Minimum (%), Maximum Offset, and Minimum Offset collectively.

In simplest terms, Risk Offset Days represent the difference between the “planning” value and the “actual” value that needs to be added or subtracted from the safety stock days value in order to improve accuracy for ordering.

Suppose we have an item with the following:

We know that safety stock, replenishment cycle, and lead time are all converted from days to units using the forecast.

In this example, our Order-Up-To level will be 60 days (RC + SS + LT), translating to 200 units (based on a forecast of 100 units every 30 days).

The app captures historical forecasts and compares those to actual historical sales that occurred.

Suppose that historically we forecasted 100 units a month and sold 200 units.

Historically, we under-forecasted, sold more than expected, and risked stocking out.

The app assumes we may under-forecast again and compensates by adding additional stock to the initial calculated safety stock.

This is known as a positive days offset.

Suppose that historically we forecasted 100 units a month and sold 50 units.

Historically, we over-forecasted, sold less than expected, and risked excess stock.

The app assumes we may over-forecast again and compensates by subtracting stock from the initial calculated safety stock.

This is known as a negative days offset.

The risk percentage indicates the degree of variability in the data — how inconsistent or scattered the data points are.

Suppose historically we forecasted 100 units every month and sold 200 units every month. This consistency makes it easy for the app to plan, because it’s clear that you under-forecast by 100 units a month.

However, suppose we forecasted 100 units each month and sold anywhere between 110 and 290 units. This means that while you under-forecast by 100 units on average, the large variation makes it hard to plan accurately.

The “risk” of applying an incorrect offset is high, resulting in a higher risk percentage.

A common misconception is that a large risk percentage always results in large risk offset days. This is not necessarily true, as these two values are calculated mostly independently.

Safety Stock is calculated using five key factors:

These factors interact to determine the required safety stock, except for risk offset days, which are applied after the calculation.

It is therefore possible to have:

Limiting Minimum Risk (%), Maximum Risk (%), Minimum Offset (days), and Maximum Offset (days) becomes crucial when the goal is to limit safety stock due to cash flow constraints or capital tied up in inventory.

However, if the business goal is to avoid stock-outs, it may be better not to enforce cutoffs for these parameters.

Take note that changing global settings can obscure item-level nuances that might have been better addressed by investigating the source of high risk.

⚠️ Remember: You can also set cutoffs for safety stock directly in the Configuration settings.