Demand Forecasting: Types, Methods, and Examples

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How will you know how much new product to produce for your next holiday? What kinds of capital will you need to invest in stock for your next fiscal year? Demand forecasting has the answers. Demand forecasts project sales for the next few months or years. Different forecasting models look at different factors. You may want to employ multiple types of demand forecasts. That will give you a well-rounded picture of potential opportunities and pitfalls.

No one can predict the future with absolute certainty. However, there are several demand forecasting techniques that use predictive analysis that will help you make an educated guess. Using a forecasting model will help you with better business decision making.

Here’s everything you need to know about demand forecasting.

What is demand forecasting?

Demand forecasting is the process of estimating future demand for a product or service, which then informs businesses about the estimated product or service quantity that consumers may want to purchase over a period of time. Accurate forecasting is important for businesses to plan production in order to meet customer demand. Overestimations or underestimations of customer demand can lead to excess inventory or a short supply of products.

6 types of demand forecasting

There are several methods of demand forecasting. Your forecast may differ based on the demand forecasting models you use. Best practice is to do multiple demand forecasts. This will give you a more well-rounded picture of your future sales. Using more than one forecasting model can also highlight differences in predictions. Those differences can point to a need for more research or better data inputs. 

1. Passive demand forecasting

Passive demand forecasting is the simplest type. In this model, you use sales data from the past to predict the future. You should use data from the same season to project sales in the future, so you compare apples to apples. This is particularly true if your business has seasonal fluctuations.

The passive forecasting model works well if you have solid sales data to build on. In addition, this is a good model for businesses that aim for stability rather than growth. It’s an approach that assumes that this year’s sales will be approximately the same as last year’s sales. 

Passive demand forecasting is easier than other types because it doesn’t require you to use statistical methods or study economic trends. 

2. Active demand forecasting

If your business is in a growth phase or if you’re just starting out, active demand forecasting is a good choice to help you make informed decisions. An active forecasting model takes into consideration your market research, marketing campaigns, and expansion plans. 

Active projections will often consider external factors. Considerations can include the economic outlook, growth projections for your market sector, and projected cost savings from supply chain efficiencies. Startups that have less historical data to draw on will need to base their assumptions on external data.

3. Short-term projections

Short-term demand forecasting looks just at the next three to 12 months. This is useful for managing your just-in-time supply chain. Looking at short-term demand allows you to adjust your projections based on real-time sales data. It helps you respond quickly to changes in customer demand.

If you run a product lineup that changes frequently, understanding short-term demand is important. For most businesses, however, a short-term forecast is just one piece of a larger puzzle. You’ll probably want to look further out with medium- or long-term demand forecasting.

4. Long-term projections

Your long-term forecast will make projections one to four years into the future. This forecasting model focuses on shaping your business growth trajectory. While your long-term planning will be based partly on sales data and market research, it is also aspirational. 

Think of a long-term demand forecast as a roadmap. Using this forecasting technique, you can plan out your marketing, capital investments, and supply chain operations. That will help you to prepare for future demand. Being ready for your business growth is crucial to making that growth happen.

5. External macro forecasting

External macro forecasting incorporates trends in the broader economy. This projection looks at how those trends will affect your goals on a macro-level. An external macro demand forecast can also give you direction for how to meet those goals. 

Your company may be more invested in stability than expansion. However, a consideration of external market forces is still essential to your sales projections. External macro forecasts can also touch on the availability of raw materials and other factors that will directly affect your supply chain.

6. Internal business forecasting

One of the limiting factors for your business growth is internal capacity. If you project that customer demand will double, does your enterprise have the capacity to meet that demand? Internal business demand forecasts review your operations. 

The internal business forecasting type will uncover limitations that might slow your growth. It can also highlight untapped areas of opportunity within the organization. This forecasting model factors in your business financing, cash on hand, profit margins, supply chain operations, and personnel. 

Internal business demand forecasting is a helpful tool for making realistic projections. It can also point you toward areas where you need to build capacity in order to meet expansion goals.

5 demand forecasting methods

There are many different ways to create forecasts. Here are five of the top demand forecasting methods.

1. Trend projection

Trend projection uses your past sales data to project your future sales. It is the simplest and most straightforward demand forecasting method.

It’s important to adjust future projections to account for historical anomalies. For example, perhaps you had a sudden spike in demand last year. However, it happened after your product was featured on a popular television show, so it is unlikely to repeat. Or your eCommerce site got hacked, causing your sales to plunge. Be sure to note unusual factors in your historical data when you use the trend projection method. 

2. Market research

Market research demand forecasting is based on data from customer surveys. It requires time and effort to send out surveys and tabulate data, but it’s worth it. This method can provide valuable insights you can’t get from internal sales data.

You can do this research on an ongoing basis or during an intensive research period. Market research can give you a better picture of your typical customer. Your surveys can collect demographic data that will help you target future marketing efforts. Market research is particularly helpful for young companies that are just getting to know their customers.

3. Sales force composite

The sales force composite demand forecasting method puts your sales team in the driver’s seat. It uses feedback from the sales group to forecast customer demand.

Your salespeople have the closest contact with your customers. They hear feedback and take requests. As a result, they are a great source of data on customer desires, product trends, and what your competitors are doing. 

This method gathers the sales division with your managers and executives. The group meets to develop the forecast as a team.

4. Delphi method

The Delphi method, or Delphi technique, is one of the qualitative methods of demand forecasting that leverages expert opinions on your market forecast. This method requires engaging outside experts and a skilled facilitator.

You start by sending a questionnaire to a group of demand forecasting experts. You create a summary of the responses from the first round and share it with your panel. This process is repeated through successive rounds. The answers from each round, shared anonymously, influence the next set of responses. The Delphi method is complete when the group comes to a consensus.

This demand forecasting method allows you to draw on the knowledge of people with different areas of expertise. The fact that the responses are anonymized allows each person to provide frank answers. Because there is no in-person discussion, you can include experts from anywhere in the world on your panel. The process is designed to allow the group to build on each other’s knowledge and opinions. The end result is an informed consensus.

5. Econometric

The econometric method requires some number crunching. This quantitative type of forecasting combines sales data with information on outside forces that affect demand. Then you create a mathematical formula to predict future customer demand.

The econometric demand forecasting method accounts for relationships between economic factors. For example, an increase in personal debt levels might coincide with an increased demand for home repair services. 

Combining demand forecasting methods – Expert Advice

Arthur Pentecoste Data scientist and author of Demand Prediction in Retail Springer 2022 says :

“Many of the above information closely interact together. To obtain the most accurate forecasts you’ll want to combine them. Common methods include: blending all available data as inputs of a single forecasting model (e.g., historical sales, marketing trends, customer survey, economic metrics…) or using several models and consider the average of the different results as your demand forecast. In any case, the best way to select a method will be to apply it to historical data and compare results”

Demand forecasting

Demand forecasting examples

All types of businesses can benefit from demand forecasting. Here are three examples of how demand forecasting might work for an eCommerce company.

Passive/Trend Projection

A husband and wife team sells costumes, party favors, and decorations for kids. They have been in business for more than 10 years. They have built their business to a comfortable level of revenue and profitability. While they don’t plan to retire soon, they also don’t plan to expand.

They average the last three years of sales data and use that to project trends for the coming year. Historical data tells them that their best months are May and October, and the worst are December and August. They use this information to create a trend projection that tells them when they need to place their wholesale orders. This also tells them when they need to add temporary staff at their fulfillment warehouse. They factor in a plan for a summer promotion in the coming year that should increase sales.

Active/Market Research

A startup has developed revolutionary wireless headphones. The company initially launched through Kickstarter. The crowdfunding platform gave them some information about customer demand. Now, however, they need to expand their customer base. They need more customers to grow their enterprise into a sustainable eCommerce business.

The marketing team sends surveys to all customers. From the responses, they develop a profile of the company’s current customers. The profile includes age, income, employment, and where they live. They discover that people who commute by public transit are enthusiastic about their noise-canceling headphones. 

From the survey responses, the company develops a marketing plan that includes ads on trains and buses. They bring in econometric principles to project the impact of their marketing campaign on future sales. From data gathered on demographics and consumer behavior, they are able to develop a demand forecast.

Short-Term/Sales Force Composite

A company sells high-end office chairs, both B2C and B2B. The sales team works primarily with B2B customers to generate large orders for corporate offices. However, the salespeople have had a hard time closing sales for the past quarter.

The CFO convenes the sales group to brainstorm. When the salespeople compare the feedback they have gotten, they uncover a market trend. More people are working from home. Companies are reducing the amount of office space they need to furnish. In addition, their corporate clients no longer view office amenities as a way to lure new hires.

The company created a short-term demand forecast with greatly reduced sales over the following six-month period. It scaled back its production accordingly. This would give the company a period of time to revamp its marketing approach to meet changing customer demand. In the meantime, it could use other demand forecasting techniques to develop projections for its new markets.

Predictive Analysis (Historical Data)

Dr. Bob G. Wood, Professor of Finance at University of South Alabama sites a couple of examples of using predictive analysis of historical data to determine demand:

  1. “I’ve worked a with local HVAC/plumbing/electrical firm using predictive analysis (historical data) and customer service experiences gleaned from company service technician’s customer interactions to estimate future service needs. Their experience has shown that using both of these methods has provided valuable service staffing level estimations and customer appointment time preferences.”
  2. “Another client has both traditional and online retailing operations. The online presence is relatively new so we were unable to use historical data. As an alternative, we used in-store and website customer surveys to rank order online purchasing preferences (free shipping and free returns dominated other preferences) to estimate online purchasing demand.”

Why your eCommerce company needs demand forecasting

Whether your eCommerce business is small or large, demand forecasting is essential. A demand forecast can be as simple as an Excel spreadsheet detailing your cash flow for the past 12 months. Or it can use statistical methods of regression analysis to study the influence of economic trends on your future business. However, even the most basic forecast will give you vital information. 

Demand forecasting

Here are just a few of the benefits of demand forecasting.

  • Reveal seasonal trends. A review of historical sales data will help you spot the seasonal fluctuations to better inform your sales forecasting. Beyond busy holiday seasons, it’s also important to know which months have less customer demand. If your sales take a dip every February, that could be a good time to offer discounts to keep customers engaged. 
  • Rationalize your cash flow. Your past balance sheet will show you how sales revenue meshes with costs of goods sold. This can help you understand when you will have the cash on hand to invest in keeping inventory levels where they need to be. 
  • Plan your supply chain. Demand forecasting will help you with capacity planning, and inventory planning so you can plan ahead to have inventory on hand when customer demand spikes. This will keep you from incurring rush charges and putting items on backorder as you scramble to fill orders.
  • Understand how outside factors will influence your sales. Forecasts can include data about industry trends, the state of the economy, and projections for your market sector. Bringing these factors into your forecasting model can help you be ready to adapt and grow your business. 
  • Prepare for the future. Every business has to be ready to weather the unexpected. That could take the form of a natural disaster or a new competitor that eats into your market share. Demand forecasting helps you prepare your supply chain and your business for future shocks.

Issues with demand forecasting in most companies

Before you can do effective demand forecasting, you need accurate information. Issues with demand forecasting in most companies have to do with missing data. Here are some of the things that can get in the way of your forecasts.

Inventory management is essential for accurate demand forecasts
  • Lack of historical sales data. This is a problem for companies without much of a track record. However, even more established businesses can struggle with this. Sales data from past years should be compiled and organized into a format that’s easy to use.
  • Inadequate supply chain management. The best demand forecast won’t help you if your supply chain isn’t predictable and well-managed. You need to know the exact lead time series required for the allocation of raw materials, to produce finished goods, and to ship them to your order fulfillment warehouse. In addition, you need to be hands-on with all aspects of your supply chain. This will allow you to quickly troubleshoot problems that might hold up your production.
  • Lack of inventory control. Good inventory management is the foundation of good demand planning. If you don’t have a handle on what you have in the warehouse, you can over- or underestimate your production. Fortunately, your 3PL services provider can help you with that.

How forecasting affects your supply chain and fulfillment 

You don’t have to fall prey to the pitfalls of demand forecasting. These best practices for supply chain operations can help you use demand forecasting to keep your business healthy.

  • Share data up your supply chain. Data silos can create inefficiency. Keep communication lines open with every level of your supply chain. Make sure the information flows in both directions.
  • Use redundant sourcing. Relying on one supplier can lead to backlogs if that supplier has a production problem. Diversify your sources to protect your supply chain.
  • Track the results of your demand forecasts. Revisit past forecasts to learn from your mistakes. How accurate was your last forecast? Did your demand forecasting techniques work well? Or do you need to look to different models for actionable results? 
  • Leverage your 3PL to avoid deadstock. Dead stock is items that never sold. This merchandise can linger on warehouse shelves for years, costing you money without bringing in revenue. It’s hard to make an accurate plan for future customer demand if you have an issue with dead stock. Your eCommerce fulfillment company (or 3PL) can help you avoid dead stock with transparent inventory.

Your fulfillment company is an important partner for your demand forecasting. It can aggregate many of the data points you need to create useful forecasts.

Demand forecasting helps drive smarter business decision-making. It doesn’t matter whether you choose simple or more complex methods. Demand planning based on sales data, market research, and economic factors will help your business stay strong.

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Demand Forecasting FAQ

What are the different methods of demand forecasting?

The five most popular demand forecasting methods are: trend projection, market research, sales force composite, Delphi method, and the econometric method.

What are the types of demand forecasting?

There are six types of demand forecasting, which include: passive demand forecasting, active demand forecasting, short-term projections, long-term projections, external macro forecasting, and internal business forecasting.

Why is demand forecasting important in supply chain?

Demand forecasting in supply chain refers to the same demand forecasting process of estimating future demand for products or services. Demand forecasting is particularly important in supply chain related businesses because forecasting plays a critical role in being able to manage inventory and knowing when to restock products, and capacity planning. A good example of demand forecasting for a supply chain related business is a fulfilment warehouse service because future demand will determine how much warehouse storage space is needed, along with the number of products that must be stored, and how many resources in terms of staffing and packaging will need to be dedicated to shipping out those products. On top of that, replenishing the supply of products on the shelves is a critical part of inventory management, which depends on demand forecasting in supply chain. 


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