Demand planning is an essential function in any organisation. Great Demand Planning can make your whole Supply Chain more profitable. The demand for any item changes depending on the season, the weather, new product launches, and many other factors. To be prepared for fluctuations in demand, manufacturers develop a detailed plan of how much inventory to keep at different times of the year and at different locations. This process is known as demand planning. We are currently seeing an explosive growth in AI adoption across all industries, which means demand planners will have plenty of new tools to leverage while working within their existing processes.
Here are five areas to explain how artificial intelligence is upending demand planning. They each explore a specific use case for AI in demand planning and include examples of companies using it effectively today.
By analysing past sales data, AI can predict future demand with more accuracy, making your supply chain more profitable
One of the most basic functions of demand planning is to forecast future demand. Traditionally, demand planners have done this manually by looking at past sales data to predict what customers are likely to buy in the future. Manual forecasting is time-consuming and error-prone. If a planner makes a mistake, the entire forecasting process must be repeated from the beginning. Artificial intelligence offers a more accurate way to forecast demand. AI can analyse past sales data to understand what customers have bought in the past and why. This allows AI to predict future demand with more accuracy than manual forecasting. AI can also learn from the data to improve its forecasting over time. This means demand planners are able to focus on the areas of their job that require human intelligence rather than on data collection and analysis.
AI can identify and eliminate waste in the supply chain.
One of the key objectives of demand planning is to minimize inventory and maximize customer satisfaction. AI can help planners identify where they should reduce inventory and where they can increase it. AI can analyse existing customer data to determine the best lead times for different items. This enables planners to reduce inventory without sacrificing customer service. AI can also analyse data to track inventory and identify areas where waste is occurring in the supply chain. This can help planners reduce the amount of inventory that is lost to spoilage or breakdown. It can also help planners identify the likely cause of breakdowns and thereby prevent them from occurring in the future. These improvements help to make your supply chain more profitable.
AI can detect fraudulent behaviour to ensure more reliable forecasts.
AI can also help planners identify any fraudulent behaviour in their customer data. This can happen when a customer orders more products than they need in order to resell them for a profit. AI can identify patterns in customer data that indicate fraudulent behaviour and can help planners eliminate it from their data. This enables AI to generate more reliable forecasts.
AI can help manufacturers find the best sourcing locations for their products.
Supply chain planners must decide where to source the raw materials used in their products. AI can help with this process by analysing the availability of raw materials and their price across the globe. AI can then use this data to determine where it is most cost-effective to source raw materials. This can help planners source materials in locations with the lowest costs while maintaining the quality of the products. You may also want to be aware of potential changes in Foreign Exchange rates. We discuss how those risks can be mitigated here, https://palmai.io/insights/how-ai-can-help-you-manage-foreign-exchange-risk-in-your-supply-chain/
AI can help manufacturers find the best locations for new production plants.
Planning the optimal location for a new production plant is no easy feat. Demand planners must account for many different factors including the amount of raw materials that are available in the region, the cost of labour, and taxes and regulations. While these challenges have always existed, the advent of AI has provided manufacturers with new tools for tackling them.
Conclusion
Demand planning is an essential function in any organization that makes or plans to make products with limited shelf life. The demand for any item changes depending on the season, the weather, new product launches, and many other factors. To be prepared for fluctuations in demand, manufacturers develop a detailed plan of how much inventory to keep at different times of the year and at different locations. This process is known as demand planning.