It’s possible for your business to never run low on inventory if you can accurately anticipate its future demand. It’s a key part of inventory management: Recognizing when you’ll need more or less of a product based on sales data, seasonal popularity, market shifts, or burgeoning trends. The process of predicting future demand is known as inventory forecasting, and it’s vital to your overall stock management.
Inventory forecasting is a proven way to meet customer demand and can be the difference between maximizing profits or turning away customers because of insufficient stock. Here’s what you need to know about inventory forecasting.
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What is inventory forecasting?
Inventory forecasting, or demand forecasting, is the process of analyzing historical sales data and other data points to predict your business’s future sales. The goal is to have the correct number of products on hand to meet customer demand, while at the same time avoiding overpaying for unnecessary stock that will slow your cash flow.
Businesses, including ecommerce retailers, face dynamic conditions such as new competitors and fluctuating supply costs. Accurate inventory forecasting can help you avoid having too much or too little stock, both of which can hurt your bottom line.
Why is inventory forecasting important for businesses?
There are several benefits to inventory forecasting, and doing it properly can make the difference between meeting demand or losing sales. Here are some ways accurate inventory forecasting can help your business:
- Minimize product waste. Inventory forecasting pinpoints when demand for certain products will increase or decrease, reducing the chance you’ll have to throw out old, unsold products.
- Increase savings. Every unnecessary product costs money to store. By ordering the right products in the right quantity at the right time, you reduce the costs incurred by overstocking low-demand inventory.
- Improve customer satisfaction. If you’ve ever tried to buy a shirt only to find that it wasn’t available in your size, then you know the value of having popular products on hand when your customers want them.
- Reduce stockouts. Any time you have a popular item out of stock, known as a stockout, you are losing revenue. Predicting future demand and understanding when to restock reduces the likelihood of running out of a product when demand is at its highest.
4 types of inventory forecasting
There are several approaches you can take to forecast how much inventory you should have on hand. Explore the following four types of inventory forecasting:
1. Trend forecasting
This method involves predicting trends based on how a product’s demand has historically fluctuated. Basically, you’re using historical sales data and performing a market analysis to project future customer demand. Only use trend forecasting if you have enough sales data—two years’ worth of data or more—to conduct a thorough analysis and produce accurate predictions.
There are two types of trend forecasting:
- Long-term forecasting. Also referred to as macro trends, this method analyzes broad indicators like societal or cultural shifts that affect your customer’s buying habits while excluding the seasonal impact and unsubstantiated irregularities (an event that can not be traced to a specific cause).
- Short-term forecasting. Also referred to as seasonal forecasting, this method looks at specific times of the year to forecast for the next six months.
Use your available data to decide if you should choose long- or short-term forecasting. If your data reveals that your products are susceptible to broader cultural shifts—like the push for organic products influencing the packaged snack industry—then long-term forecasting would serve you better. If demand for your products fluctuates because of the time of the year—like demand for pool floats peaking in the summer—consider leaning more heavily on short-term forecasting.
2. Graphical forecasting
This method requires you to graph historical data to identify market trends and sales patterns. Visually depicting your data can be useful to unearth in-depth insights and ensure that you don’t miss something in the numbers.
You would use the same data as trend forecasting—the only difference is you represent it visually. Choose this forecasting type if you prefer to visually discern patterns rather than review numbers as line items.
3. Qualitative forecasting
If your business lacks sufficient historical data for trend forecasting, qualitative forecasting can provide actionable insights. Instead of looking at historical sales data, use focus groups, surveys, and market research to create forecasting models to predict future demand.
This is a strong choice for businesses in their first few years or those who have shifted their business model or product offerings. You can also use qualitative forecasting to supplement graphical and/or trend forecasting.
4. Quantitative forecasting
This method builds forecasts based on numerical data. Ultimately, the more numerical data available, the more accurate a forecast will be. There are a couple of popular types of quantitative inventory forecasting:
- Time-series forecasting. This organizes data points based on the time of the year to predict future seasonal trends. Time series forecasting techniques involve moving averages, exponential smoothing, and other mathematical models to identify patterns and make predictions.
- Demand-driven forecasting. This approach uses real-time demand data captured through point-of-sale (POS) features or similar tech to generate accurate forecasts.
How to calculate an inventory forecast
- Measure sales trends
- Calculate lead time demand
- Calculate your safety stock
- Set concrete reorder points
To calculate inventory forecasting, you’ll need to determine your safety stock, reorder points, and lead time demand. There are multiple steps to this process:
1. Measure sales trends
A sales trend indicates a pattern in increases or decreases in sales over time. You can analyze this data in the micro (one product over a short period, like a few weeks) or the macro (a range of products over a more extended period, like a quarter) to get insight into buying patterns. The common forecasting timeframes are 30 days, 90 days, or 12 months.
To move on to the next step, start by finding your average daily sales over the past year:
Total number of sales last year / 365 = average daily sales
2. Calculate lead time demand
Lead time is the time it takes for a supplier to fulfill an order. Lead time demand is the number of products you want to have on hand to avoid running out before your next order comes in. The formula to calculate lead time demand is:
Average lead time in days x average daily sales = lead time demand
So, for example, if it takes a water bottle company 10 days to get a new order in and the company has average daily sales of five water bottles, it wants to have 50 water bottles on hand to be able to complete expected customer orders.
3. Calculate your safety stock
Safety stock is the extra inventory required to mitigate the risk of stockout. You need the right quantity, as too much will increase your holding costs and too little will negate its purpose. The formula for calculating safety stock is:
Maximum daily sales x maximum lead time in days – lead time demand = safety stock
For example, if our hypothetical water bottle company sold at most 10 water bottles in one day last year and it took a maximum of 15 days to get a new shipment in, their safety stock would be 100 water bottles (10 x 15 – 50 = 100).
4. Set concrete reorder points
A reorder point is the inventory level at which you need to reorder more of a product. The formula for calculating a reordering point is:
Lead time demand + safety stock = reorder point
If the water bottle company has a lead time demand of 50 water bottles and a safety stock of 100, they’d want to reorder when their inventory reaches 150 water bottles.
Take the guesswork out of restocks
Only Shopify helps you make smarter inventory purchasing decisions. See your most profitable and popular items, forecast demand, get low-stock alerts, and create purchase orders without leaving your POS system.
4 best practices for inventory forecasting
Use these best practices to forecast your inventory and potentially reduce holding costs:
- Use comparable time periods. You want to compare apples to apples when using sales data for inventory forecasts. For example, if you’re forecasting sales for the second quarter of this year and your business sold 500 units during the second quarter last year, use 500 units as the base for your forecasting model.
- Review trends and marketing variables. Consider if a trend or marketing initiative, like a promotion, affected demand and factor in these trends and variables into your inventory forecasting. For example, if a marketing initiative ran one year but is not scheduled to run again, then your sales might be lower, even if every other variable remains the same.
- Review all future marketing activities. Align with your marketing team as you put together your inventory forecast. Consider whether you need to carry extra stock to coincide with a promotion or advertising campaign.
- Continuously adjust. Forecasting is based on assumptions. As real-life events happen and sales accumulate, adjust your original forecasting parameters (such as time of year, sales data, and lead-time demand) accordingly.
Shopify’s POS features include delivering accurate and automated inventory forecasting. Business owners can forecast customer demand with inventory reports, which track quantities and percentage of inventory sold per day, and retail sales reports, which provide information about point-of-sale orders.
Inventory forecasting FAQ
What role does technology play in inventory forecasting?
How do you choose the right forecasting method for your business?
Start by considering how much available data you have. If you have an established company that’s been collecting data for several years, you could produce accurate forecasts with a quantitative approach. Qualitative forecasting would be more appropriate for newer businesses with less data to work with. Consider using a combination of both approaches to produce more informed forecasts.
Can inventory forecasting be automated?
Yes, automation is possible, so you can forecast more accurately and ensure that forecasting is part of your regular inventory management.
What factors affect inventory forecasting accuracy?
Financial or economic factors, supply chain issues, lead time, and product type (perishable or non-perishable items, for instance) can all impact inventory forecasting accuracy.
How can you evaluate the accuracy of your inventory forecasts?
Choose the forecasts you want to measure. Next, measure the actual demand from that same period and compare them to your forecasts. Essentially, measure a product’s sales against what you predicted its demand would be.
How often should you update your inventory forecasts?
Update your inventory forecasts quarterly or when events—such as a busy season or a marketing initiative—require you to adjust your initial predictions.