Intelligent Recommendation based Demand Forecasting using AI
Demand forecasting is the process of estimating the forecast of customer demand. One of the biggest challenges for most businesses is demand volatility in relation to demand forecasting, which is due to data growth and customer purchase patterns becoming complex.
If businesses forecast customer demand accurately, it can increase sales revenue and improves the decision-making process of cash flow, risk assessment, profit margins, and capacity planning to minimize the overstocking in inventory and workforce.
One of the retail business clients used to have problems like inaccurate manual forecasting, missing sales opportunities due to under-forecasting, overstocking in inventory, and gaps in logistics. To address these problems, we introduced our BIG-AI (Business Insight Generation using AI), which automatically understands the data and extracts insights to help businesses in data-driven business decision-making.
Demand Forecasting is pivotal to every business due to the process around which strategic and operational plans of a company are devised. Based on the Demand Forecast, strategic and long-range plans of a business-like budgeting, financial planning, sales and marketing plans, capacity planning, risk assessment, and mitigation plans are formulated.
Demand forecasting is used in retail, supply chain, manufacturing, FMCG, mining, logistics, marketing, etc.
The five most common influencers impacting forecasting and demand management are Seasonality, competition, geography, economy, and types of goods.
The key benefit of AI-powered demand forecasting can reduce errors by 40 to 60% in supply chain networks. The improved accuracy leads up to a 75% reduction in lost sales due to inventory out-of-stock situations and warehousing costs decrease around 20 to 50%.
The key benefits of demand forecasting with AI are
- Improvements in accuracy over time
- Higher customer satisfaction
- Improved workforce planning
- Improved markdown/discount
- optimization
- Overall efficiency
In conclusion, AI-based recommendation systems can provide valuable insights and recommendations across many aspects, from inventory management to logistics, demand forecasting, supplier selection, product recommendations, and quality control. By leveraging these systems, supply chain managers can improve efficiency, reduce costs, and increase profitability.
For further reference, visit our channel and refer the video named How Demand forecasting leverages Business Value Growth using BIG-AI or click the link
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