Improving demand forecasting accuracy is one of the main goals for demand planners within the fast-paced constantly changing F&B industry. As a demand planner, Demand Forecast Accuracy is crucial to your company's success because it enables you to optimize inventory levels, minimize stockouts, increase supply chain agility, and ensure you can meet customer demand efficiently.
However, demand forecasting in the F&B sector can be challenging due to factors like seasonality, product life cycles, and changing consumer preferences for which AI is playing a very important role to predict nowadays.
What are some strategic moves you need to make to improve your demand forecast accuracy?
- Leverage Actual Data – that is point-of-sale data. Collecting and analyzing real-time POS data provides extremely valuable insights into consumer buying patterns, market trends but also deficiencies within your operations process. Actual data helps you identify factors driving demand, such as promotions, weather, and holidays, new product introduction and cannibalization as well as anomalies.
- Use Market Trends and Consumer Behavior data – using Actual data is crucial for accurate forecasting but combining that with real-time market trends and consumer behavior data takes it to the next level of accuracy because you will be ahead of the game when consumer preferences, economic conditions and demographic shifts happen quick. Having this vast amount of data can help you identify drivers and signals the can help predict the future more accurately.
- Use Advanced Analytics Models that are Python based: Python is the new business language that lets you work quickly, easily integrate systems and come up with highly complex calculations, machine learning and AI-powered forecasting models. Python is an open-source language where users can easily contribute code, documentation, and add most recent accurate forecast models and/or apps that are constantly evolving and becoming more accurate.
- Engage and collaborate with all teams and departments: Engage with your sales, marketing, and operations teams to gain a holistic understanding of the factors influencing demand. Their insights can help you adjust your forecasts to account for planned promotions, new product launches, and other strategic initiatives.
- Use scenario planning: Develop multiple forecast scenarios based on best-case, worst-case, and most-likely outcomes. This will help you understand the potential impact of uncertainty and create contingency plans to mitigate risks.
- Monitor daily and adjust: Regularly review your forecasts and compare them to actual sales. Identify the root causes of any deviations and adjust your models and assumptions accordingly. Carefully look at your Forecast Value Add (FVA) from all your planners and models, drivers they are using to come up with the demand.
- Automate and streamline processes: Invest in demand planning software and tools that can automate data collection, model building, and forecast generation. Using Python based tools is key to better forecasting models due to its flexibility, scalability, AI/ML models - this will help you save time and reduce the risk of manual errors.
If you implement these strategies, as a F&B demand planner you can enhance your demand forecast accuracy, optimize inventory management, and improve overall business performance.
