Demand planning is a supply chain management process that enables a company to project future demand and successfully customize company output — be it products or services — according to those projections.
Demand planning seeks to achieve and maintain an effectively lean supply equilibrium, one in which store inventories contain just as many products as demand dictates, but no more. Finding that perfect balance that exists between sufficiency and surplus can prove especially tricky. And although maintaining that balance is a major concern of demand planning, so is the constant effort to help shape demand through an effective use of promotions.
Effective demand planning typically requires the use of demand forecasting techniques to accurately predict demand trends, and carries added benefits, such as heightened company efficiency and increased customer satisfaction.
Demand planning is the linchpin of an effective supply chain, serving two essential functions — which makes it doubly important to business.
First, there always exists the fundamental drive to protect the sale and ensure that expected revenues are generated. But retailers can’t sell what they don’t have in stock. And it doesn’t take long for today’s consumers to develop a lasting impression of a company, and whether it can meet supply demand. Demand planning works to see that retailers have exactly the right amount of inventory at the right place to avoid stock-outs and remain prepared for that next sale.
But protecting sales isn’t enough anymore. It’s also about running businesses more efficiently. Demand planning assists with efficiency, by helping manage inventory space smarter. Why should companies invest in more physical space than they need? Demand planning can help businesses avoid the perils of overstocking — such as increased inventory carrying costs and financial situations that require the use of product discounts or other temporary measures to alleviate overstocking by selling inventory as quickly as possible.
Demand planning and forecasting is more crucial than ever, especially since so many outside forces — such as weather events, economic trends and global emergencies — can end up shaping and reshaping demand.
Effective demand management requires a comprehensive understanding of products and their respective lifecycles. Product portfolio management offers this, detailing a product’s complete lifecycle, from its origins until its eventual phase-out. And since many product lines are interdependent, product portfolio management shows you how shifting demand can affect “neighboring” products.
Working from the traditional concept that past history is usually the best predictor of future performance, statistical forecasting uses complex algorithms to analyze historical data and develop supply chain forecasts. The mathematics of statistical forecasting methods is advanced and the exacting process demands accurate data (including from outliers, exclusions or assumptions).
Demand sensing uses a combination of new sources of data, such as weather, infectious disease trends, government data and more, with historical trend data and applies AI to detect disruptions and demand influences in near real-time.
Survival in the retail jungle depends on sparking the interest of potential customers. Trade promotions and other marketing strategies use special events (such as discount prices or in-store giveaways) to spike consumer demand. Trade promotion management works to ensure that such opportunities are properly executed and deliver all expected benefits.
Organizations vary widely in how they approach the demand planning process, but there is a general set of steps that businesses typically follow. Those steps include:
In addition to establishing a precise set of implementation steps, successful companies usually engage in the following best practices for demand planning:
In order to process complex projections, effective demand planning requires ample amounts of data. Smart companies rely on metrics reports that help them prepare their data through increasingly sophisticated data mining and aggregation techniques.
There are numerous options when choosing demand planning software, but companies should try to be selective, based on their unique needs. Goal: Find a solution refined enough to reflect the subtleties of demand forecasting methods yet robust enough to handle reporting tasks.
Experienced demand planners typically begin their process by using descriptive analytics data to develop a testing baseline. Next, they shape the actual plan, devoting personnel and resources to cultivate and refine that plan, and then work on the exact implementation steps.
To be sure, the future is digital — and so is the outlook for demand planning. As demand forecasting in supply chain management becomes increasingly sophisticated because of advances in machine learning, companies will reap substantial benefits, such as being able to receive precise, real-time inventory updates and forecasts.
These continuing advances are drawing companies closer to the ideal promoted through demand planning. If an enterprise stocks just enough inventory to satisfy customer demand and withstand temporary market fluctuations, it’s able to run more efficiently and profitably thanks to its lean inventory strategy.
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