As a retail business owner, you need to know how much inventory you need to carry to meet your customer needs. When you are worried about getting out of stock, the easiest way you can do is reorder. But, can you sell your goods quickly?
Inventory shortages slow down the order fulfillment process which ultimately leads to customer disappointment. However, excessive stock can cause other problems such as waste, damage, value reduction, and so on. This is why you need to forecast your inventory needs.
What is demand forecasting?
Demand forecasting is the practice of predicting which and how many items customers will buy for a certain period of time. This is usually done using historical data and external analysis (such as holidays, consumer trends, etc.).
Forecasting inventory needs can help you figure out when you need to order new products and how many you have to buy. When forecasting, you need to consider the lead time needed to determine your reorder point.
What is lead time?
Lead time is the time it takes from the first time you place an order with your supplier to the time it arrives. In other words, it is the time it takes for new items to arrive.
Most suppliers provide estimated lead times. But, it is best to use your own data to accurately calculate your lead time.
What is reorder point?
Reorder point is the inventory level that requires you to immediately replenish stock. Simply put, it is the minimum quantity of an item that you have, so when a stock drops to this level, you have to reorder the item immediately.
Related article: 6 Efficient Ways to Prevent Inventory Shrinkage in Retail
How to forecast inventory needs
According to Carlos Castelán, managing director of The Navio Group, a retail consulting firm that has worked with Whole Foods, CVS and Kraft Heinz, forecasting inventory needs is one of the most difficult analyzes to get right, because you must ensure that you don’t forecast too little, but not too much either.
The following are some methods that you can use to forecast your inventory needs:
Qualitative forecasting is a forecasting method that relies on expert judgment instead of numerical analysis. Unlike a quantitative method that counts on historical data, qualitative forecasting depends on the knowledge of highly experienced staff and consultants, taking into account various factors that will affect future demand.
Time series analysis
This method is similar to the quantitative method because it requires historical data to analyze trends. You must use an analytical approach, examining sales channels, suppliers and demands, to accurately forecast inventory needs.
The causal model is the most sophisticated and complex forecasting method, because it uses specific information related to relationships between variables that affect demand in the market, such as competitors, economic strength, and other socioeconomic factors.
For example, if you sell jackets, then you can see factors such as your historical sales data, marketing budget, promotional activities, any new jacket stores in your area, the price of your competitors, weather, overall demand for jackets in your area, and so on.
Simulation forecasting is an approach that combines all methods, both qualitative and quantitative, to provide more holistic insights. However, it is also the most complicated forecasting technique to do, because it requires you to consider internal and external factors.
The following are some tips for better demand forecasting:
Prepare comprehensive data
Without data, it will be very difficult for you to make accurate forecasts and decisions, because you don’t have critical information required for forecasting. Therefore, make sure you can easily see complete historical data; weekly, monthly and yearly.
Understand customer shopping habits
To effectively forecast inventory needs, you must be able to understand your customers’ buying behavior patterns. Here are some questions that you should be able to answer:
- Are my customers seasonal or consistent buyers?
Which products are most popular among customers?
What kind of products consumers love right now?
Where do most of my customers come from?
How fast do trends affect customer demands?
Implement an automated solution
Human error is the main cause of data inaccuracies. When the data is inaccurate, then your demand forecasting goes wrong as well. So, consider automating your manual work.
Use an inventory management system that can alert you when your inventory is running low, produce complete analytical reports, and allow integration with the purchase, accounting, POS, and your other systems.