Inventory Forecasting Guide: How to Predict Demand
Can retailers predict demand? Learn how inventory forecasting can help manage stock and what to consider before choosing an inventory forecasting tool.
Having the wrong amount of stock is a huge, expensive problem for retailers.
According to a study by IHL group, inventory mismanagement losses added up to $818 billion globally every year. That breaks down to approximately $580 million in losses per business.
52 percent of that was due to stockouts (not having enough stock to meet customer demand) and the remaining 44% was attributed to overstocks (having more stock than necessary). The impact of this mismanaged inventory is felt much more acutely during and after holidays, or major sale events such as Black Friday.
There are some things – such as pandemics, disrupted supply chains and trade embargoes – that no business can predict. Common inventory mistakes, however, are often preventable.
Inventory Forecasting is the secret to staying on top of demand and making sure your business always has the right amount of stock. In this guide, we’ll explain how it works, highlight the most effective methods and their pros and cons, and help you decide which inventory forecasting method is best for your business.
What is Inventory Forecasting?
Inventory forecasting is the process of predicting future demand for a company's products or goods. The process involves analyzing historical data, market trends, and other relevant factors to estimate the quantity of inventory needed to meet customer demand while minimizing excess or stockouts.
Retail is unpredictable and there are a lot of factors that are in constant flux.
It is, however, possible to make informed predictions about the amount of inventory needed, by considering expert opinions, information, and available data.
The goal? To make sure that your business has enough products to fulfill customer orders, without tying up too much cash in unnecessary inventory.
Can Inventory Forecasting Really Predict Demand?
Of course, no one can predict the future with complete accuracy. Forecasting always involves a certain amount of guesswork and can never be 100% guaranteed. There will always be things that come out of the blue (such as the sudden spike in demand for comfy sweatpants and home office equipment that happened in the spring of 2020.)
It is, however, possible to make a relatively accurate “educated guess” by bringing together data from multiple sources. The more data you have, the more accurate the prediction will be.
These data sources might include:
Current inventory levels
Outstanding purchase orders
Historical trendlines
Expected seasonal demand
External factors like supply chain issues and weather events
Sales trends and velocity
Historical daily inventory
Historical daily sales
And more.
If you’re basing your business decisions on multiple factors in an integrated and analytical way – you’ll have an advantage over businesses that are merely guessing.
Predictive Analytics: How It Works
Predictive analysis is a data analysis technique that uses historical and current data to assess why people buy products and predict future demand.
Here’s how Predictive Analytics works:
Pool your past sales, inventory and channel data, as well as your expected inventory from open purchase orders and internal transfers.
Then, analyze all the data and calculate daily sales in correlation with stock levels and inventory movements on those days. You can identify patterns, seasonal trends and sales trajectories in order to create an accurate prediction of future demand.
Based on this analysis, project the optimal inventory levels and future reorder points.
Add business-driven adjustments to the calculated data. This could include external factors known by the business owner that might influence reorder suggestions and forecasted demand. For example, you can adjust vendor pricing and prediction periods, add in upcoming promotions or price changes and other factors that will result in insights customized to the unique goals of your business.
One of the distinguishing factors of predictive analytics is that it doesn’t just reveal what will happen, but it also offers some insight into why it will happen. This gives business owners a deeper understanding of the retail landscape and provides them with more control and confidence over their decisions.
What Problems Does Inventory Forecasting Solve for Businesses?
When done properly, inventory forecasting can solve a lot of problems for your business, such as:
Preventing Stockouts
If you have customer demand, yet not enough inventory to fulfill it – you’re missing out on sales. For example, let’s say you’re selling a limited edition portable bluetooth speaker at a discount for a special Black Friday offer. You take a rough guess at what you’ll need, and you stock 100 speakers, each selling for $25. But your Black Friday sale attracts more interest than you expected, and before you have time to restock there are 150 orders that you can’t fulfill because you’ve already sold out.
If you had used inventory forecasting methods to predict the required level of goods and stocked up in advance, you could have sold 50 more speakers. That’s a total of $1,250 revenue you’ve missed out on. Additionally, and perhaps more importantly, routine sales are affected. Without proper software for demand forecasting and optimal reorder points, you’ll consistently face problems with stockouts.
This can add up to huge losses over time. For example, imagine you were out of stock for 50 days out of the year on your best-selling wireless headphones that sell for $19.99 each. If you’d normally sell 40 units per day, you’d be losing $39,980 in revenue on just that one product alone.
Reducing Overstocks
On the other hand, having too much stock can also be costly. Products with expiry dates, such as food or cosmetics, will be wasted and must be thrown away if they are not sold. The same is true for items that become obsolete or irrelevant, such as electronics or commemorative items for an event that has already passed.
Overstocks also lead to an increase in holding costs, which are the expenses associated with storing large amounts of unsold inventory in your warehouse. You’ll need to pay for insurance, storage, handling, packing, and shipping. If you are using Fulfilled by Amazon (FBA) or a third party logistics service (3PL), you’ll be charged storage fees based on the volume of space your product takes up in their warehouse every month.
While these seem like small costs, they add up to a significant amount when you’re working with large quantities of inventory.
Decrease Your Risk Of Reputation Damage
Another negative result of incorrect stock levels is disappointed customers. If a customer often discovers that your online store is sold out of a particular item, they won’t keep coming back. Instead, they will look for a different retailer who stocks that item more reliably. If your high-demand items are inconsistently out-of-stock, word will spread and your reputation as a go-to supplier of those items will suffer. When it comes to e-commerce platforms such as Shopify and Amazon, each platform has it’s own unique challenges associated with stockouts.
Amazon's A9 algorithm heavily factors sales velocity into how products are ranked. Stockouts mean no sales, leading to a sharp decline in product rankings. When a product is out of stock on Amazon, potential buyers quickly turn to other sellers or listings. This results in immediate lost sales and gives competitors an edge in gaining market share.
Loss of "Buy Box": Winning the coveted "Buy Box" is crucial for Amazon sellers. Regular stock outs make a seller less reliable in Amazon's eyes, making it harder to win the Buy Box in the future, even if inventory levels are restored. Frequent stockouts can even impact the overall health of a seller’s Amazon account.
Shopify brings slightly different challenges. Unlike Amazon, where a consumer can easily switch to another third-party seller offering the same product, Shopify stores usually offer unique products or brands. A stockout could lead to immediate lost sales as customers may not find the same item elsewhere on the platform. Shopify sellers often invest heavily in branding. Running out of stock can harm the brand's image and diminish the trust customers place in the brand, especially if pre-orders or backorders are unfulfilled. Stockouts, especially if prolonged, can negatively affect search engine rankings. If a product page is marked as out of stock or removed, it might lose its SEO position, leading to decreased organic traffic.
In addition, many Shopify sellers run targeted ad campaigns. If potential customers click through an ad but find the product out of stock, it results in wasted ad spend and a poor return on investment. While there are many other problems inventory forecasting helps to eliminate, these are the most important ones that will impact your success in the long run.
Glossary: Important Inventory Forecasting Terms
The following are some of the most important terms you’ll come across in the field of inventory forecasting. In other words, the terms you’ll want to be familiar with if you’re thinking of using this kind of tool.
Demand Forecast: A demand forecast is an estimate of the quantity of a product or item that customers are expected to purchase during a specific period. It serves as the foundation for inventory planning and management.
Lead Time: Lead time is the duration between the placement of an order for inventory and the receipt of that inventory. It includes the time required for order processing, manufacturing, transportation, and other factors that influence when the inventory is available for use.
Days of Supply (DOS): This term refers to the number of days your current inventory will last based on forecasted demand.
Forecasted Growth Rate: Your Forecasted Growth Rate is the percentage increase in sales or demand that you expect in the future.
Safety Stock: Safety stock is an extra quantity of inventory held in reserve to protect against variations in demand and lead time. It acts as a buffer to prevent stockouts when demand is higher than expected or lead times are longer than usual.
Reorder Point: The reorder point is the inventory level at which a new order should be placed to replenish stock. It is calculated based on the lead time and the expected demand during that lead time, along with safety stock considerations.
Available Inventory: This term refers to the quantity of stock you have on hand available for immediate use.
Daily Sales Rate: The Daily Sales Rate refers to the average sales volume of an item on a daily basis.
Out-Of-Stock Day: This term refers to a day when the inventory levels have fallen below a minimum threshold.
Types of Inventory Forecasting Methods
There are four main types of inventory forecasting methods that businesses can use to predict future demand and manage their inventory levels. The most common types of inventory forecasting methods are:
1. Quantitative Forecasting: This method involves using statistical models and algorithms to predict future demand based on historical sales and inventory data. In other words, anything you can quantify – such as historic sales data – is used to complete the forecast.
It can be more accurate than other methods but requires a significant amount of data and expertise to implement. (And of course, the more data, the more accurate and comprehensive the predictions will be.) This is the method Goflow uses to make inventory forecasts.
2. Qualitative Forecasting: When you use information that is non-measurable (such as social, economic, and political factors) to predict demand, this is known as Qualitative Forecasting. Since it is largely based on the opinion and judgment of the forecaster, it is seen as speculative and not as accurate as Quantitative Forecasting.
However, it can be very important when there is limited historical data available, such as for new businesses or launches of new products.
3. Trend Forecasting: This method involves using historical sales data to identify trends and patterns in demand over time. It can help businesses to predict future demand based on past performance.
For example, you can observe peak seasons where demand for your products is high, which allows you to stock up beforehand. Of course, there are some trends that cannot be predicted. For example, if a celebrity causes a spike in demand by wearing or mentioning your product.
4. Graphical Forecasting: As the name suggests, this type of forecasting uses graphs and charts to visualize sales data to make it easier to identify and interpret trends. Often being able to “see” the data laid out visually, such as on a line graph, pie chart or histogram, will help you to identify patterns that may not be obvious from the raw data.
These four types of forecasting methods are not exclusive and are often used in combination with each other to achieve the most robust and comprehensive inventory forecasting analysis.
What Are Some Essential Inventory Forecasting Formulas?
When it comes to predicting future demand and making decisions about inventory levels, businesses use certain formulas to make important calculations. Here are some examples of the most crucial inventory forecasting formulas a business might use when employing the Quantitative Forecasting method.
Safety Stock: Safety stock is the amount of inventory that a business keeps on hand to protect against unexpected demand or supply chain disruptions. The formula is: [maximum daily use x maximum lead time] – [average daily use x average lead time].
Purchase Order Cycle Time: Your Purchase Order Cycle Time is the average time it take to ship out an order, from a purchase requisition to a purchase order. A shorter PO Cycle Time means cost saving and improved efficiency. The formula is: [Delivery Date - Order Date / Total Number of Orders Shipped]
Lead Time Demand: Lead time demand is the amount of product you should have on hand after ordering, to be sure you don’t run out before the order arrives. The formula is: [Average Lead Time (the average number of days between ordering the product and getting it to your shelves) x Average Daily Sales.]
Reorder Point Formula: The reorder point is the inventory level at which a business needs to place a new order to avoid stockouts. The formula for this is (lead time x demand rate) + safety stock level.
Average Inventory Formula: This is a calculation of how much inventory you have on-hand over any given time period. It’s important to keep this consistent over time, so you can avoid stock-outs. The formula for this is (beginning inventory + ending inventory) / 2.
Stock to Sales Ratio: Stock to Sales Ratio is the amount of inventory you’re carrying, compared to the number of sales orders being fulfilled. The formula is: [Average stock value/net sales value.]
Inventory Turnover Rate: This formula will calculate how many days it will take to sell the inventory you currently have on hand. A higher ratio means you have strong sales. For this formula, you’ll need to first calculate your “Cost of Goods Sold” (COGS) which is the sum of all the costs of producing goods, including the raw materials. Then, you divide COGS by your average inventory to calculate the Inventory Turnover Ratio.
Pros and Cons of Common Inventory Forecasting Methods
When it comes to making inventory forecasts, there are a number of different methods of how it can be done - from a simple spreadsheet, to outsourcing, to specially-designed software. Let’s look at some of the main inventory forecasting methods and their advantages and disadvantages.
Excel Spreadsheets for Inventory Forecasting
Ad hoc inventory tracking spreadsheets are commonly used by small businesses who haven’t moved to a larger scale software solution yet. In fact, according to a State of Small Business Report that surveyed more than 1,100 U.S. Small Businesses, 21% used an Excel spreadsheet to track their inventory. Here are some of the advantages and disadvantages of using an Excel spreadsheet for inventory forecasting:
Pros:
Cost Effectiveness: Excel (or another alternative such as Google Sheets) is a widely available and affordable tool. It can be used for inventory forecasting without costing the company any additional fees.
Familiarity: Let’s face it – Excel is a familiar tool for a lot of business owners, and you’ve likely used it successfully to track and organize other data in your business. It’s easy to use and there’s information readily available online to help you learn new formulas when you need them.
Customizable & Flexible: Some spreadsheet-loving business owners want to be able to build their own forecasting model, so they can tweak each column and row to suit the specific quirks of their business. Plus, you can use Excel for a range of different forecasting methods, or even incorporate several different types of predictions.
Cons:
Limited Functionality: A spreadsheet can’t do everything. You’ll be limited to the functions and formulas available on Excel and it may not provide the accuracy, functionality, and features of more advanced tools. Also, you won’t be able to sync the data with other software, or benefit from the power of machine learning or AI.
Time Consuming: Sellers will need to input all their updates manually, which can take hours and hours of time. This factor also means that Excel quickly becomes an impractical option when it comes to scaling up with large amounts of data.
Prone to Errors: Manually uploading data also means that human error is a risk. It only takes one small piece of data to be uploaded incorrectly to skew the results and lead to inaccurate forecasts.
Third Party Logistics Providers (3PLs) for Inventory Forecasting
A third-party logistics provider can provide inventory forecasting services, as well as helping you optimize your supply chain and reduce costs. They often provide any number of services associated with the logistics of the supply chain, including warehousing, transportation, picking and packing, order fulfillment and more. Here are some of the pros and cons of choosing this option:
Pros:
Cost Savings: Using a third-party logistics provider can offer you cost savings. By leveraging a 3PL's lower rates for inventory management, transportation, and other tasks, a company can save money and reduce or eliminate expenses like maintaining their own warehouses and fleets of vehicles.
Time Savings: When you delegate the responsibility of managing inventory forecasting to your third-party logistics provider, you’ll free up time and reduce the workload of your employees.
Expertise & Experience: A third-party logistics provider likely has a lot of experience in managing supply chain logistics for a wide variety of companies. So, they will be able to bring this knowledge to the table and offer suggestions based on what they have learned.
Access to Technology: Third-party logistics providers offer advanced systems for managing inventory and shipping routes, which can optimize a company's logistics and save them time and money. By outsourcing to a 3PL, a company can access these technologies without having to invest in them themselves.
Cons:
You’ll Have Less Control: When you outsource your inventory management decisions to a 3PL, you’ll have less control over the shipping process and other aspects of your supply chain. This can be a disadvantage if you value having more control over your operations.
Risk of Choosing the Wrong Provider: Not all third-party logistics providers are equal in their experience and the quality of their service. Choosing the wrong one can result in a lot of unexpected problems that are out of your control.
Potential Communication Issues: When you choose a 3PL company to take on your logistics responsibilities, you’re not just giving up control. You’re also creating one more step between yourself and those who are moving your products and materials along the supply chain. That means you’ll always have a middleman to deal with, which can sometimes make inventory management more challenging.
Inventory Forecasting Software
Inventory forecasting software can be a valuable tool for businesses, as it is designed to make these predictions accurately, quickly, and easily. However, there are also some potential drawbacks to consider. Here are some pros and cons of using inventory forecasting software:
Pros:
Greater Accuracy: Inventory forecasting software can analyze large and diverse data sets to identify patterns and trends that may not be visible to human analysts, leading to more accurate predictions. When you are relying on gut feelings, intuition, experience, or manual calculations, this can be inconsistent and can involve a lot of guesswork.
Faster and Easier Processes: Inventory forecasting software can automate and streamline the forecasting process, generating forecasts for multiple products, locations, and time periods with visualizations and recommendations. This eliminates the need for unruly, time-consuming, and difficult-to-update spreadsheets. The data is updated to the software automatically, which eliminates the risk of human error. Plus, you’ll also avoid manually filling out PO templates or forms and sending them to suppliers via email or fax.
More Flexibility and Scalability: Inventory forecasting software can handle complex and dynamic scenarios, such as new product launches or market shifts, while scaling the data volume up or down. Inventory forecasting software lets you be proactive, rather than only ordering stock when levels are already low. You can predict shortages and prevent them from happening, while growing your business strategically.
Integration with Other Systems and Platforms: Older methods often lacked seamless integration with other systems, meaning business owners would manually input data from sales platforms, CRM, and other tools. Inventory forecasting software can integrate with other systems and platforms, such as accounting software, to provide a more comprehensive view of inventory management. If you sell on multiple platforms (such as Amazon, eBay and their own websites), it’s also possible to consolidate sales data across channels, helping to support better inventory decisions.
Cons:
It Takes Time for the Data to Accumulate: The more historical data the inventory forecasting software gathers over time, the better it will perform. But of course, it takes time for this data to accumulate.
Integration is Important: In order for the forecast to be as accurate as possible, you’ll need to be able to have all your systems, stores and channels integrated.
You’ll Need to Pick a Software that Understands Your Needs: There are many different options when it comes to inventory forecasting software, and it’s worth taking the time to understand which software is the right fit for the needs of your business.
What To Consider When Choosing an Inventory Forecasting Tool for Your Business
When choosing the best inventory forecasting method for your business needs, ask yourself these important questions:
How Much Historical Data Do You Have?
Look at the relevance and availability of your historical data. Do you have enough data to use to inform the forecast? You want to be able to consider the larger context of the forecast, considering the product life cycle, market trends and any seasonal events that might impact demand. An established company will be able to start with historic data and take more of a quantitative approach, while a newer company will need to start with qualitative market information until they can gather their own data.
How Much Time Can You Spend on Forecasting?
Be honest about the amount of time you have for making these calculations — as forecasting can be very time consuming. If you are using the spreadsheet method, you (or someone on your team) will need to take the time to input the data manually. If you don’t have time for this tedious manual inventory planning process, you might want to consider choosing inventory forecasting software that automates that step for you.
Who Will Be Using the Inventory Management System?
Another factor to consider is the vendors who will be using the system and how much training and assistance they will need. By choosing an inventory management system that is easy to use and understand, you can make the onboarding process a lot easier.
Do You Need the System to Integrate with Multiple Channels?
Do you want the system you choose to be able to easily integrate with your POS systems, back-office financial systems and ecommerce software? If so, you’ll likely need to choose robust inventory forecasting software with an open API to support this ease of integration.
Inventory Forecasting Best Practices
Here are some of the most important forecasting best practices that will help to improve the accuracy of your predictions and deliver higher quality results:
Dedicate a Team to Inventory Planning: Build a team you can count on to develop the forecast. Involve key stakeholders from across the business in the forecasting process to ensure that everyone has a clear understanding of the data and assumptions used in the forecast. Make sure these team members have time to dedicate to reviewing inventory levels and adjusting forecasts as needed.
Your Forecasts Are Only as Good as Your Data: Make sure your data is accurate and covers as much of your sales history as possible. Six months is a good starting place, but a year or two of data can give you better insight into monthly demand and seasonal fluctuations.
Always Have Safety Stock: When you have safety stock, this provides you with a buffer to protect you in the face of unexpected situations – such as delays in shipments, damaged or stolen products or an unexpected order influx.
By following these best practices, you can optimize your inventory levels, reduce costs, and improve customer satisfaction.
Set Forecasting Boundaries: Even though there are a lot of unpredictable factors, there are certain logical boundaries you can set most of the time when it comes to forecasting demand. For example, it is highly unlikely that any product will push out all the competition and sell more than the average units sold in the entire product category. So, you can therefore put a logical boundary on your predictions.
Communicate With Your Marketing Team: Make sure you’re aligned with your marketing team when you put together your forecast. You may need to carry extra stock if they are planning a promotion, a special offer or an advertising campaign.
Conclusion & Key Takeaways
Demand for any product is influenced by several factors, including seasonal fluctuations, market trends, sales, and other events.
Finding the right balance between having just enough, but not too much, inventory can mean the difference between earning a profit and losing revenue.
Although inventory can fluctuate in an unpredictable way, that doesn’t mean you have to always scramble to guess what will happen next, or manually keep track of various data channels.
Forecasting demand involves using various formulas to determine how much stock you need and at what intervals you should order it.
Inventory forecasting can be qualitative (based on observations and expertise), quantitative (based on data points) or a combination of both.
There are several ways to make these predictions, including using spreadsheets, outsourcing it to a third-party logistics provider or using inventory forecasting software.
Goflow’s Inventory Forecasting Software, designed specifically for e-commerce businesses, has a suite of features that seamlessly integrates real-time data, predictive analytics, and user inputs. The optimal forecasting means that your inventory levels will always be synced with market and customer demand, without having to manually update multiple spreadsheets.