What is demand planning?

This process helps organizations decide where their money should make operational decisions about procurement, supply planning and inventory management.

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 and supply chain planning to accurately predict demand trends. It carries added benefits, such as heightened company efficiency and increased customer satisfaction.

The approach is used to optimize workflows, automate tedious tasks and drive strategic decision-making.

Demand planning is critical to an effective supply chain, serving two essential functions.

First, there always exists the fundamental drive to protect the sale and generate the expected revenues. But retailers can’t sell what they don’t have in stock.

It doesn’t take long for today’s consumers to develop a lasting impression of a company and whether it can meet supply and 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. The second essential function of demand planning is to help run businesses more efficiently. Demand planning assists with efficiency by helping manage inventory space smarter and improving forecast accuracy.

Why should companies invest in more physical space than they need? Demand planning can help businesses avoid the perils of overstocking. The issues might include 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 also gives supply chain managers accurate forecasts so new product releases can be scheduled in the time frame with the highest likelihood for profitability.

Demand planning and sales forecasting are 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.

Demand planning is built on a range of different practices that work cohesively to predict demand and respond proactively when changes do occur.

Organizations vary widely in how they approach the demand planning process, but there is a general set of steps that businesses typically follow:

• Organize and prepare data: Collect, clean and standardize all relevant internal and external data sources, including from an enterprise resource planning (ERP) system. Validate data for accuracy, completeness and timeliness before analysis.

• Make a preliminary forecast: Generate an initial demand forecast using historical data and baseline assumptions. Data needed can include sales data, historical data, out-of-stock rates and more, depending on the organization’s needs. Document key drivers, constraints and known risks, such as excess inventory or information silos.

• Integrate market data: Incorporate current market trends, customer insights and competitive intelligence into the forecast. Adjust assumptions to reflect external demand signals and market conditions.

• Reconcile bottom-up and top-down forecasts: Compare bottom-up forecasts from operational teams with top-down strategic targets. Resolve gaps through cross-functional review and alignment in areas like sales teams, supply chain managers and distributors. Consider scenario planning in this step to compare different outcomes.

• Develop a final forecast: Refine the forecast based on agreed assumptions and reconciliation outcomes across stakeholders within the organization. Approve and publish the forecast for execution and planning.

• Use analytics to monitor project performance: Track forecast accuracy and demand variability using defined metrics and dashboards. Use insights to correct deviations and continuously improve planning.

In addition to establishing a precise set of implementation steps, successful companies usually engage in certain best practices for demand planning:

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 (ML), companies will reap substantial benefits, such as being able to receive precise, real-time inventory updates and streamlining forecasts.

These continuing advances are drawing companies closer to the ideal promoted through demand planning. If an enterprise stocks 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.