Demand forecasting techniques are an integral part of inventory management. If retailers can measure forecast market demand accurately, they can also ensure that they have the right amount of stock for optimum sales and profit. Businesses can get a correct demand forecasting analysis with the help of demand planning techniques that we will cover in this article.

What is Inventory Demand Forecasting?

Evaluating customer demand for every individual inventory item over a particular period is known as inventory demand forecasting. Correct predictions of inventory demand forecasting enable businesses to stock the right amount of items and avoid occurrences like overstocking or understocking. It provides organizations with optimum control over the inventory. Data patterns of the past and knowledge about fluctuating demands are utilized for forecasting inventory demand.

Significance of Correct Inventory Forecasting

Inventory forecasting can be simple or complicated depending upon business needs. As a rule, the more complex your demand forecasting techniques are, the more precise your conjecture will be. Correct demand prediction permits you to meet customer demand effectively without spending too much on stocks, allowing you to lower the operational costs overall. The cost behind overstocking can also be saved, which requires excess capital for maintaining the stocks unnecessarily. However, without the proper guidance, inventory demand forecasts can be challenging.

Let us start with the fundamental concepts of demand forecasting techniques.

Top Demand Forecasting Techniques

Many demand forecasting techniques are available that businesses can integrate into their model. Forecasting techniques mainly use:

Qualitative forecasting (that uses subjective insights and opinions) and

quantitative forecasting (uses demand data from the past).

Let us take a closer look at the different techniques.

Inventory Forecasting: Demand Types

If you look at the sales data of the past of every product, you will find out that the demand for every product is different, some having high demand consistently and some having low or sporadic demand. Moreover, demand depends on the product life cycle, and it keeps changing as the product enters the market, matures, and finally declines.

Demand type is essential for each product and should be used to identify the kind of algorithm or calculation to be used for demand forecasting. A product with inconsistent demand will have a different equation than a product with slow demand. Figuring out the base demand is the beginning of accurate demand forecasting.

Inventory Demand Patterns

Your inventory items are likely to go through fluctuating demands due to changes in fashion and new developments in technology. Economic, legal, and social factors also influence changes in demand. Products follow the demand trend during the product cycle; the demand will be high during the growth phase and gradually decline.

While predicting your demand forecast, you need to look out for the historical demand data patterns. Referring only to the base trend won’t help if items follow a specific trend.

Seasonal Items Demand Forecasting

Every manufacturer and retailer is aware of the fluctuations due to seasonal factors. The seasonal weather trends, annual customs and traditions, and school holidays have a fluctuating influence on demand. You must understand how these seasonal factors affect your customer’s buying habits and plan your inventory accordingly. It gives you an advantage during the peak season as you can be already prepared to meet the rising demand.

Inventory Demand Forecasting Outliers

Abnormal demand patterns result from everyday actions such as employee strikes, sales promotions, and more or may result from unpredictable circumstances such as natural disasters, out-of-business competitors, etc.

Businesses should inspect their inventory forecasting data to identify outliers as they can almost change the precision of your prediction. Demand data that is unreasonably high or low should be detected, and you should choose whether to include it in the demand forecasting calculations.

Qualitative Data

Although historical demand data provides almost accurate results in inventory planning, you also need to consider the qualitative factors. It includes taking external market factors and future events into account, such as competitor activity and sales promotions. To get the best results, you should also include marketing and sales data in your forecast.

Comprehending Demand Forecasting Correctness

Your demand forecasts most likely will be inaccurate. If you can judge the error percentage in your previous demand forecasting, you can use it in future ones. If you can find out how unresolved a prediction is for a particular business period, you can bring changes to how you plan your inventory management.

You can estimate demand forecasting accuracy or error through formulas like the Mean Absolute Percent Error, which calculates the average percentage of the difference between your predicted demand and the actual demand over a particular period. The Mean Absolute Deviation gives you the deviation of predicted demand from the actual one in units.

Demand Forecasting Reviews

The duration you select for demand forecasting is directly proportional to the correctness of your prediction. For instance, a forecast for the next two weeks is likely to be more accurate than a prediction of the next 12 months.

If there are frequent fluctuations in the demand pattern and the market is volatile, you need to analyze your forecasts regularly compared to slow markets. You should readjust your forecasting schedule if you find over-stocking or under-stocking.

Demand Forecasting Software

Precise demand forecasting is challenging if you want to do it for every item, and it requires insight into correct stock levels in the inventory and sales across multiple channels. Demand forecasting software provides quick and accurate forecasting, however complicated and fluctuating the demand might be. Investing in demand forecasting software allows you to handle more complex demand forecasting needs.

Fountain9 provides you with an AI-powered demand forecasting software that accurately measures the historical data and provides correct prediction requirements to keep stocks ready in case of stockouts and to meet customer requirements efficiently.