Many businesses use the terms “demand forecasting” and “demand planning” interchangeably, but they’re not the same.

Demand forecasting tells you how much of your product customers would buy in a perfect world: one where your business has no operational constraints like capital shortages or supply chain disruptions. 

On the other hand, demand planning factors in your existing business priorities and constraints, including consumer trends, marketing, and storage and distribution considerations.

In this article, we’ll explain the differences between demand forecasting and demand planning, and share tips for how you can use both to effectively scale your retail business.

What is demand forecasting?

Demand forecasting tells you how much of your product customers would be willing to buy in the absence of operational constraints. In other words, it's like looking at pure consumer demand in a vacuum.

Demand forecasting is important because it informs all your inventory decisions, including what new products to launch, when to promote existing products, how to set pricing, how much inventory to order, where to store it, and more. 

An accurate demand forecast helps you optimize your inventory, increase your margins and improve your bottom line.

What is demand planning?

Forecasting future demand is only half the battle. Without an actionable strategy to meet that demand, you're always passively reacting instead of planning ahead.

Demand planning tells you how much your customers will buy, based on the constraints you project for the future. These may include the amount of available capital, planned or unplanned supply chain disruptions, and other logistical and operational limits. Based on this more in-depth picture, your business can develop actionable steps to meet and/or shape demand.

Think of it like this. When you’re planning a party, your first step might be to list everything you’d like to offer your guests — drinks, meals, entertainment, the whole enchilada. 

But once you start reaching out to vendors, you’ll need to align your ideal list with your budget and timelines for the party to make any necessary adjustments.

Save time on manual demand forecasting and improve your accuracy with Flieber. Try it for free today to see how deep inventory visibility can help you boost your sales and margins.

The benefits of demand planning in e-commerce

By consolidating and analyzing data from a variety of sources, demand planning helps online retailers manage and control inventory in a growing multichannel operation.

With strong demand planning and forecasting processes, your business can enjoy benefits like:

• Stockout prevention: When you know exactly how much stock you need on hand to meet customer demand, you can work to actively reduce the risk of going out of stock.
• More sales: When you can fulfill every order, every time, you lose fewer sales to your competitors. You also develop a reputation for dependability, which can mean even more sales as brand awareness spreads.  
• Reduced storage costs: Better demand planning means less overstock. When you don’t need space for items that aren’t selling, you can reduce your warehousing costs.
  
• Optimized supply chain: Increased visibility into the inner workings of your supply chain keeps it operating smoothly so you react faster to any disruptions or delays.
  
• Improved customer experience: When you always have the products you promise in stock, you’ll gain and retain loyal customers more easily. 
  
• Increased profit margins: Efficient inventory processes allow you to minimize costs and maximize profits. 

As you add new channels, products, and revenue streams, effective demand planning helps you deliver on every promise to every customer. 

You’ll have the insights you need to effectively manage new lead times, suppliers, and inventory constraints. All with fewer headaches and unforeseen issues. But where do you start?

5 demand planning and demand forecasting methods for e-commerce

Some of the following methods fall more closely under the umbrella of demand forecasting, while others combine elements of both demand forecasting and demand planning. 

The lines can get blurry, but the best systems typically unite the two methods in a meaningful way based on the real needs of your business.

Here are some common methods for forecasting and responding to demand:

1. Historical data method  

In the historical data method, you examine a product’s historical sales to predict how many units you’ll need in the future based on the number you sold in the past.

Strengths of the historical data method:

The historical data method is grounded in real sales data. The data is easy to understand and built on information that you already have available in your sales system.

The more accurate and stable your historical sales data, the better predictions and estimates you’ll be able to achieve with this method. 

Weaknesses of the historical data method:

Unfortunately, the historical data method doesn’t account for factors like past stockouts, seasonality, surges in demand, or competitor actions. It provides a vital piece of the puzzle, but doesn’t give you the full picture. 

2. Market research method  

The market research method uses real customer insights to make decisions about the future of your inventory. It relies on two main approaches: 

1. Primary research - using data obtained through customer surveys, or via the Delphi method where a facilitator sends a group of industry experts a questionnaire then compares and discusses responses until arriving at a consensus.
2. Secondary data - sizing up the market via secondary data, like market growth, penetration, external demand surveys, and more.

Strengths of the market research method:

Rather than relying solely on past trends, this method allows you to gain insight into future trends you might not otherwise anticipate.

The market research method is also a major win for customer satisfaction and loyalty, since surveying your customers about your product line shows them you care about them enough to ask for their input.

Weaknesses of the market research method:

The market research method is time and resource intensive, making it impractical to sustain if your business doesn’t have sufficient capital or staffing. 

Also, the primary data you’ll receive in this method is self-reported, making it inherently biased. After all, just because a customer says they plan to purchase something, doesn’t necessarily mean they’ll follow through.

While market research is incredibly useful for predicting trends or developing products in the longer term, it’s not something you can use on a month-to-month basis to make immediate inventory decisions on a SKU level. This method may be great for the occasional temperature check, but it isn’t a standalone method for demand forecasting.

3. Sales force composite method

In the sales force composite method, you get your sales team together for a detailed brainstorming session. They share and compare any feedback from customers to uncover potential market trends.

Strengths of the sales force composite method:

One major strength of the sales force composite method is that it leverages existing company resources. You already have knowledgeable sales reps who are in close contact with your customers. You don’t have to design expensive surveys, run complex algorithms, or invest in new tech.

Weaknesses of the sales force composite method:

A major disadvantage of the sales force composite method is that the data is inherently biased. Your sales reps may be overly optimistic about potential sales, or they may not be speaking to a representative sample of customers. Customers themselves might also be biased about what they share, or sales reps may not yet have the skills to make accurate predictions.

4. Econometric method

The econometric demand planning method combines sales data with outside data known to impact purchasing decisions. For example, you may include trends like personal debt levels, local income rates and more, in your calculations.

Strengths of the econometric method:

This method has numerous strengths. The econometric method accounts for past sales data like in the historical data method. But it also lets you combine this data with external factors that may impact a customer’s desire to purchase in the future. 

Weaknesses of the econometric method:

The main downside of the econometric method for demand planning is that it is time-consuming and challenging to calculate by hand. If you’re manually planning for demand, you may not want to pursue this method, as there may be increased risk of human error. 

5. Algorithm-based 

The algorithm-based method uses a dedicated algorithm to analyze vast amounts of data based on your preferred forecasting model.

Strengths of the algorithm-based tool method:

The algorithm-based method has numerous advantages. First, the predictions created by this method are based on real data. This data includes historical data, current trends, demographics, and more.

If you’re using an inventory planning solution like Flieber, you can enlist the help of AI to improve your forecast accuracy over time.

Weaknesses of the algorithm-based method:

The algorithm-based method requires you to invest in an inventory planning tool, which can feel costly upfront depending on your needs. However, with the right solution, this cost can be easily recouped through improved efficiencies in your inventory and demand planning.

Always know when and how much to reorder. Try Flieber for free today to learn how better forecasting can help you avoid costly stockouts and overstocks.

What are the best tools for demand planning and forecasting?

There’s no such thing as a one-size-fits-all “best” demand planning and forecasting solution. 

Some businesses will benefit from enterprise solutions that can handle enormous amounts of data and integrate with legacy systems. Others may be able to get by on simple spreadsheets and calculations. 

Here are some of the broad categories of demand forecasting and planning tools:

• Spreadsheet tools: Simple spreadsheets like Microsoft Excel or Google Sheets can be effective for small businesses with less complex demand planning and forecasting needs. These tools enable basic trends analysis, statistical forecasting, and visual data representations and are ideal for brands with just one sales channel.
• Advanced Planning Systems (APS): APS are comprehensive software solutions that can handle huge data sets and analyses. An APS can incorporate demand planning, inventory management, supply and production planning.
• Machine learning-based tools: Machine learning tools employ algorithms that improve over time, becoming more reliable and precise. These tools use large sets of historical and real-time data to create a more accurate forecast.
• Enterprise Resource Planning (ERP) systems: ERPs provide end-to-end operational insight for managing a variety of activities, including demand forecasting and planning, inventory and supply chain functions, and even accounting, project management, business planning, and more. Some demand forecasting and inventory management systems are designed to pull data from an ERP.
• Software-as-a-Service (SaaS) platforms: Unlike ERPs and legacy platforms, SaaS platforms are “live” cloud-based programs that may be updated and improved as often as every day. These solutions tend to be more agile and customizable than other options and users can choose from a menu of affordable feature packages.

Control your inventory. Master your operations.

True inventory optimization requires both demand planning and demand forecasting.

To drive sales and margins, look for an inventory planning solution that can help you master your inventory levels and actively avoid the chronic stockouts, overstocks, and backorders draining your profits.

When you’re ready to take control, Flieber can help.

Flieber is the inventory planning platform that gives you deep visibility into your sales, inventory, and supply chain data to help you make better decisions in a fraction of the time.

Everything works better with a plan. Try Flieber for free to learn more.

Frequently asked questions (FAQs)

Demand forecasting and planning can tell you a lot about your business. However, you also need to have a firm grip on your sales forecasting and planning in order to capture as much revenue as possible.

Here are a few frequently asked questions to help you understand the differences between each key process.

What is demand forecasting?

Unlike sales forecasting, demand forecasting focuses on understanding unconstrained consumer demand to ensure the business is optimized to meet this demand without overstocking or understocking.

What is demand planning?

Demand planning involves not just predicting demand, but also coordinating with supply chain and inventory operations to ensure that the company can meet that demand efficiently.

It encompasses demand forecasting but goes further to include common constraints such as inventory management, production planning, and distribution strategies.

What is sales forecasting?

Sales forecasting is the process of estimating future sales using historical sales data, market trends, and other indicators. Sales forecasts are used to project revenue over a specific period, helping businesses make informed decisions about resource allocation, budgeting, and financial planning.

To forecast actual future sales or revenues, it’s best to start from an unconstrained demand forecast.

What is sales planning?

Sales planning is the process of organizing, setting goals, and outlining strategies to achieve the sales forecast. It involves allocating resources, setting sales targets, defining sales territories, and planning the sales activities that will help achieve the desired revenue.