Improve Forecast Accuracy by Eliminating Error

Identify inventory requirements at their distribution centers and client sites based on forecasted demand. Distributors rely more often than not on historical sales data and an arbitrary sales target for the year.

As an example, if a business wishes to grow 5% in 2022, it would increase the stock of the items it sold in the last year by 5% as well. The forecasting formula is generally the same, though distributors occasionally add seasonality to forecasts. Moreover, salespeople may add their own forecasts based on what they anticipate purchasing in their region. Each year at the same time, distribution companies assume the customer will buy the same quantity of each item.

It is a flawed method, which is well known to those familiar with it. Each is striving to provide their customers with stock levels that are as close to the levels they require as possible. Since distributors must constantly work on reducing forecast errors, they are always searching for ways to improve accuracy. Reducing forecast error makes inventory management strategies easier. In this article, we will take a look at what forecasting error is, what its causes are and how you can improve it. 

How does forecast error work? 

An error in forecasting is a deviation from what is anticipated. This can be caused by a number of factors. There is a direct impact on a distributor's bottom line if actual demand differs from projected demand.

Risk increases as forecast error increases:

• Too much inventory is stocked at the customer's location or in the distribution center, increasing carrying costs
• Customers are more likely to look for alternate sources for critical items when stock levels are low
• In the case of new products with short sales histories, lead times will be longer

What is the importance of forecast accuracy?

Accurate forecasts are important. As well as how and where to stock products, it drives decisions on what to buy and when. In addition, it could influence your hiring decisions or how you allocate your most valuable resources. The service your customers need at the most critical moments may not be available if you lack it. A good inventory system like the Amazon inventory management system can certainly help you improve forecast accuracy for your Amazon inventory.         

Forecast error increases for several reasons. The following 3 are some of them:

Inventory-level contracts between a distributor and a customer.

Several distributors have agreements with customers that stipulate that their inventory level must be met at all times. Despite the fact that they may need up to 15 times more, they are legally required to stock it because they agreed to do so. Forecasts will be distorted as a result. Distributors have to pay 25% to 55% of the cost of inventory annually just to keep it if they are not compensated in any way.

Stocking up on rarely used items as a safety measure.

It is important for customers to keep certain items on hand even if they use them only once or twice a year. In the event that they do not have them in stock when they're needed, a production line or project could stall. Often, customers are not even aware of when the items are out-of-date before they are used by them. Furthermore, if they are bought with the intention of placing them on a shelf, the sales history would be reflected in the forecast. Stocking these for customers shouldn't be a problem, but when making a purchase decision, take previous sales data into account.

Validity of the data.

The relevance of an inventory system's data has a much larger impact on forecast error than the quality of the data. The distributor ignores any shift in a customer's business when listing all items purchased by a customer in the past year to base future inventory purchases. In this case, the items that the customer will order will change accordingly. Thus, the value of a customer's history of sales for forecasting is significantly diminished. 

Here are 4 methods for improving forecast accuracy

Stock levels should be accurately accounted for

Even though demand and sales are often confused, it's important to note that they're not the same thing. Sales represent what is actually sold or is potentially sold as opposed to demand, which is based on market appetite for a business. Among the determining factors for these two is the quantity of inventory on hand. 

It's imperative that stock levels are accurately recorded at any given time. Be sure not to mislead yourself when analyzing historical data with inadequate stock levels to meet full demand. It is the same when analyzing future data. Taking into account how much demand will go unmet is crucial when forecasting an inventory shortage.

Calculate the number of receipt delays

Count not only the inventory that is owned and sellable but also the inventory that is coming into the facility. If stockouts occur, replenishment must be made sooner. Measuring the delay in receiving goods will allow the loss of sales to be quantified. You can include this loss or an amount you will capture later into forecast estimates based on what you intend to capture later.

Understanding seasonality is essential

Understanding your customers' behavior over time is the key to truly understanding them. During a time period, it is normal for demand to fluctuate at regular intervals. This phenomenon is referred to as seasonality. A season can be referred to as a week, a month, a quarter, or simply a season. 

An obvious example can be found in products that keep you warm during the winter and cool during the summer. Additionally, some industries can use it to determine the value of major holidays such as Mother's Day, Valentine's Day, and Christmas. Seasonality should be understood through a detailed understanding of product shifts throughout the year. Determine what constitutes a significant shift by quantifying the variance from the norm.

Analyze your competitors 

Let's examine the external factors to understand how they affect your accuracy now that we've covered the internal factors. Understand competitive performance and changes by working with relevant departments in your business. If you introduce new product categories that are unique and attract new customers, you must take this into consideration. 

You can make a few predictions about your business if you observe what your competitors are doing. First, you need to figure out the revenue potential for your business. Because public companies have to make their information available online, finding information on them should be straightforward. A company's success will depend on a variety of factors, including how they advertise, how much funding they have, and how much TAM (Total addressable market) they have. In addition, you can determine a company's revenue potential.

Your expectations can be adjusted in accordance with the seasonality that the agency sees. Learn what the company's product line consists of and when they introduce new products. In addition to paying attention to what goes on sale, you might also want to pay attention to what goes on sale.

Conclusion

Maintaining credibility is not the only benefit of accurate forecasting. By making a precise prediction, we increase our chances of profit and reduce our exposure to risks. By reducing demand variability, you can improve the accuracy of your forecasts.

The following article discusses how forecasting errors can be reduced and the most common reasons for them. If you need more help with forecasting errors, contact our E-commerce experts at Inventooly. We also provide an Amazon inventory management system, so you can effectively manage your inventory without any hassle.