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Automation of Order to Shipment Operations in the Food Industry - Φ-Conductor

Automation of Order to Shipment Operations in the Food Industry - Φ-Conductor

A business solution that automates and supports decision-making for order allocation and delivery conditions of food products with expiration date management, as well as shipping instructions arranged according to shipping routes.

**Feature 1**: Maximizing Order Response Capability [Arrangement Simulation] - Instantly calculates all arrangement methods, including inventory from multiple warehouses, expected arrivals, substitutes, and suppliers, to navigate delivery options for incoming orders. - Avoids missed sales opportunities due to stock shortages when orders come in, while keeping inventory to a minimum. **Feature 2**: Enabling High-Quality Operations for Anyone [Automation/Semi-Automation of Arrangements] - User-friendly screen design - Allows for instant understanding of the situation and enables optimal decision-making and execution of arrangements for shipping, horizontal transfers, and ordering. - Detailed business scenarios - Implements detailed business scenarios for all possible cases that may arise in operations. - Φ-Conductor navigates "what to do next," allowing operational staff to make rational and optimal decisions and instructions. **Feature 3**: Advanced Inventory Allocation Engine Capable of Responding to Dynamic Changes - Capable of allocation tasks that require complex inventory attributes and time management, such as time-specific allocations. - Resolves the complexity and confusion in operations caused by variations in "usable inventory" for the same product due to factors like expiration dates, customer-specific inventory, and origin specifications.

  • Order management system
  • Sales Management System
  • Inventory Management System

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[Φ-Pilot Implementation Case] Sekisui Medical Co., Ltd.

[Φ-Pilot Implementation Case] Sekisui Medical Co., Ltd.

Evolving towards precise supply and demand planning based on data!

Improving Demand and Supply Planning Supported by Data and Interdepartmental Collaboration with Φ-Pilot [Challenges Before Implementation] ◼ The main tasks involved collecting and processing information from multiple Excel files and core systems. ◼ With a wide variety of low-volume products and inspection items, time spent on information gathering led to insufficient checks for stockouts. ◼ The tasks were left to individual employees, resulting in stockouts and losses due to differences in their capabilities. ◼ There was a need for a system to centralize information so that departments could communicate using the same data. [Countermeasures and Implementation Effects] ◼ Excel processing tasks were eliminated, allowing focus on demand and supply operations. ◼ Inventory and shipping statuses are now clearly displayed, enabling quick decision-making and detailed inspections, significantly improving the quality of demand and supply management. ◼ Standardizing information display in Φ-Pilot allows for consistent operations even during personnel changes. ◼ Coordination with marketing and sales can now be based on concrete numbers, enhancing operational efficiency. This has made adjustments for new products and responses to stockouts smoother.

  • Purchasing Management System

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[Φ-Pilot Implementation Case] Tominaga Trading Co., Ltd.

[Φ-Pilot Implementation Case] Tominaga Trading Co., Ltd.

Achieving a 30% reduction in food waste! Introducing examples that have also contributed to raising awareness and morals regarding food waste.

We would like to introduce a case study of the implementation of the "Φ-Pilot Series" at Toin Trade Co., Ltd. It had become difficult to manage inventory control of products with different shipping deadlines for each manufacturing lot using only Excel. As a result, there were delays in noticing issues, leading to losses due to expired shipping deadlines, as well as risks of stockouts. With our product's expiration date monitoring system, we successfully detected products that were likely to expire in the future early on and took proactive measures, resulting in approximately a 30% reduction in losses. [Case Summary] ■ Challenges - Losses due to expired shipping deadlines - Risks of stockouts ■ Implementation Effects - Successfully reduced losses by approximately 30% - Stockouts have become almost nonexistent

  • Inventory Management System

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