Use case
Supply chain modernization for faster business change
Overview
Value delivered
Redesign complex supply chain systems and modernize them to enable AI-driven development processes. By combining Uvance Wayfinders’ transformation expertise with Fujitsu’s technology and implementation capabilities, organizations can build agile business foundations that continuously adapt to changing market and customer needs.
Challenges

Increasingly complex supply chain systems
Solution approach

Business and systems redesign & AI-driven development
Results

Supply chain foundation built for change
Challenges
Complex business systems hindering supply chain transformation
System Complexity
Structures become increasingly complex through years of continuous upgrades
Slow response to change
Unable to rapidly adapt to changes in products or production methods
Higher development effort
Longer lead times from impact assessment through testing
Systems supporting supply chain operations tend to become increasingly complex after years of ongoing use and enhancement. At the same time, responding to changing business environments requires the ability to produce personalized products tailored to customer preferences within shorter timeframes and through high-mix, low-volume production models. What is needed is not simply modernization. Organizations need a system foundation that can continuously and rapidly adapt by incorporating changing business requirements and requests from customers and ecosystem partners in a timely manner.
What we do
Redesigning business and systems for AI-driven development
A transformation approach for business-resilient systems
Step 1
Assessing the current state and identifying issues
Assess the structure and challenges of current operations and systems
Step 2
Comprehensive redesign based on the target business model
Redesign each layer based on the target business model
Step 3
Transformation to AI-driven development
Leverage CI/CD and AI to shorten development cycles and accelerate business change
Wayfinders helps define the future business model while taking existing operations into account. Based on this vision, data, application, and infrastructure architectures are redesigned to support greater business agility. At the same time, an approach that maximizes the use of existing assets helps address accumulated technical debt efficiently. Development processes are transformed through CI/CD practices, and AI-driven development capabilities are embedded into the delivery lifecycle, significantly shortening development cycles and accelerating the implementation of business change.
Impact
Building a supply chain foundation resilient to change
Flexible system foundation
- A flexible architecture that is easier to change
- Transition to AI-driven development
Faster development and change
- Reduced impact scope of changes
- Shorter development and testing cycles
Greater business agility
- Rapid response to business changes
- Continuous productivity improvement
By applying AI to labor-intensive testing activities, which often account for nearly half of system enhancement efforts, and fully automating them through CI/CD-based processes, some organizations have achieved approximately 30% improvements in development and maintenance productivity within these activities. In addition, API-enabling high-change areas such as user interfaces and integrations with internal and external systems helps localize the impact of changes on core functionality. In some cases, this has reduced development timelines by approximately 20% compared with typical enhancement cycles. As the scope of AI adoption continues to expand, further productivity improvements and shorter response times can be expected.
Agentic transformation
The supply chain transformation featured in this use case is based on Uvance Wayfinders’ Agentic Transformation approach. Discover an approach to enterprise transformation for the AI agent era.


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