All You Need to Know About the Inventory Forecasting

Accurate inventory forecasts are essential, especially when supply chains and consumer demand change rapidly. Forecasting requires a mix of data analysis, industry experience, and customer insights to predict future demand.

This article will discuss the methods and formulas commonly used for inventory forecasting and best practices for your business when you design and carry out this process.

What is Inventory Forecasting?

Demand planning – also known as inventory forecasting- predicts future inventory levels based on historical data, trends, and predictions of upcoming events. Having accurate forecasts ensures businesses have enough products to fulfil customer orders without tying up funds in unnecessary costs.

Importance of Inventory Forecasting

The advantages of accurate forecasting include:

• Minimising sales losses as a result of unavailable products.
• Perishable stock is less likely to spoil before the sale.
• Maximising workforce capacity, i.e., not having too many or few employees.
• Increased profit margins by not oversupplying products.
• By ensuring proper fulfilment flows through warehouses and distribution centres, less strain is placed on storage facilities.

Types of Inventory Forecasting

There are four types of inventory forecasting:

• Trend forecasting: 

Analyse changes in demand over time for your product to predict future trends. A trend forecast is a way to forecast future consumer behaviour based on research and analysis.

• Graphical forecasting: 

By historical graphing data, you can identify patterns and add slopped trend lines to discover possible insights that you may not have noticed otherwise. 

• Qualitative forecasting: 

Analysing numerical data is not qualitative forecasting – it relies on expert judgment. As part of this forecasting technique, highly experienced employees and consultants are consulted to provide insight into future results.

• Quantitative forecasting: 

The quantitative forecasting process uses mathematical calculations to predict future revenues by analysing historical data and patterns. Making informed decisions on strategies and processes to ensure continuous success is possible through forecasting.

Inventory Forecasting Methods and Formulas

Here we glance in additional detail at some of the formulas and methods of research inventory forecasting uses.

The safety stock formula

A business holds safety stock so that it does not run out of merchandise in an emergency or a failure in the supply chain. It ensures that manufacturers and retailers can always supply goods to their customers, maintaining customer satisfaction and maximising profits.

Safety stock = (Maximum daily use x Maximum lead time) – (Average everyday use x Average lead time)

The reorder point formula

You can decide when to replenish your stock by setting a reorder point for your most important SKUs (Stock Keeping Unit) so that you do not have too much or too little of each item.

The reorder point is then calculated by adding the demand lead time to the safety stock:

Reorder point = (Average daily use x Average lead time in days) + Safety stock

The Economic Order Quantity (EOQ) formula

We use the economic order quantity formula to determine the right amount of inventory to order. By doing this, the business minimises the number of times it has to place orders and ensures that excess inventory is not stored – resulting in lower costs.

To calculate the economic order quantity, you will need the following variables: demand rate, setup costs, and holding costs. The formula is:

EOQ =

Time series method

Analysis of time series takes into account patterns of repeating demand as well as long-term trends. Using averages, patterns and other relevant data, this method uses historical information to predict the future. The data can then analyse what future demand will look like.

ABC method

In ABC classification, products are ranked from A to C according to their value to a business. Businesses can prioritise their most important products by identifying their demand, cost, and risk factors.