Pilot Program Begins for 'Digital SECI Model' Supporting Tacit Knowledge Transfer in Manufacturing

NTT Data Corporation and Fortiens Consulting, Inc. (formerly QUNIE Corporation) launched a pilot program in May 2026 for the "Digital SECI Model," designed to support the transfer of tacit knowledge in supply chain management (SCM) operations within the manufacturing industry. This initiative builds a unique framework utilizing AI agents based on the "SECI Model" of knowledge creation, advocated by Ikujiro Nonaka and Hirotaka Takeuchi, both former professors at Hitotsubashi University.

Targeting material procurement planning in manufacturing, the pilot formalizes decision-making perspectives—such as demand forecasting and material procurement judgments—through dialogues between experienced SCM professionals and AI agents. This process supports the development of less experienced staff and promotes knowledge sharing throughout the organization. NTT Data oversees the design and implementation of the AI agent foundation, while Fortiens Consulting manages knowledge and business design utilizing its SCM expertise. Through this pilot, both companies aim to advance knowledge transfer in the SCM domain and realize next-generation, knowledge-creating SCM powered by AI.

In recent years, the transfer of operational know-how has become a critical challenge in the manufacturing sector due to a shrinking labor force and a shortage of experienced staff. SCM operations, in particular, are considered difficult to standardize or manualize, as they rely heavily on the insights of experienced staff to navigate complex conditions, such as demand fluctuations, inventory status, procurement terms, and logistics constraints.

In this pilot, the companies combine Fortiens Consulting's expertise in SCM business and knowledge design with NTT Data's implementation capability for AI infrastructure to inherit the decision-making processes of experts. To achieve this, they will verify a system that continuously learns and updates decision-making viewpoints—"what experts observe and how they judge"—through dialogue with AI agents.

This pilot utilizes multiple AI agents to support the entire business cycle from preparation and execution to review of SCM plans. Specifically, two core AI agents will be implemented to verify their effectiveness:

1. Tutor AI Agent: In the planning phase, it suggests changes from previous plans, key points, business rules, and adjustment perspectives. Instead of providing the answer, it supports less experienced staff in deepening their own judgment by suggesting "which points to consider."

2. Interview AI Agent: It scores plan results and visualizes the quality of judgment. It engages experts and less experienced staff in dialogues to perform business reviews, record observations, confirm preconditions, and revise adjustment viewpoints. It draws out decision-making reasons and focal points that experts may not have fully articulated, continuously accumulating them as knowledge shareable throughout the organization.

Expected Effects:
- Transfer of expert SCM knowledge through formalization of tacit knowledge
- Improvement of judgment quality in SCM operations by promoting mutual learning between experts and less experienced staff
- Increased efficiency of the entire supply chain through improved judgment quality (e.g., shortening the cash conversion cycle and suppressing excess inventory).