Why Your Supply Chain Needs to Know The Difference Between Demand Planning and Demand Forecasting

Imagine you are a supply chain manager who has done everything in your power to develop and sell new products that have now taken off in the market. However, the demand planning process you enacted for the product was forecasted inaccurately and now you’re running low on the inventory – which means you are missing out on a major revenue opportunity. This happened recently to Sony when the PlayStation5 was released late last year, costing the company millions of dollars in missed revenue. The problem with this situation and a problem that many companies face today, is that managers put a lot of emphasis on demand forecasting, but fail to successfully implement demand planning. 

 

Demand forecasting is the process of predicting demand based on historical data and patterns, while demand planning begins with forecasting but then goes a step further and takes into consideration many other aspects that are important in order to get an accurate prediction – like distribution, seasonality, where the inventory will be housed, where it will be sold, external factors like a global pandemic, etc. 



So What Exactly is Demand Planning? 

 

Demand planning is a supply chain management process of predicting or estimating how much inventory your customers will buy from you to help businesses meet customer demand for products while minimizing excess inventory. It involves creating a demand plan based on a statistical forecast that takes into consideration many factors that can influence demand – such as inventory levels, marketing strategies, buying trends, etc – and then details where to distribute the products in order to meet the anticipated demand.    

 

Why is it Important? 

 

Demand Planning is important because it can lead to an increase in profitability, customer satisfaction, efficiency and so much more. Projecting sales and planning for peaks in customer demand is crucial to keeping customers happy and maintaining a successful business. Poor planning can have far-reaching negative consequences on a business’s growth, operations and brand – and can even lead to a loss of customers. 

 

According to research by EnsembleIQ, 34% of supply chain professionals report a lack of demand forecasting and planning accuracy. This challenge is consistent across professionals in every sector. In fact, 6 in 10 retailers report that they are taking steps to improve their inventory management through the use of demand planning software. 

 

How Can AI Improve Demand planning? 

 

The main goal of demand planning is to maintain the right amount of inventory to meet customer demand without incurring shortages or wasting capital on producing and storing surplus inventory. A key element to ensure this is data collection. Advanced machine learning makes access to real-time data increasingly available, improving forecast accuracy and thus demand planning immensely. It also provides collaboration tools that enhance the ability of planners to share information amongst one another and react more quickly to changes that occur in supply and demand. 

 

Demand planning solutions are increasingly being used across a large variety of industries – healthcare, e-commerce, food & beverage, automotive, retail and many more. According to recent research, increasing demand planning accuracy can increase revenue by up to 3%. Additionally, according to research by the Aberdeen Group, companies that are able to produce accurate demand plans are 7.3% more likely to hit their quotas and are 10% more likely to make improvements to their bottom line. While implementing demand planning solutions such as AI-driven software may be an adjustment and investment for a business, owners can expect to see a return on investment in less than a year.


To discover how your supply chain business can improve profitability and efficiency through the use of AI-driven demand planning, contact info@conversight.ai or request a demo

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