Demand forecasting and demand planning are two supply chain terms that sound plausibly interchangeable. However, while they are closely related, they refer to distinct parts of the sales and operations planning (S&OP) process, which aligns an organization’s sales expectations, operational capacity, material availability, and financial goals around a single game plan.
From manufacturers to retailers, a smooth supply chain relies on accurate demand forecasting and planning. When done well, these processes support better decision making that saves time and money.
In this article, you will learn:
What demand forecasting is and best practices
What demand planning is and key processes
Why demand forecasting and demand planning are important
What Is Demand Forecasting?
The Institute of Business Forecasting (IBF) defines demand forecasting as “the process of using data, analytics, insights, and experience to estimate future product and service needs.” Or as NetSuite describes it, demand forecasting is “fundamentally about predicting what people are going to want, how much, and when.” Similar to a weather forecast, a demand forecast is an educated guess about what will happen in the future.
Demand forecasts can be:
Short-term: “Will the retailer need more pairs of socks shipped on Friday or Saturday?”
Long-term: “How many pairs of socks will the retailer sell this year?”
Specific (microlevel): “How many pairs of Crocs will Americans buy this year?”
General (macrolevel): “How many pairs of casual shoes will Americans buy this year?”
Related Reading: Why Demand Forecasting Accuracy Starts Before the Forecast Runs
Demand Forecasting Best Practices
While the Institute for Supply Management (ISM) notes that no demand forecasting model is perfect, it offers the following best practices:
Avoid relying on historical data too much. Historical data is helpful, but forecasting cannot start and stop here.
Pay attention to external factors. Combine historical data with external factors like what your competitors are doing, economic conditions, weather patterns, and consumer trends.
Avoid statistical models that are overly complex. A model with a lot of bells and whistles can seem appealing, but sometimes, simpler is better. Simpler models are easier to interpret and less prone to errors.
Understand your model’s limitations. Again, no model is perfect. Knowing your model’s weak spots can help you incorporate buffers
Collaborate across departments. Involve all stakeholders in the process (e.g., sales, marketing, supply management).
Tweak your forecasts as needed. Forecasts aren’t a set-it-and-forget-it endeavor. As variables change (e.g., market trends), your forecast should as well.
Related Reading: The 5 Biggest Demand Forecasting Challenges in Supply Chains — and How To Fix Them
What Is Demand Planning?
Demand forecasting is part of demand planning. According to the IBF, demand planning “takes the forecast further by integrating it into the business strategy, aligning stakeholders around a shared set of expectations, and determining the actions needed to respond to that demand.” This creates a “realistic and actionable view of future demand so the organization can align supply, resources, and investments accordingly.”
If demand forecasting asks what demand will be, demand planning asks what needs to be done to meet that demand.
Key Demand Planning Processes
NetSuite’s breakdown of the key demand planning components demonstrates how demand forecasting fits into demand planning:
Collect the data. Good demand planning hinges on access to good data, which can be internal (historical sales, production lead times, inventory, upcoming marketing campaigns) and external (major weather events, material shortages).
Analyze the data. Once your data is standardized, you will need to analyze it (often using AI or machine learning) to find patterns and correlations.
Predict future demand. This is demand forecasting: inputting your analyzed data into statistical models to come up with a prediction.
Manage your inventory. Figure out how much inventory you need across your supply chain.
Integrate demand sensing. Incorporate real-time data to detect changes in demand.
Engage in scenario planning. Plan for multiple hypothetical outcomes.
Like demand forecasting, demand planning isn’t static. It must be able to react to environmental shifts, like world events and consumer trends.
Related Reading: Revitalize Your Supply Chain
Frequently Asked Questions
What is the difference between demand forecasting and demand planning?
Demand forecasting predicts what consumers are going to want, how much they’re going to want, and when they’re going to want it. Demand planning uses demand forecasting to create a plan for how to meet that demand.
What are the benefits of demand forecasting and demand planning?
Good demand forecasting and planning can help companies:
Minimize stockouts and overstock
Improve customer satisfaction
Improve efficiency
Maximize cash flow
Build better trading partner relationships
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