Inventory forecasting is crucial for successful inventory management in warehouses and retail businesses. Even e-commerce vendors rely on it to ensure they have everything they need to keep goods and income flowing. Effective forecasting requires an understanding of a few key elements and calculations. It’s built on educated guesses, and almost no business can last long without relying on it.
What Is Inventory Forecasting?
“Inventory forecasting” is a common term for those who manage or own e-commerce and similar retail businesses. It can also be applied to services and even software-as-a-service, but, in all uses, it has generally the same meaning. It’s a major part of the process of keeping goods available for customers. This means purchasing just the right amount of stock to avoid shortages and undesirable overstock. This practice relies on careful study of market forces and forecasting strategy to attain the desired results.
What Is the Purpose of Inventory Forecasting?
Without inventory forecasting, retail companies must rely on guesswork that may lead to either shortages or overstock. Too few products on the shelves means money left on the table for shop owners, and too many products can quickly overwhelm storage resources and warehousing solutions. Inventory forecasting helps ensure that you have “just in time” replenishment of goods when stocks start to run low.
Components of Inventory Forecasting
The below universal terms and equations are often used as a major component of “simulation” forecasting, which takes multiple data sets into account to provide a more holistic prediction model. Your own knowledge of your market and the seasonality of your goods are important qualitative factors and additional data of value. These key terms and calculations can go a long way when it comes to setting up your own inventory forecast strategy:
- Sales velocity, which is the rate of your sales without including any out-of-stock days, is measured using the formula (total sales over the past 365 days / number of days without out-of-stock issues) * 30 days. In the case of a store selling 800 items over the course of a year with 200 days of items in stock, the sales velocity would be 120 per month.
- Sales trends, defined as increasing or decreasing sales, can also prove invaluable. These are typically plotted out in a chart that shows the number of units sold on one axis and a monthly account on the other. The trend line is the upswing or downswing of the sales and indicates either increasing or decreasing demand.
- Lead time is the amount of time it takes between placing your order and receiving your shipments. If you place an order on Wednesday and you get your deliveries on Sunday, then your lead time is 4 days.
- Baseline inventory refers to the amount of stock you need to keep available to ensure no shortages during your lead time. Depending on your business and goods, this may also include additional stock as protection against outages.
How to Forecast Inventory Properly
Efficient forecasting requires you to work with these factors in order to, in effect, predict the future as best as the data allows. These strategies often rely on a combination of time-based, qualitative, and causal information. Time-based data indicates past trends that may continue while qualitative data is your understanding of your product, sales, and market. Causal data is comprised of any external factors that may affect logistics, such as the weather, current events, or even local political activity.
Of course, having accurate, detailed, and consistent information is easier when you use a dedicated inventory management app, integrating it with your other tools like accounting software or even your e-commerce platform. The point is to make the data easily accessible so it can inform your forecasting.
Determining Economic Order Quantity (EOQ)
Economic Order Quantity is the ideal number of units you should purchase considering key factors, such as fixed costs, demand in units per year, and carrying costs per unit per year. The current accepted formula for this is the square root of ((2 x Fixed Costs x Units Per Year) / the carrying cost per unit per year). This figure will require careful analysis of your previous year’s sales records to determine the exact value.
Consider Lead Time
Because lead time is a major consideration, you must always factor it in when reordering. As well as your forecasted order, you’ll need to add the average sales volume per day and multiply it by the number of days in your lead time. If you sell 10 widgets per day and have 4 days until your order arrives, you’ll need 40 widgets in stock right now to account for the lead time. If you’re already below that figure, you’ll want to adjust the order amounts to prevent future shortages.
Have Safety Stock Available
The extra inventory on hand between the reorder date and the delivery date is often referred to as “safety stock.” Using your safety stock figures, you can more easily determine if you need to increase or decrease order levels. If you have an overstock situation, you can even figure out how long it is likely going to take you to move the excess using your sales velocity and EOQ. Automated triggers in scanning software and automated shipping can be a big help in keeping this level just right.
Determine a Reorder Point
Ultimately, the calculations and terms used so far serve to help you determine your reorder point, or the quantity that signifies you need to place a new order to avoid any shortages. The formula for this is exceedingly simple. Take your average daily use rate and multiply it by your lead time in days. If this number is less than the stock you have on hand, you should place an order immediately.
Forecasting for New Items
What about when you don’t have historical data? New product releases keep markets vibrant and alive. While you may not have stocked a particular item before, using data from similar items (i.e., those with different flavors, vendors, or styles) can help you fill in the gaps. Just remember that your order forecasts are likely to be less accurate without specific data. Here’s where your qualitative and causal knowledge will really come in handy.
If you’ve had overstock issues in the past, conservative orders of new items can help. The same is true when you forecast big sales for new items. All forecasting comes down to data and experience.