The Importance of Demand Planning for Retailers

Edited by Christian Thompson

Over the past two years, many large retailers have experienced supply chain issues due to COVID-19 and other macro factors leading retail companies to look for a solution to better forecast demand.

NWO.ai's signal for Retail Demand Planning

Demand planning is a supply chain management process of predicting product demand to ensure on-time delivery and satisfied customers. Demand planning aims to balance having enough inventory to meet customer demand without a surplus. Over the past two years, the impact score for “Retail Demand Planning” has increased by 172%, with the future estimate predicting growth in the coming months. We understand how vital demand planning is for companies, but which companies stand to gain the most from the process?

Clothing retailers have experienced complex supply chain strains causing overproduction and inventory surplus. Some companies that have been hit especially hard by a lack of demand planning are Macy’s, Gap, and Kohl’s. These larger retailers failed to account for the shift in consumer spending spurred on by rising inflation, causing overstocked warehouses. Over the past year, the impact score for “Clothing Demand Planning” has increased by 575%, with exponential growth in the future estimate. Another signal that has seen substantial growth is “Markdowns.” Over the past year, the signal has increased by 2746% and is forecasted to continue to grow in the coming months. The rapid increase illustrates how companies are dealing with overproduction by having to put products on sale and offer discounts. Don't be surprised if the summer sales continue.

Inflation concerns are contributing to the significant shift in consumer spending retailers currently face. Rising inflation has increased the prices of goods and shifted consumer spending away from discretionary spending to necessary expenses. The change in consumer demand is mainly responsible for the overproduction of products. Over the past year, the impact score for “Inflation” has increased by 138%. The future estimate forecasts steady growth throughout the following year, signaling that inflation may stay. We used our platform to compare the signals for “Food and Fuel Spending” versus “Discretionary Spending.” Over the past two years, the impact score for “Food and Fuel Spending” has increased by 479%, while the impact score for “Discretionary Spending” has decreased by 21%. This shows that consumer spending has shifted towards necessary expenses as people brace for continued inflation and a possible recession. The question remains: how will companies adjust to understand consumer demand better?

The future of demand planning lies with technology. According to McKinsey Digital, AI-powered forecasting can reduce errors by 30 to 50% in supply chain networks. The improved accuracy can foster up to a 65% reduction in lost sales due to inventory stocking issues. On top of all this, AI-powered forecasting can also decrease warehouse costs by 10 to 40%. Over the past two years, the impact score for “Demand Planning AI” has increased by 1395%, and the future estimate forecasts continued growth. Indicating retailers are beginning to realize the important role AI will play in demand forecasting in the future.


We hope you enjoyed this week's Inflection Point covering demand planning and the future of retail. Tune in next week and as always, have a great weekend.

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About NWO.ai
NWO.ai's predictive platform enables leading Fortune 500 companies and government agencies to anticipate and track global cultural shifts by aggregating, analyzing, and producing actionable reports on human-generated data. We are leveraging petabytes of external, noisy, and unstructured data from various sources including search, social media, blogs, news, patent databases, and SEC filings and we are continuously adding more sources. Our mission is to answer the what, when, and most importantly, 'why' behind a consumer trend and enable our customers to detect these shifts as early as possible.

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