Mismanagement of inventory is costing $1.75 trillion in lost sales and costs for retailers worldwide annually — and inventory forecasting is one way to tackle the problem.
This article covers the basics of inventory forecasting, including what it is, why it’s important, as well as inventory forecasting methods, useful formulas and examples.
Are you ready to improve your inventory management techniques? Let’s get started!
- What is inventory forecasting?
- Why is inventory forecasting important?
- Common inventory forecasting methods
- Inventory forecasting formulas & examples
- Some last words
What is inventory forecasting?
Inventory forecasting refers to the process of predicting inventory levels for a given time period in the future.
By forecasting inventory accurately, you can get a grasp of the amount of stock needed to fulfill customer orders, avoiding tying up too much cash in inventory at the same time.
Why is inventory forecasting important?
Inventory forecasting is an essential and important aspect of inventory management. If done properly, it can save you the headache of having insufficient inventory to satisfy customer demand.
More importantly, accurate inventory forecasting can help maximize your business’s revenue potential, reduce costs and minimize waste. Here is how.
1. Reduce stockouts
Inaccurate inventory forecasting often leads to stockout situations.
Consumer demand is there, but you don’t have enough inventory to fulfill their needs. It means you can’t capture all of the demand that could have been yours had you predicted and managed inventory properly.
Example: You have 100 tourist t-shirts in hand. Each is sold at $5.
During the holiday season, an influx of foreign travelers led to a surge in demand for your t-shirts. Before you have time to restock from your supplier, a total of 180 visitors want to buy from you.
With only 100 t-shirts to sell, your total revenue is $5 x 100 = $500.
Had you used inventory forecasting methods to predict the required level of goods and stocked up, you could have sold 80 more t-shirts, which represent a total revenue of $5 x 180 = $900.
In this scenario, inventory forecasting could help you capture $900 − 500 = $400 of revenue which you now lose.
2. Reduce holding costs
Holding costs, sometimes known as inventory carrying costs, are the costs incurred while you store unsold inventory in your warehouse.
Examples of holding cost components include insurance, storage, handling (e.g. man hours to perform physical count of inventory), but to name a few.
Although each component of inventory holding costs may appear negligible on your books, they can add up to a significant number — which is why inventory management is often cited as a cost reduction strategy, and inventory forecasting is one way to improve inventory control.
3. Reduce overstocks
Overstocks — the opposite of stockouts — is a culprit of inventory holding costs.
In addition to drawbacks in pecuniary terms, keeping excess inventory may also result in wasted materials in the medium and long term.
For example, overstock of unsold goods could turn into municipal solid waste in the following situations:
- Expired or spoiled products (e.g. food)
- Non-food items with limited shelf lives (e.g. electronics, cosmetics)
- Out-of-fashion goods that can’t sell (e.g. apparel, luxury goods)
→ The takeaway: Inventory forecasting is an important part of inventory management.
Common inventory forecasting methods
Though consumer preferences and demand may change over time, there are some time-tested techniques to help you with inventory planning.
This section discusses four inventory forecasting methods which will help you predict demand effectively and navigate the dynamic business environment.
1. Quantitative forecasting
Quantitative forecasting involves the use of historical data to predict future demand.
For example, analysts would look at sales histories to project inventory levels needed over a given time period in the future. The more data available, the more accurate the estimate will be.
Quantitative forecasting is a data-based mathematical process, making it consistent, unbiased and reliable.
However, it requires analysis of past data and may not be applicable to businesses that don’t have the relevant data at hand.
2. Qualitative forecasting
Qualitative forecasting is the practice of predicting inventory needs based on non-measurable information.
It takes into account social, economic, political and any other factors in the macro environment that might affect consumer demand.
Unlike quantitative forecasting, which makes use of figures and statistics to inform predictions, this inventory forecasting technique is largely based on the opinion and judgment of the forecaster.
Qualitative forecasting is typically used in cases where historical data is unavailable, such as for new businesses or launch of new products.
It can also be used in combination with quantitative forecasting when changes in the external environment (e.g. Brexit, pandemic outbreak) affect future sales demand in a way that past data alone can’t give you a complete picture.
3. Trend forecasting
In trend forecasting, past sales patterns and market growth trends are analyzed to predict future sales performance of your products.
It gives you insights on the timing of ups and downs in your business cycle, helping you improve your inventory and marketing strategy to make the most of your high and low seasons.
Example: Trend forecasting
Your company sells reference books to college students.
Analysis of historical sales patterns shows that revenue is highest right before and during exam periods (e.g. May and November), whereas semester breaks are the off-seasons.
Using trend forecasting, you’ll know when to stock up (before the peak seasons).
You can also use these insights to inform your marketing strategy, such as by setting up promotional campaigns (e.g. back-to-school discounts) during the slow months.
4. Graphical forecasting
Graphical forecasting, as its name indicates, uses graphical representation for data interpretation. It turns numerical data into visual images, helping you read, analyze and interpret data more easily.
When using the graphical forecasting technique to assist inventory planning, here are some forms of graphical representation you can consider:
- Line graph
- Pie chart
→ The takeaway: Inventory forecasting methods can be broadly categorized into four types.
Inventory forecasting formulas & examples
Although inventory forecasting requires human judgment at times, it’s certainly not a game of blind guessing about when you need to re-stock.
This section explains three formulas for inventory forecasting (with examples), so that you can make inventory decisions that are backed by numbers.
1. Lead time demand
Lead time is the number of days between placing an order with your supplier and receiving the goods. In other words, it’s the amount of time you need to re-stock.
The level of demand during this time period is called lead time demand.
Calculating lead time demand lets you know how much inventory you need to have, so that you can avoid stockouts while waiting for new stock. It can be computed with the formula below:
Lead time demand = Average lead time in days x Average daily sales
Below is an example to illustrate how this formula can be applied.
Example: You run a luxury fashion store. Regarding one of the bestselling trench coats, you have the following information:
- Maximum lead time: 20 days
- Minimum lead time: 8 days
- Maximum daily sales: 12 units
- Minimum daily sales: 6 units
Before proceeding to compute the lead time demand, some working drafts must first be done:
- Average lead time = (20 + 8) / 2 = 14 days
- Average daily sales = (12 + 6) / 2 = 9 units
The lead time demand for this trench coat is calculated by:
= 14 x 9
It means you’ll need at least 126 units of this coat in stock during the time you wait for new stock from your supplier.
Otherwise, there’s a risk that you won’t have enough inventory to fulfill customer orders during this period.
2. Safety stock
Safety stock, sometimes known as minimum stock level, is the amount of extra stock that you keep in storage to prepare for demand fluctuations and unexpected circumstances.
Having safety stock minimizes risks of stockout, and helps you determine when to reorder (more on this below).
Safety stock = (Maximum daily sales x Maximum lead time in days) − (Average daily sales x Average lead time in days)
Example: You have the following information on a bracelet sold at your jewelry store.
- Maximum daily sales: 5 units
- Minimum daily sales: 1 unit
- Maximum lead time: 11 days
- Minimum lead time: 7 days
Working drafts for the computation are as follows:
- Average daily sales = (5 + 1) / 2 = 3 units
- Average lead time = (11 + 7) / 2 = 9 days
The safety stock for the bracelet is calculated by:
= (5 x 11) − (3 x 9)
In this scenario, you should always have at least 28 of this bracelet in storage as safety stock.
3. Reorder point
Reorder point (ROP) refers to the specific stock level at which inventory should be replenished.
Once your stock reaches the reorder point or below, it’s time for you to place an order with your supplier.
Reorder point = (Average daily sales x Lead time) + Safety stock
Depending on your business type and consumer behavior, the reorder point can be set with or without safety stock.
Should you decide not to factor in safety stock in your reorder decisions, the formula for calculating reorder point is as follows:
Reorder point = Average daily sales x Lead time
Following is a numerical example which takes into account safety stock in the computation of reorder point.
Example: The information below relates to a cookbook sold at your shop.
- Maximum daily sales: 22 units
- Minimum daily sales: 14 units
- Lead time: 2 days
- Safety stock: 30
Before the reorder point can be computed, you must first work out the average daily sales:
- Average daily sales = (22 + 14) / 2 = 18 units
Therefore, the reorder point for this particular book is:
= (18 x 2) + 30
It means once the stock level for the cookbook hits 66 or less, you’ll have to re-stock.
Pro tip: The reorder point is a numerical representation of consumer demand for your products, taking into account order lead time.
Since product demand is dynamic, the reorder point shouldn’t be a static number.
Don’t be afraid to re-compute and set a new reorder point if changes in product demand or sales patterns are observed.
It’s only good for you to keep your inventory management practices up-to-date with prevailing trends and actual demand.
Some last words
“Good forecasting is a blend of both art and science,” said Thomas Schleicher, a well-respected expert in the space of measurement science.
When it comes to inventory management, a strong mix of knowledge, tools and experience — which is exceedingly difficult to acquire — is integral to accurate inventory forecasting.
As the growth partner of hundreds of businesses, Choco Up understands your pain points in running a business, and hence we’ve prepared a variety of resources and tools to help you along the way:
- E-commerce Inventory Management: A Step-By-Step Guide
- E-commerce Logistics: 6 Winning Strategies For Online Sellers
- E-commerce Fulfillment: The Secret To 10X Customer Satisfaction
On top of online resources and articles to equip you with the necessary skills in growing your business, we also provide flexible funding for companies of all sizes and shapes, fuelling your business’s growth in ways that you may never have imagined before.
Whether you need more cash to stock up for peak seasons, have plans to invest in a new product line, or are looking to take your business global, Choco Up is a funding and growth partner that you can trust.
About Choco Up
Founded in 2018, Choco Up is the leading revenue-based financing platform in Asia Pacific, offering non-dilutive growth capital to fast-growing companies.
Currently covering more than 10 markets and 10 sectors, Choco Up has helped hundreds of businesses capture growth while protecting equity upside.
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