Retail AI Forecasting Analysis Deep Predictor Demand Forecasting Service
No-code AI predictive analytics and decision support service Deep Predictor
No-code AI demand forecasting service usable by on-site personnel.
In the retail industry, responding to demand fluctuations and optimizing inventory are crucial. In particular, it is essential to minimize the risks of food waste and unsold goods while maximizing profits. Deep Predictor supports the resolution of these challenges through high-precision demand forecasting and the calculation of optimal order quantities. 【Use Cases】 - Store inventory management - Sales forecasting for seasonal products - Calculation of optimal order quantities 【Benefits of Implementation】 - Inventory optimization - Reduction of food waste - Decrease in ordering workload
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basic information
【Features】 - High-precision forecasting considering external factors - Easy to implement and simple to operate - Automatic calculation of optimal order quantities - Strong design for forecasting other items as well - Provides a high-precision demand forecasting platform using AI algorithms
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Delivery Time
※Preliminary verification (optional) will take 1 to 3 months, and the implementation will take about 1 month.
Applications/Examples of results
**For such challenges:** ● **Optimization of Inventory** We accurately forecast future demand to minimize the risks of excess inventory and stockouts. There are cases where inventory optimization has led to cost reductions of several tens of millions of yen annually, contributing to improved profit margins. ● **Optimization of Personnel Allocation** Based on forecasts of shipping and sales volumes, we can optimize the shifts of warehouse staff. This helps to control costs due to overstaffing and delays in operations caused by staff shortages, enabling efficient personnel management according to peak and off-peak periods. ● **Optimization of Production Planning** By utilizing forecasts of sales and shipping volumes, we can develop highly accurate production plans. AI predictions lead to reduced lead times, lower production costs, and improved profitability through inventory optimization. ● **Reduction of Ordering Workload** By calculating the optimal order quantity based on accurately forecasted demand, we achieve a reduction in ordering workload and eliminate dependency on specific individuals. ● **Reduction of Food Waste** Utilizing forecasts in material procurement planning helps to minimize inventory waste. This reduces missed sales opportunities and contributes to the reduction of food waste. *For more details, please refer to the PDF document or feel free to contact us.*
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Company information
Our company actively engages in technological innovation and creates efficient communication infrastructure based on predictive models utilizing machine learning, thereby generating new value in communication.
![[AI Prediction Implementation Case] B-R 31 Ice Cream Co., Ltd.](https://image.mono.ipros.com/public/product/image/770/2000737415/IPROS05984121210789003016.png?w=280&h=280)
