Post Index:
When talking about supply chain planning processes and supply chain management, the terms “demand forecasting” and “demand planning” are frequently mentioned. And even people in the know will often use these two terms interchangeably, using one when they mean the other and vice versa.
Although they are related, demand forecasting and demand planning are really two distinct concepts and cover different aspects of the supply chain planning process.
Below we explore the definition of demand forecasting vs demand planning, let’s first expand upon what each process entails, how they are intertwined, and how the approach to both concepts has changed in recent years. We will also explore how each continues to evolve as companies seek to effectively plan and mature their processes to thrive in today’s dynamic marketplace.
Understanding the differences between the two concepts can provide you with the context needed to optimize practices and take your supply chain planning processes to the next level.
Demand forecasting
A forecast is, in its simplest form, a prediction of future events. In a business context, demand forecasting, is the process by which demand planners attempt to predict what demand for a given product will be in a week’s, a month’s, or even a year’s or more time. Its singular objective is to arrive at the right answer (or as close to right as possible). To arrive at this conclusion, demand forecasting must be very data driven.
Demand planners are collaborative and often work with sales, marketing, finance, operations, and other key stakeholders to gather historical information, such as sales projections, the company’s prior growth rate, as well as real-time data such as consumer behavior, market trends, weather, and more. Then, by using various forecasting models and techniques, a solid consensus forecast can be reached.
Demand forecasting can be seen as the starting point for demand planning, as it involves analyzing data and other relevant factors to predict future demand. This forms the basis for the overall demand plan.
As an exercise in estimating the future, demand forecasting always involves some degree of uncertainty. Thankfully, technology has rapidly evolved in recent years to increase accuracy, remove bias and improve forecastability. The advances in Artificial Intelligence (AI) and Machine Learning (ML) have ushered in a new era of forecasting capabilities that are transforming the way organizations plan for the future. (Learn more about AI and ML in the guide, The Practical Role of Machine Learning and Artificial Intelligence in Supply Chain)
In recent years and with accelerated changes in the market, there has been a significant shift in planners’ ability to forecast with confidence. Many of the tools and traditional methods for demand forecasting, which were largely based on historical data and rigid statistical models, simply don’t cut it anymore. This is largely due to the increasing volatility and complexity of demand, which now impacts not just finished goods planning, but also raw materials and semi-finished goods. These processes are being replaced by advanced AI-powered capabilities that can analyze vast amounts of data to identify patterns that would otherwise go undetected, allowing companies to make more accurate predictions about future demand and effectively plan strategies to meet that demand.
Demand Planning
While demand forecasting is focused on predicting demand, demand planning takes into account the available resources and capacities required to meet that demand. So, the process of demand planning covers the entire undertaking: forecasting consumer demand and then arranging things accordingly. Its overarching goal is to make sure a company can supply customers with a given product or service when, where and how they want to buy it while keeping costs as low as possible, to improve margin and support profitable growth. The demand planner takes the demand forecast and translates it into action, mapping out all necessary steps and ensuring everyone is able to perform their parts well.
Demand planning, encompasses much more than demand forecasting. Although producing the forecast is a critical component, it triggers a series of other duties and responsibilities that are all part of demand planning.
As a key aspect in this process that bridges a company’s sales and operations verticals, demand planners must coordinate with stakeholders up and down the multi-enterprise supply chain to ensure customers are happy and the overall company remains healthy.
The rise of new channels and quick shifts in consumer behaviors has led to an explosion of demand signals, making it more challenging to accurately predict future demand. Additionally, product life cycles are shorter, and geopolitical and economic uncertainty is on the rise, all of which further complicate both the demand forecasting and demand planning processes.
To properly capitalize on new market opportunities in today’s fast-changing environment, companies require the ability to sense, analyze and shape demand. The fact is, demand planning has evolved significantly over the years, and what constitutes a good demand plan has changed along with it. An effective demand plan must now align with more areas across the business, such as marketing, sales, and commercial teams. In addition, external alignment is becoming increasingly important, which means that the planning process requires more advanced tools and capabilities to enable and extend collaboration both internally and externally with partners.
All companies engage in some kind of demand forecasting and demand planning. The real question is whether they’re doing so effectively. Are the tools they’re using and the processes they have in place yielding great results? If not, a lack of differentiation between these two concepts could be to blame. Great demand forecasting strategies may not necessarily prove optimal for carrying out an overall demand plan, for instance.
Is your organization taking advantage of the recent breakthroughs in supply chain planning technology to move away from reactive strategies? Today’s advanced supply chain planning software helps companies identify new opportunities for business growth and make better decisions faster to minimize the impact of disruptions. By analyzing market trends, customer behavior, and other external factors that come into play for specific products, these systems can uncover hidden insights and provide valuable guidance on how to capitalize on emerging trends and opportunities.
Our Atlas Planning Platform software was designed to help you with both demand forecasting and demand planning. Schedule a consultation with one of our experts today to explore how we can help you accurately forecast demand and effectively plan for it.
