Why inventory demand forecasting is essential?
Most businesses, at some point, may have encountered a situation when it realizes that it doesn’t have enough inventory to meet consumer demands. There are also cases where businesses are holding too much stock than required. Inventory often accounts for the highest cost involved in running a business. However, most companies are usually in the dark when it comes to the optimal amount of inventory it needs to maintain.
Overstocking often results in capital that is unnecessarily tied up in inventory. On the other hand, businesses could lose thousands of dollars in sales opportunities due to understocking. What becomes apparent is the fact that businesses must maintain the right amount of inventory to keep their customers happy and grow efficiently.
How much stock is “right”?
The obvious question is – How do you know what amount of stock is right for your business? The answer lies in accurate inventory demand forecasting. While demand forecasting sounds simple, it requires companies to invest significant time and efforts to make the predictions dependable. However, it can yield astounding results – both short and long term. Read on to find out how you can make accurate inventory demand forecasts for your business.
How to forecast inventory accurately?
Inventory demand forecasting can be a very complicated and time-consuming task without the right tools and information. Here are a few steps to ensure that your demand forecasting is as accurate as possible.
Maintain accurate inventory records
If your business deals with a large number of products and locations, it can be quite challenging to ensure that you have accurate inventory information. The risk of having incorrect stock information is almost as bad as not having any information at all. A good inventory management software will help your business to achieve an accurate and efficient way of tracking your inventory across multiple warehouses.
Maintain accurate sales and customer data
The most critical data that a business requires for demand forecasting is actual sales history. The historical trends in your sales volume will give you a pretty good idea of the seasonality of your products and the average increase or decrease in demand YoY. These are valuable inputs for statistical models to make accurate predictions for the future. It is equally essential to maintain accurate information regarding your customers if your business is operating in multiple locations. An integrated CRM and order management software can help with recording customer and sales data.
Use an integrated business software
With the growing popularity of SaaS (Software as a Service), several solutions are available today for every business function imaginable. SaaS solutions offer companies a cost-effective way to manage different aspects of their business. Unfortunately, the majority of such solutions are independent pieces of software focusing on a specific business problem – inventory, sales, purchases, etc. They may not offer the possibility of seamless integrating with other applications your business might be using. An integrated business software, on the other hand, provides an efficient way to manage all your core business functions in one place – without the need for complex integrations.
Use the right statistical method
Several statistical approaches are available today for demand forecasting. The ideal demand forecasting method must take into account your sales history and the seasonality of your products or raw materials. However, every statistical model requires historical data as input to produce meaningful projections. If you are a startup, you obviously may have very little or no factual information at your disposal. In such cases, it may be wise to forecast based on your sales targets. With time, your business will have sufficient data to use a more realistic forecasting model. But if your company has been operating for a considerable amount of time, you may already have adequate data to use more advanced forecasting methods. In principle, the statistical model you choose for demand forecasting influences its accuracy. For example, a model that suits a business with a relatively linear demand trend may not be the ideal choice for another company with a seasonal demand pattern.
Conclusion
In conclusion, with the right set of tools and accurate historical data, you can make reliable predictions for your inventory demand. A dependable demand forecasting process will help your business maintain the right amount of stock at all times.
