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AI for Demand Forecasting and Inventory Planning in Retail

Advanced data analytics is now a table-stakes tool for inventory planning. Some estimates show that applying AI-driven forecasting can reduce errors by between 20 and 50 percent, reducing lost sales and product unavailability by up to 65 percent. Sharper demand forecasting also reduces waste and unsold products that need to be marked down or liquidated. Although the complex array of variables and multiple sources of uncertainty ensure demand forecasting will always require some art along with the science, if managed correctly, a data-driven approach can mean the difference between growth and underperformance. Leveraging AI for demand forecasting and inventory planning in retail is a great opportunity for businesses to consider; retailers are particularly seeing opportunity in these three key areas: automation, articulate demand prediction, and reduction of overstock and stockouts. 

3 Areas Retailers Can Leverage AI


AI is well known and widely used for mimicking human productivity, but the key to unlocking AI’s true potential is not to think of it as a replacement, but instead, as an enabler for people to move away from manual, tedious tasks, and move into a space where they can be creative and think strategically about how an organization can grow. AI is being used for demand and inventory planning in leading organizations to automatically update purchase recommendations and ordering plans based on real-time information and eliminate human error. Answering questions like, What will my future sales be? What should my inventory levels/assortment look like? What inventory do I have now? What is being delivered currently, and how might delays affect my supply chain? 

AI offers the ability to inform future sale predictions and current stock levels as well as raises flags when an order is at risk of a supply delay. Plans are updated based on the latest information and can incorporate any number of demand and supply constraints, leading to a more realistic and up-to-date replenishment plan. 

Articulate Demand Prediction  

AI and ML have unlocked new potential for more accurately predicting demand both for existing products as well as new SKUs. For existing products, historical information can be leveraged to predict demand based on seasonality and consumer purchasing patterns. Well-integrated AI takes the generated demand forecast and predicts downstream implications related to inventory planning and production scheduling to execute against the projected demand. Further, AI’s distinctive strength is its ability to forecast demand for new SKUs by leveraging data from similar products to forecast for the new product. As data for the new product is available, it automatically updates the forecast. 

Some supply chain AI solutions can predict incoming disruptions by analyzing the weather, financial trends, geopolitical issues, and other shifts. They can then recommend changes to mitigate the impact of otherwise disruptive events. 

AI also has the capability to gather demand Insights based on consumer trends by ingesting data sets from customer sentiments to anticipate needs. AI enables sentiment analysis by processing large amounts of data from various sources such as social media, online reviews, satisfaction surveys, emails, etc. This analysis helps detect positive and negative customer opinions as well as emerging trends. Such insights can assist companies in understanding customer motivations and concerns, anticipating future needs, and adjusting their strategies and demand plans accordingly.  

Reduction of Overstock and Stockouts 

Predictions about demand shifts and disruptions are only as helpful as an organization’s ability to adjust its inventory accordingly. ML offers more reliability, as it can track inventories in real time and doesn’t make data entry errors. Before the pandemic, the supply chain was relatively predictable, and supplier lead times were more or less stable. However, that’s no longer a given, so ML can be leveraged to adjust for supplier unpredictability and create ordering plans that are increasingly accurate as more data is available for the supplier. If there is a trend for longer lead times, then ordering plans can be adjusted to accommodate the impact and reduce stockouts. Preventing stockout and overstock situations saves the business money and ensures customer satisfaction with timely order fulfillment. 

By employing AI, businesses can make informed decisions based on these insights, whether optimizing reorder points, managing supplier relationships, or adjusting pricing strategies. The result is smarter, data-driven decision-making that contributes to overall business success. 

Future of AI and Human Collaboration in Inventory Planning 

The use of AI and ML is developing as a standard across the industry and can take organizations to the next level of resilience; however, the collaboration of humans and AI is where a company can thrive the most.  

Tomorrow’s supply chain managers will use AI to inform virtually every decision and likely automate many small actions, like ordering and billing. The final decision — especially in terms of company-wide strategic changes — will still fall to humans, who must interpret AI’s insights. Pure AI models may struggle to accurately predict demand during significant market fluctuations and unexpected events, like Barbie’s immense success and push for all companies to suddenly produce something pink. This is where knowledge from Marketing or other organization groups is critical to obtain more accurate and refined forecasts and inventory balances. Ultimately, humans are responsible for leveraging the tool in combination with their expertise and outlook on the situation to refine inventory strategies as needed to sustain success for the organization. 

Every evolving technology landscape and suite of functionality will continue to lead with AI and more deeply integrate AI and ML into the everyday practices of demand and inventory planning teams. If your organization has questions about how best to take a first step with generative AI technologies, let’s connect. Our retail supply chain analytics experts are passionate about solutions that may fit your needs.   

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Tags: Artificial Intelligence