Have you ever wondered how businesses avoid buying too much or not enough inventory? I have, and my curiosity was enough to make me look into how businesses use inventory forecasting to predict demand without incurring the costs of unsold products.
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Typically, when I’m thinking about something, you can find me Googling it in the middle of the night. As it turns out, there’s a whole industry behind predicting inventory needs. It involves carefully studying past trends, customer data, and other factors to help business owners make the best decisions when purchasing and storing stock.
Instead of spending the rest of the night searching for answers, I went straight to a reliable source. Recently, I sat down with Mark Zalzal, a senior data analyst, to better understand how to forecast inventory. Here’s what I learned.
Table of Contents
- What Is Inventory Forecasting?
- The Benefits of Inventory Forecasting
- Inventory Forecasting Formula
- What I Learned About Inventory Forecasting Methods
What Is Inventory Forecasting?
Inventory forecasting uses data and analytics to predict trends in inventory movement. Although it goes hand in hand, inventory forecasting isn’t exactly sales forecasting, and it isn’t meant to give sales projections.
Instead, it’s used to help companies better plan their inventory management strategy based on historical trends and data, like how much product they should have on their shelves at any given time.
I asked Zalzal for his insights into inventory forecasting, and he told me that it plays a huge role in demand planning.
“You need to know how much you’re going to sell in the next couple of months,” he said. “Then you can go back down and look at your inventory and understand what you’re going to sell and how much inventory you need to make sure to fulfill those sales.”
How Businesses Can Use Inventory Forecasting
Trust me, your company doesn’t want to be known as a brand that can’t keep products in stock. When inventory levels drop, you risk losing loyal customers to other brands that have better inventory management.
One reason your company might struggle with low inventory is vendor delivery times. 72% of small and medium-sized businesses struggle with inconsistent delivery times, especially if they’re sourcing their inventory from vendors overseas. Inventory forecasting can help reduce this problem by giving businesses a better understanding of when they should re-order their products to stay ahead of product demand.
Zalzal told me demand planning and inventory forecasting are also especially important for companies that sell products with expiration dates. You don’t want to purchase an overabundance of a product with an expiration date only to have it expire while sitting on your warehouse shelves — talk about a loss in profit margins.
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AI and Inventory Forecasting
I know enough about AI to know that it can be incorporated into nearly every aspect of business operations. And, as it turns out, AI is convenient for inventory management and forecasting, too.
According to Mark, using AI when forecasting can help companies make better, more accurate predictions. The better your predictions are, the better your inventory management will be. Mark mentioned that you can do inventory forecasting manually using tools like Excel. However, your margin of error will likely be higher, which could lead to unexpected surprises later.
AI uses machine learning to make predictions based on historical data. However, unlike Excel, machine learning can make predictions based on variables that might not be included in the historical data.
For example, let’s say your company sells live Christmas trees, and you know that demand will increase in mid-November. Theoretically, you can use your past data to help you understand how many trees you should order and when. But if you use an AI model, you can factor in other variables, like the weather, to better understand when you should place your order to avoid transportation delays within the supply chain.
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The Drawback of AI Inventory Forecasting
Although AI inventory forecasting can help you make better, more informed decisions for inventory management, there is still a significant drawback. Only 23% of small and medium-sized businesses use AI in their forecasting efforts. Most companies say they are concerned about data security and integrity.
Since Mark is a data scientist and a big fan of AI, I asked him for his thoughts on this. Zalzal confirmed that security breaches are a big concern for companies since most businesses work with private and sensitive data. AI tools work by storing massive amounts of data in warehouses. However, if those warehouses are hacked, sensitive data can become public information.
Although this is a concern, Zalzal said there are things you can do as a company to ensure your data is protected. He mentioned there are certifications you should look out for, like certification of SCO2 compliance, and that AI software companies must undergo compliance audits similar to audits in the financial industry. These cybersecurity audits ensure AI companies meet federal regulations to protect and manage your data.
The Benefits of Inventory Forecasting
There are plenty of benefits from inventory forecasting, whether you use an Excel spreadsheet or an AI tool. Let’s take a look at them.
1. Improves Accuracy
One of the biggest benefits of inventory forecasting is improving order accuracy. With forecasting, you get a better idea of how much inventory you should purchase, when you should buy it, and how much time you’ll need to move your product. The more accurate your predictions are, the less likely you’ll lose revenue.
Zalzal had some thoughts to add to this.“If you can predict accurately what you‘re going to sell by item and take everything into account, like your marketing efforts and your seasonality, and actions that the company does, that’s definitely going to translate to better inventory management,” he explained.
2. Reduces Over or Understocking
As Zalzal told me, “The more accurate the models are, the better you‘re going to stock up and the less waste you’re going to have.”
When your predictions are more accurate, you can purchase only the necessary items. This means you’re reducing the risk of having too much or too little inventory and maintaining only the optimal stock levels.
3. Increases Customer Satisfaction
I know I’m not the only one who gets a little disappointed when my favorite company is out of stock of something I want to buy. When this happens, I usually go to Google to find a brand with the item in stock.
Don’t let low stock cause you to lose customers. Inventory forecasting can help you maintain your stock levels, keeping your loyal customers happy and satisfied with your product selection.
4. Saves Costs
It helps to know when certain products might become popular and how quickly you’ll sell through your stock. By purchasing the appropriate amount of inventory — no more than what you need — you can reduce the amount of money you’ll pay in storage and holding costs and stretch your budget just a bit farther.
Plus, the longer your products sit on the warehouse shelves, the more money you’ll lose. With an estimated 8% of surplus stock worldwide going to waste, businesses lose $163 billion in inventory each year.
Inventory forecasting can help save your business money and reduce error margins.
5. Supports Demand Forecasting
As Zalzal told me, inventory forecasting is the foundation for demand forecasting. When you factor in supply, demand, other variables, and historical data and trends, you can make educated predictions about future sales and how quickly your inventory will dwindle.
6. Boosts Efficiency
As a small business owner, I’m bad about putting off tasks that need to be done as soon as possible. Thank goodness I don’t have inventory to manage, or I’d always be behind. If I did manage inventory, though, I would purchase a subscription to a forecasting tool to help increase my efficiency.
In fact, an increase in efficiency is why 51% of businesses opt to use inventory management software. Business owners who use inventory management tools can better manage their orders. Using these tools, you can get a good idea of when to order or move products, helping you stay more efficient, organized, and on top of product demand.
7. Improves Financial Planning
As Zalzal and I chatted, I learned there’s one more major benefit to inventory forecasting: better financial planning.
As a business owner, you need to ensure you have enough funds allocated to inventory management in your yearly budget. Looking at past historical data and pairing it with machine learning can help you make better predictions for your budgets in the next year.
“Financial planning becomes much simpler,” he added. “In retrospect, over the last year, it‘s easy to find the mistakes. It’s easy to say where we overspent and where we underspend. But when you want to look ahead into the future, you need a very accurate forecast. A good forecast allows you to put yourself one year in advance, look back at the year, and ask, ‘What could I have done here to save and optimize our financials?’”
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Inventory Forecasting Formula
To do inventory forecasting, you will need some data, like lead time demand and safety stock. Lead time demand refers to the amount of inventory required to meet your demand during the time it takes for a supply order to arrive from your vendor after you place the order. You can average the lead time using this formula:
Safety stock describes the extra inventory you need to prevent a stockout. You can find your average safety stock using this formula:
After you’ve crunched those numbers, it’s time to plug them into the inventory forecasting formula.
Inventory Forecasting Formula Example
I find it helpful to see a formula in action, so let’s plug in some numbers for an example. Let’s pretend I sell water bottles. Once I place my order, it takes 15 days to receive the bottles, and I typically sell five water bottles a day.
Here’s the lead time demand formula using my data:
Lead Time Demand = 5 water bottles/day X 15 days =
75 water bottles
Next, I need to find the number to represent my safety stock. Let’s pretend that on my best day, I sold 15 water bottles, and it only took 7 days for the shipment to get to my storefront. Here’s what the safety stock formula looks like using those numbers:
Safety Stock = [(15 water bottles X 7 days)] - [5 water bottles X 15 days)]
After calculating those numbers, my safety stock value is 30.
Now, I can plug those values into the inventory forecasting formula:
Inventory Forecasting = (75) + (30)= 105
To stay on top of inventory and ensure I don’t run out while waiting on a new shipment, I’ll need 105 water bottles on hand.
What I Learned About Inventory Forecasting Methods
If you’ve ever sat through a statistics class, you know plenty of ways to crunch numbers and visualize data. For example, if you’re a visual learner like me, graphs can help you better understand your trends by visually representing your data.
In inventory forecasting, you can use modeling to understand your data in various ways. It’s helpful to understand there are multiple types of modeling, and they fall under four specific categories. Those four categories are:
- Trend forecasting. This kind of forecasting analyzes historical data to identify demand trends. Typically, it ignores seasonality and doesn’t take irregularities into account. Trend forecasting is great for businesses with stable demand.
- Graphical forecasting. As the name suggests, graphical forecasting creates graphics to help you better understand and visualize trends in your data.
- Qualitative forecasting. If you’re a newer business and don’t have enough data to help make inventory predictions, you can ask your customers. Collecting data through surveys and then analyzing it can help predict inventory needs. Qualitative forecasting isn’t the most accurate, but it can give you an idea.
- Quantitative forecasting. Quantitative forecasting is the most popular inventory forecasting method. It uses historical data to make educated predictions about possible inventory needs.
I think it’s important to use a good mix of each method to make better inventory decisions.
(Looking for a more in-depth course? Check out these lessons on forecasting analytics and sales forecasting.)
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Inventory Forecasting Models
As I chatted with Zalzal, I learned that businesses can use several inventory forecasting models to determine inventory projections. The type of forecasting you do depends on the data you’ve collected.
The good news about inventory forecast modeling is that you can use software like Excel, Google Sheets, or HubSpot’s forecasting software to make sense of your data. You don’t have to do the calculations by hand unless you want to, of course. (I’m a big fan of calculators and software, though. Highly recommend.)
Let’s look at six inventory forecasting models you can use to get a more accurate look at your inventory management.
1. Trend Analysis (Time Series Forecasting)
According to Zalzal, there are three basic inventory forecasting models, and you can calculate them by hand without getting a headache. Those are trend analysis, moving average, and exponential smoothing. I’ll talk more about moving average and exponential smoothing later, but for now, let’s focus on trend analysis.
Trend analysis helps businesses use historical data to identify patterns and trends in their inventory stock. If you’ve been in business for a while, you likely can predict when your products will be popular among your customers based on their purchase history.
For example, if you have data on your past water bottle sales, you might notice an uptick in sales in January when your customers make healthier New Year’s Resolutions. You might also see an increase in sales in late spring when the weather turns warmer.
Using the insights from this data and your lead time numbers, you can plan the appropriate time to purchase your stock to have it on hand when demand increases.
2. Moving Average
The moving average is relatively simple among the inventory forecasting techniques. Zalzal told me: “The Moving average is deterministic, and there's really no room for playing around with it.”
Back in college, I took a statistics class. I’ll be the first to tell you I was confused nearly half the time. However, moving average is a concept I understood because it’s simple addition and division. I can see why Zalzal says it’s deterministic.
The moving average is simply an average of units sold over a set period. This forecasting model is best used for products with a relatively stable demand. For example, let’s pretend your business sells toothpaste. Toothpaste is a product that I hope nearly everyone uses. It’s also a commodity that likely won’t see a spike in demand unless something crazy happens, like panic buying because of a global pandemic.
So, if your business sells 100 tubes of toothpaste in the first month, 120 tubes in the second month, and 110 tubes in the third month, the moving average (found by adding those numbers together and dividing by three) is 110 tubes.
Knowing this number, you can place an inventory order for 110 tubes of toothpaste and sell them each month.
3. Exponential Smoothing
Exponential smoothing is very similar to moving average. It just takes it one step further. You’ll want to run this inventory forecasting method if you notice a slow uptick in the demand for your product.
Let’s go back to the toothpaste example. If you take a quick look at your numbers, it’s clear that 110 toothpaste tubes are enough to maintain your inventory levels. However, you’ve changed your marketing approach and gained loyal customers. So, in the fourth month, you sell 112 tubes. Then, in the fifth month, you sell 116 tubes. And, in the sixth month, you sell 121 tubes of toothpaste.
Do you see the slow uptick in the number of tubes sold? Over time, this increase will affect your inventory supply. Exponential smoothing gives your more recent data a heavier weight to help highlight the more recent demand patterns. This can help you plan your stock order without overbuying.
4. Demand Forecasting Based on Lead Time Demand
Demand forecasting based on lead time demand uses the inventory forecasting formula. You can use this forecasting method to calculate future inventory needs to ensure you have enough stock to last through delivery times.
For a quick refresher, this technique factors in your average demand and the lead time to give you a better idea of the safety stock or the amount of stock you have on hand during the order wait time, ensuring you don’t run out of product.
This is a relatively simple math formula that you can do by hand. Or, if you’re a whiz at spreadsheets, you can set up your sheet to calculate this for you as you enter data.
5. Regression Analysis
Regression analysis, sometimes called causal models, can help you find patterns and trends based on external factors. These factors can include the economy and market conditions, the weather, or your marketing campaigns.
As a business owner, you know there are times when your inventory demand increases and decreases, and it can be challenging to find the “why” behind the change just by looking at your numbers. Predicting your inventory needs based on your recent numbers can be even more difficult. Regression analysis can help you forecast demand based on specific variables.
You can do this by hand. However, it’s much easier to use an inventory forecasting tool. Zalzal told me that when you use AI software for predictions, your numbers will be a bit more accurate because all variables are considered. He said, “Theoretically, if you have all the variables that impact your inventory, then you should precisely be able to predict the outcome of that.”
6. Economic Order Quantity
If you want to minimize costs within your inventory management system and have the perfect number of products in stock, you’ll want to use economic order quantity forecasting, or EOQ.
In my opinion, EOQ best benefits companies that have a consistent stock demand. By consistent demand, I mean that your products predictably move out of the warehouse without sitting on the shelves too long. Examples of these products might be everyday household commodities such as cleaning supplies or hand soap.
EOQ models factor in your demand rate, order, and holding costs to help you optimize your inventory. This is helpful because you can determine the appropriate amount of inventory you have on hand without worrying about being unable to sell it or stockouts.
Optimize Your Business Inventory Forecasting
From chatting with Zalzal, I learned that forecasting in inventory management is crucial for businesses that want to manage their stock effectively. Forecasting helps ensure they have enough product on their shelves to both meet customer demand and minimize inventory costs. Forecasting software can give businesses a quicker answer, reducing human error and maximizing accuracy.
Inventory management isn’t just about staying ahead of product demand. It’s also about reducing costs and building a more efficient supply chain. With the right tools and processes, you can accurately predict inventory demand and effectively eliminate future surprises.
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