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How to Avoid Forecast Error in the Supply Chain

Demand forecasting is an intricate science with many moving parts, and it can be challenging to get right, especially if you’re just getting started. With ecommerce continuing to grow, creating a similar shopping experience across channels creates a level of demand from customers that can be very challenging to plan for.  However, forecast errors in your supply chain can be devastating to your business’s productivity and bottom line, so you must avoid mistakes as much as possible. 

With the proper planning processes in place, it is possible to achieve demand forecast accuracy and enjoy the benefits of demand planning without the risk. This article will discuss how demand forecasting errors affect your business and where they originate. 

What Is Forecast Error?

Forecast error occurs when there is a difference between the forecast demand and the actual demand. This can involve various calculations, but in general, the more significant the difference between these two factors, the greater the impact on your bottom line and the greater the risks will be. Dangers of forecast error include: 

Forecast accuracy determines all kinds of factors about how you run your business. It helps you decide what to buy and when to buy it. It also tells you what to stock and where to do so. It could even determine how you hire personnel and where you allocate your resources. In the end, forecast accuracy determines whether you can meet your customers’ needs. 

Three Sources of Forecast Error

No. 1: Data Problems

If your data is incorrect, your forecasts will be inaccurate as well. Organizing, acquiring, and checking data is a significant source of delay in implementing forecasting software because so many businesses neglect data until forecasting brings data issues to light. Therefore, keeping up with and mastering your supply chain data is critical to accurately forecasting your inventory demand and ensuring proper inventory levels

Data anomalies are also something to keep in mind. Even if your forecasting data is up to date and perfect, inaccurate or inconsistent data can easily drive forecasts off track if you don’t manage your data properly. This is why it is critical to measure forecast error and make error calculations.

No. 2: Wrong Forecasting Method

There are various forecasting methods that businesses use to try and calculate their demand. For example, traditional forecasting techniques are referred to as extrapolative methods. These methods attempt to find patterns in an item’s demand history, then project that same pattern into the future. 

Some of these methods include exponential smoothing and moving averages. However, these methods are designed to work on consistent and regular data, not intermittent data. If you try to use them with intermittent data, your results will be inaccurate. Beyond that, with the last two years of shifting purchase and demand behavior, historical data needs to be carefully reviewed to ensure current conditions are met.

Big-ticket and slow-moving items usually involve intermittent data that must be calculated another way. In these cases, regression analysis, also known as causal modeling, may be used. These models use data other than an item’s demand history to forecast demand. However, they require more skill to use. 

Picking the correct forecasting method for your products is crucial to getting the right results. So know your product, know your business, and you will know which model to choose. 

No. 3: Flaws in the Forecasting Process

While organizations may think they are working together, different people will have different priorities depending on their departments. Or, the mistake may be evaluating the forecasts incorrectly. If time isn’t taken to assess each forecast properly, collaboratively, the business is risking error in its estimates. 

There are many phases in a forecasting process, and things can go wrong. There is a team component to forecasting, and this is where the process may get messy. Sales and Operations Planning is often where the collaborative aspect comes into play. 

During these meetings, different departments come together to determine what the official forecast will be for the company. This enables more effective and collaborative communication to occur, so that all departments are aligned on goals and strategies.  This helps improve forecast accuracy, adding to better inventory management and ultimately increased customer satisfaction.  

Reduce Errors in Your Demand Forecasting

You don’t have to handle your demand forecasting all on your own. Blue Ridge Global offers a tool that can help you with forecasting at all steps of the supply chain to ensure that you can confidently predict your business’s needs and deliver your customers’ satisfaction. Our smart software incorporates your data and can help you identify risks, optimize planning, and even improve pricing. Try out Blue Ridge Global software for yourself and see what we can do.