Development of Supply Chain Digital Rehearsal Technology for Medium- to Long-Term Supply Chain Strategy Planning to Prepare for Various Uncertainties

February 27, 2026

In recent years, corporate supply chains have been exposed to growing levels of uncertainty due to climate change, geopolitical risks, logistics disruptions, rising material costs, and changes in consumer demographics caused by urban development. These uncertainty scenarios have the potential to significantly impact procurement, logistics, manufacturing, and sales operations-making it increasingly difficult to manage risks using conventional methods.
To address this challenge, Fujitsu has developed Supply Chain Digital Rehearsal, a technology that supports medium- to long-term strategic decision-making under such uncertain environments.

Key Features of the Technology

Impact analysis and forecast by scenario
The technology models the entire supply chain—from procurement and logistics through manufacturing and sales—as a network. It conducts exhaustive impact analysis and forecast by scenario to identify how various uncertainty scenarios may affect different parts of this supply chain structure.
Derivation of improvement measures
In addition, the system automatically performs the derivation of improvement measures, such as expanding procurement sources or modifying logistics routes, to minimize the impacts identified in the scenario analysis.

The system’s outputs not only match expert assessments but also provide additional insights with high accuracy and quality across multiple perspectives—including cost performance and delivery time.

Details of the Developed Technology

Fujitsu has developed a proprietary simulation technology that integrates AI with domain-specific business expertise. This technology enables:
comprehensive Impact analysis of uncertainty scenarios, including the extraction of intermediate factors and the prediction of medium- to long-term time-series changes, and the derivation of improvement measures from among thousands of potential options, including those that may not have been previously considered.

1. Impact Analysis and Forecast by Scenario

Risk Scenario Analysis
Based on public and enterprise-specific information, the system analyzes how uncertainty scenarios influence each part of the supply chain. It automatically extracts causal chain graphs, including intermediate factors, enabling a comprehensive understanding of how an event propagates to eventual impacts.
Scenario Forecasting
For each factor in the causal chain, the system automatically generates a change scenario, altering how future developments may evolve. It then forecasts medium- to long-term time-series changes in key indicators such as supply–demand balance and price levels for each change scenario

2. Derivation of Improvement Measures
The system automatically proposes optimal improvement measures—including expanding procurement sources, switching logistics modes, adjusting inventory strategies, and consolidating sites—selected from thousands of candidates.
These measures are evaluated across multiple criteria such as cost, delivery time, inventory level, and environmental impact, enabling the identification of practical and highly effective strategies.

In a joint verification project with a major food company, we conducted a trial of our technology on the company’s product supply chain. Specifically, we applied an uncertainty scenario that assumed the closure of the Suez Canal due to geopolitical conflict in the maritime transportation of raw materials.
Using this scenario, we tested (1) impact analysis and forecast by scenario, and (2) the derivation of improvement measures provided by our technology.

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Results of the Technology Trial

Comprehensive impact analysis of the uncertainty scenario
The system identified that detouring maritime transportation around the Suez Canal led to longer transit times, while securing vessels in parallel became increasingly difficult. These factors caused delays, which ultimately resulted in reduced inventory levels of raw materials.
Through this analysis, the system was able to comprehensively capture the full chain of impacts—including intermediate factors such as detours and difficulties in securing vessels.
Forecasting medium‑ to long‑term time‑series changes under the uncertainty scenario
For multiple change scenarios that varied the degree to which cargo volumes increased due to the Suez Canal closure, the system forecasted the medium‑ to long‑term time‑series changes in maritime freight rates.
Comparisons with past real-world cases confirmed that the system accurately captured the characteristic sharp increase in freight rates, thereby validating the soundness of the technology.
Derivation of multiple improvement measures to minimize the impact
In addition to reproducing the measures proposed by experts, the system generated appropriate improvement measures—such as alternative logistics routes—evaluated from multiple viewpoints including cost. These system‑derived measures were highly evaluated by the food company for their precision and practicality.

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Developer Comments

Converging Technologies Laboratory Development Team Members

Masami
Mizutani

Miwa
Ueki

Takeshi
Ohtani

Toshio
Ito

Eiichi
Takahashi

Satoshi
Amemiya

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Akira
Karasudani

Takayuki
Baba

Hiroshi
Otsuka

Susumu
Ogata

Hiroaki
Takebe

Kazuho
Maeda

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Nobuhiro
Miyazaki

Susumu
Endou

Soichiro
Kuribayashi

Hisaya
Kobayashi

Kozo
Baba

Akinori
Miyamoto

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Our project develops Supply Chain Digital Rehearsal technology to support medium- to long-term strategy planning for customers in a wide variety of industries—including manufacturing, logistics, retail, and construction. This technology conducts comprehensive impact analysis and scenario forecasting for various uncertainty scenarios, and automatically derives improvement measures such as supply chain structural changes, including the expansion of procurement sources or modification of logistics methods.
We have validated the usefulness of this technology through retrospective simulations based on actual cases experienced by customers. Moving forward, we will continue advancing joint verification and research & development to help optimize supply chains—an essential component of business operations—through advanced technologies.

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Future Initiatives

Fujitsu will continue to strengthen and validate this technology for broader deployment across multiple industries. Through comprehensive scenario-based impact analysis and multi-dimensional derivation of improvement measures, this technology aims to contribute to more resilient and sustainable supply chain operations.