Once you’ve determined what you hope to get out of SCM, the next step is assessing customer demand. Demand forecasting is the process of predicting what products your customers want and resourcing against that demand with the right amount of inventory. Done well, demand forecasting will help you make better buying decisions to replenish your stock at the right time.
Determining what your customers want, when they want it, and how much they want is no easy task. Analyzing your business’s historical data, coupled with the rate at which your business is growing today (i.e., online and offline traffic and corresponding conversion rates), will help inform your future inventory needs. In addition to understanding your business’s growth trajectory, you’ll need product-level sell-through data. When analyzing your sell-through data, take into account variables like seasonality, promotions, or other events that may have influenced sales. There will almost always be a margin of error, but the closer you can forecast, the better you’ll be able to maximize profit.
Utilizing analytics, software, and technologies such as artificial intelligence (AI), which uses real-time data to predict demand, can improve the accuracy of your demand forecasting and save time. The case for AI is especially promising, with AI-driven demand sensing shown to reduce inventory errors in supply chain management by up to 50%, according to McKinsey & Co.