3 Inventory Forecasting Methods in Excel (Plus a Better Alternative)

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Every business wants to know what lies ahead, stay ahead of competitors and determine how specific trends and events will affect them in the long run.

What is inventory forecasting?

Inventory forecasting is the process of predicting required inventory levels for a future time by using past data, trends, and known imminent occurrences. Inventory forecasting is also called demand forecasting.

Forecasting accurately guarantees that firms have enough stock to satisfy consumer orders while not needlessly tying up cash in inventory.

What exactly is the purpose of inventory forecasting?

Inventory forecasting is one of the most successful strategies brands have used to predict the future. More than just looking to the future, demand forecasting supports businesses' current decision-making.

An efficient inventory forecasting strategy can help your business manage inventory, identify lead time demand, minimize sales revenue loss, and assess sales trends. Inventory forecasting helps to raise a brand's revenue and reduce unnecessary costs.

For many businesses,  Excel is their primary forecasting tool.

Why do many companies, particularly start-ups, seem comfortable using Excel for their analytical and inventory forecasting needs? 

We will consider this in this article and outline some drawbacks to using Excel. And if you stick around, we will introduce you to a much more powerful tool for business.

Let's first talk about the factors that made Excel a popular tool. 

Using Excel for inventory forecasting

Excel has a large variety of capabilities, which is frequently why new business owners rely more on it. It is known for using these three popular methods to forecast inventory.

Linear regression. 

Here, the outcome of one variable is predicted using one or more independent variables. Modeling the linear relationship between two or more variables might benefit from it. 

An example is when a business forecasts consumer influx (dependent variable) using independent factors like price rates.

Moving Averages 

When there is additional data beyond baseline information, most brands use this method to find trends or buying patterns that may alter their predictions.

Moving averages do precisely what their name suggests: they calculate the average value from a set of time-stamped data and then apply the result to a projection of future demand.

For instance, a business can determine the target market by averaging its sales over the previous two months and comparing it to the subsequent two-month periods.

Exponential smoothing 

This procedure entails smoothing some data. By finding seasonality and confidence intervals, exponential smoothing is for smoothening out prior data trends.

This algorithm combines additive error, trend, and seasonality to produce a more accurate demand forecast.

For instance, a brand could directly or invariably base subsequent prediction adjustments on the preceding forecasting result.

Next, let's go through the most common advantages of using Excel.

The Upside of using Excel for Inventory Forecasting

Data visualization

Excel is a fantastic tool for advanced analytics, enabling companies to understand their enormous data sets properly.

Excel uses elements like bars, pie charts, histograms, or line graphs to depict data visually. Businesses correctly understand their inventory and make wise decisions with Excel.

A low pricing range

Most businesses, especially start-ups, use Excel because it is a low-cost solution.

Users get it for a low monthly subscription fee. Its cloud-syncing feature enables users to work remotely on the same Excel file. 

There is a saying, "you get what you pay for." 

The value justifies the price.

Businesses that have specific, attainable goals look beyond price. Value is more important to them.

Conditional formatting

Excel allows users to alter the appearance of their spreadsheet to suit particular conditions. They utilize this tool to highlight essential numbers or cells in their spreadsheets, enhancing the visual impact of the numerical data.

Additionally, by preserving previous data for future forecasts, this formatting technique helps avoid information overload caused by an abundance of data.

Multiple forecast functions 

Excel has predefined formulas called functions that can fill up predictive values based on historical data. Excel has six forecast functions;






  6. FORECAST.LINEAR: We have discussed the advantages of using Excel and three standard techniques. 

Here are the downsides to using excel for your inventory forecasting.

The downsides of using Excel for inventory forecasting

With customer demand constantly in flux, businesses are very concerned about time, scalability, reliability, and data protection. Excel has been found wanting in some ways in these aspects. Let’s discuss this further.


Microsoft Excel is not time-friendly. It can be tiresome having to work manually with data in Excel. Finding data is complex even with simple tasks like sorting, analyzing, exporting, and locating data.

Because users get data from numerous sales channels, Excel makes omnichannel retailing challenging. A more efficient technology will undoubtedly save more time by integrating various selling points.

Not scalable

Can you trust a non-scalable prediction system? You won't. What will you do when the system isn’t robust enough to manage your business? 

As your business grows, the amount of data you generate grows too, scalability becomes crucial here.

Large amounts of data are more challenging to manage with Excel. The working performance is complex.

Inventory forecasting quickly becomes a continuous activity from the start, so if your company aims to grow in the long run, you need a more scalable platform.

Prone to human error

This is entirely reasonable. That is something you would undoubtedly anticipate from a solution that only automates the forecasting process itself.

It is impossible to overstate the likelihood of errors when humans are involved. The truth is that even a minor typing error can impact the entire data set. 

Businesses should leverage advanced automation to compete effectively in the marketplace. This will reduce inaccuracy, improving reliability.

Complex reports

Due to its extensive feature set, Excel is difficult and even overwhelming to use.

Predictions will undoubtedly be inaccurate without a brief and precise report.

Most reports generated by Excel data entry are challenging to read and would need you to seek the help of a professional analyst to interpret

Let's explore a superior substitute.

Luminous; A better alternative



Excel was fantastic in the past, but it has now become almost obsolete. To keep up with today’s demand for inventory forecasting, your business needs to leverage a more trustworthy technology, such as Luminous.

Here is why Luminous is your go-to solution for all your inventory forecasting needs.

  • Luminous gives you a real-time bird-eye view of all your channels, warehouses, and units.
  • Helps you create a perpetual inventory system where orders are instantly pushed live across channels without worrying about stockouts or overselling.
  • Automatically places product orders, customize trigger notifications, and receive intelligent inventory data. 

Its unique automation capabilities and clever reporting eliminate human error, helping you save time, energy, and money. Luminous makes the RFQ and purchasing process more straightforward.

  • Saves time by combining all retail channels in one location, offering you an omnichannel retail experience.

The answer to an efficient forecasting method is only one click away. Want an overview of how you can leverage Luminous? Check it out here.

Make the jump your business needs with Luminous, and you won't be sorry.

Request a free demo today!

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