Key Benefits of Using AI and Tools for Demand Planning
- Improved Forecast Accuracy: AI-powered demand planning tools leverage large data sets and advanced algorithms to predict demand with greater accuracy.
- Increased agility: AI can dynamically adjust demand forecasts in response to real-time data, enabling rapid adaptation to market changes.
- Reduced Inventory Costs: Optimized demand forecasts lead to better inventory management, thereby reducing the need for excessive safety stocks and reducing storage costs.
- Improved customer satisfaction: Responding to demand without constraints, without delays or shortages, guarantees a higher level of customer satisfaction, leading to increased loyalty.
- Data-Driven Decision Making: AI tools provide actionable insights, enabling demand planners to make informed decisions based on data rather than intuition.
- Efficient resource allocation: By automating demand planning tasks, human resources can focus on strategic initiatives, improving overall productivity.
- Sustainability: Optimized demand planning reduces waste by minimizing overproduction and reducing spoilage, which is essential for sustainability efforts in the FMCG industry.
By deploying real-time demand monitoring and adjustments, FMCG companies can use AI tools to track real-time sales data, adjust forecasts instantly, and alert demand planners of sudden changes in demand. This enables dynamic, near real-time adjustments to production and inventory levels, ensuring that demand is met without excess, leading to a reduction in response time to fluctuations in demand, thereby reducing the risk of lost sales due to to peak demand and reducing waste due to excess. inventory.
Customer segmentation and personalization uses AI to segment demand based on customer demographics, purchasing behavior and regional trends, enabling personalized marketing and promotion strategies. This ensures that supply is closely aligned with demand from different customer segments and results in increased customer loyalty through targeted promotions, maximization of product profitability and better alignment of production with demand at a granular level.
FMCG companies’ use of AI-driven scenario planning and simulation creates demand simulation models that allow planners to test multiple scenarios (e.g., new product launches, changes prices or competitive actions) and their impact on demand across the portfolio. This shaping of demand allows planners to optimize inventory levels under various conditions and allows businesses to prepare for market fluctuations, improves strategic planning by reducing uncertainties, and improves decision making by simulating different market conditions . Demand shaping levers include traditional promotional activities, advertising or social media influencers, and the tactic can be used to better balance limited supply and demand to improve profitability.
Inventory and replenishment optimization will always be hot topics – and topics that keep CPG executives up at night. AI algorithms help optimize inventory replenishment processes by predicting when and where inventory levels should be restocked based on forecasted demand, demand errors, and replenishment. This approach minimizes out-of-stock situations while avoiding overstocks, reduces carrying costs associated with excess inventory, ensures product availability across all channels, and reduces transportation costs by optimizing replenishment cycles. These benefits, in turn, drive sales growth potential and increase market share.