It’s increasingly difficult to forecast demand accurately in today’s volatile, disrupted environment. Smart planning teams are turning to artificial intelligence.

Has there ever been a more challenging time to accurately predict demand?

Today, supply chain planners must contend with inflation, high interest rates and other economic forces that influence consumers’ buying behaviors and preferences. Planners must also consider extreme weather, social media trends and other unknowns that might suddenly create a demand peak — or valley. In addition, labor shortages, blocked shipping lanes and geopolitical uncertainty affect organizations’ ability to move products swiftly and profitably from Point A to Point B, which must certainly be part of the demand planning exercise.

While it’s always been difficult to predict demand, today these macro trends and complications create a cascade of challenges for demand planners. The current dynamic environment means that static monthly planning cycles are no longer enough. Instead, to keep pace with demand volatility, planners need to re-plan much more frequently, possibly up to several times a day, to reflect news, weather, economic trends and other influencing factors. However, planners are often limited by dated technology solutions that cannot support actual business requirements, iterative planning processes or today’s fast pace of change.

The High Cost of Outdated, Inefficient Forecasting Methods

Despite the error-prone nature of creating forecasts via manual analysis, static monthly planning cycles and consumer-grade spreadsheets, many demand planning teams still stick to their traditional methods. Why? Because change is difficult. It requires an investment in new solutions and new processes, as well as significant employee education and cultural transformation efforts.

When market volatility and disruptions cause planning teams to produce an inaccurate forecast via outdated, inefficient forecasting methods, the costs are incredibly high. The consequences include:

  • Lost sales and decreased consumer loyalty due to product shortages
  • The financial costs of markdowns, waste and excess inventory
  • Damage to crucial retailer relationships

The Only Comprehensive Solution? Artificial Intelligence

The truth is that most planning teams aren’t equipped to consider hundreds of relevant factors and arrive at an accurate forecast in a dynamic daily or intraday fashion. The scope, depth and pace of the required analysis exceed human cognition and consumer-grade tools — and historic sales data has become almost meaningless in today’s fast-changing landscape.  

Today successful organizations are empowering their demand planning teams with advanced, forward-looking, predictive technology solutions that are powered by artificial intelligence (AI). How is this accomplished?

  • Fueled by AI, modern decision engines can ingest huge volumes of real-time data from across the supply chain, as well as external sources like news, weather and social media, and arrive at optimal forecasts in mere seconds.
  • As conditions change, these “always on” engines dynamically adjust their predictions in real time to reflect new influencing factors. Invisibly and behind the scenes, they’re constantly creating more and more accurate predictions, enabled by AI capabilities that continually learn and improve.
  • In addition to making recommendations, AI-enabled decision engines further support decision-making by autonomously creating and analyzing hundreds of scenarios — then providing insights to planners.

AI represents the best way for demand planning teams to keep pace with the dynamic nature of today’s markets and make optimal decisions. For example, because new tariffs may follow the U.S. presidential election on Nov. 5, many American companies are stalling their offshore production efforts, while other companies are speeding imported products across the border. Probabilistic capabilities in advanced demand planning software can show the likely outcomes of both strategies. In addition, the analysis conducted by demand planning engines can have big implications upstream, downstream, and across the supply chain, if the planning team shares these kinds of predictions.

Can You Afford Not to Invest in AI?

As mentioned earlier, change is intimidating — and it often requires significant investments. But I would argue that, given today’s extreme volatility, companies are losing more by choosing not to invest in AI.

Smart companies are already capitalizing on the ability of AI to consider hundreds of demand-driving variables, plan dynamically and continuously, and generate ever-more-accurate forecasts. The benefits include enhanced margins and revenues, a greater return on inventory and other investments, higher shopper satisfaction, faster fulfillment and improved customer service. AI adopters also achieve a powerful competitive advantage as they anticipate and react to changing conditions faster than others in their industry. In addition, as AI-enabled engines do more of the work of forecasting autonomously, companies can also elevate their demand planners to more strategic, value-added roles.

AI-enabled, dynamic, real-time demand planning might sound futuristic, but it’s within the grasp of every company today.

Learn more about how Blue Yonder’s  AI-powered planning solutions are changing demand planning forever — and start seeing the benefits for yourself.