When technology 4.0 exploded, all industries quickly caught up with the trend and had an amazing transformation. Demand forecasting is one of the activities that have been applying scientific and technical advances to increase the accuracy of their forecasting activities, significantly eliminating factors affecting forecast results. newspaper. According to McKinsey & Company Digital, AI-powered forecasting can reduce errors in supply chain networks by 30 to 50%. Improved accuracy results in a 65% reduction in lost revenue due to out-of-stock situations and a reduction in inventory costs by about 10 to 40%
Here are some benefits of applying AI to data analysis to make demand forecasts:

Improved visibility

One of the core benefits of AI technology is to help planners quickly update consumer needs, thereby helping businesses control the number of goods in stock. If issues occur, AI-powered analytics will notice them faster so you can make improvements more efficiently. For example, planners will be alerted when inventories are low or buffer stock levels are available allowing demand planners to take immediate action.

Reduce costs & increase inventory turnover

An uncertain demand forecast often brings a very high risk of inventory, the number of goods in the warehouse may be overloaded, or conversely, there is not enough stock to supply the market. Both cases affect the cost of the business. The application of digital technology helps to forecast the most accurate demand. Thereby minimizing the cost of handling inventory and increasing the inventory turnover in a certain period of time.

Improve cooperation among stakeholders

A unified analytics platform that gives your teams a common view of each department, channel, and store location. With everyone on the same page, communication improves and your teams work together more efficiently

Increase sale revenue

Advanced analytics ensures your stores have the products customers want when they're ready to buy. More accurate demand forecasting using resulting technology solutions can inform accurate future addition quantities and costs. This can reduce missed sales opportunities through running out of stock or offering discounts on over-stocked products. Excess stock takes up extra space, limits working capital, and can lead to increased costs for the business.

Increase the ability to expand the market

These cloud-based platforms process millions of data points in seconds, allowing them to scale with your business on demand. Add more stores, add new channels, and use more variables. Advanced retail analytics seamlessly integrates every aspect of your growing business.

Improve customer experience

The e-commerce space is becoming increasingly competitive and driven by customer demand. Ensuring product availability is key to ensuring customer loyalty and possible dissatisfaction due to out-of-stock. If a product is not available when and how they want it, there is a high risk that consumers will buy it from a competitor.

Conclusion:

Failure to meet the challenges of forecasting demand and supply causes the most difficult problems in retail from slow inventory turnover to GMROI anemia. But now you can get to the root of these problems.

State-of-the-art, AI-powered retail analytics allows you to leverage real-time customer demand forecasts to streamline your business:

• Eliminate costs and inefficiencies from your planning processes.
• Increase revenue, profit and market share.
• Consolidate your sales channels.
• Improve cooperation and communication.

General source