Global Fujitsu Distinguished Engineer
Tomoyuki Yamada
Message
At the forefront of data-driven value creation, I have a deep understanding of corporate business issues, taking the lead in constructing and optimizing a series of data analytics processes--from data collection and processing to feature engineering, advanced predictive modeling employing statistics and AI machine learning, and evaluation. I successfully led the application of AI to real business operations for customers across industries. Currently, going beyond the utilization of AI machine learning, I head a mixed team of data engineers and data scientists. Together, we're building a data utilization platform that supports everything from data collection, storage, and processing to optimization and decision-making. My work supports data-driven management innovation and business transformation on a global scale, accelerating the evolution of various industries by making full use of cutting-edge technologies.
Achievements
Consecutive Top Prizes Received From NEDO (New Energy and Industrial Technology Development Organization)
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NEDO Supply Chain Data Challenge (System Development category: Ports and Harbors, 1st place)
Team PPP — Platform for Procurement and Production
As the engineering leader, I developed a system to support procurement decision-making by quickly detecting maritime logistics delays based on satellite data and visualizing their impact across the entire supply chain. - (Japanse site)
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NEDO Challenge, Satellite Data for Green Earth (Development of Energy Management Infrastructure, 1st place)
Team ONS (Ocean Navigation Specialists) — Wave Height Map
As the engineering leader, I developed a wave height prediction map for forecasts of up to two weeks in advance, utilizing satellite data, other data, and AI. The map has a resolution of 1 km and an accuracy of ±1 m. We developed an ocean navigation app based on this map. - (Japanse site)
Lectures and Information Dissemination
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Instructor of DX courses for mid-level managers at public educational institutions
Every year, I deliver data and AI lectures for mid-level management at a public educational institution to help promote DX.
By explaining to the decision-makers in organizations the importance of data utilization, the latest AI trends, and how to apply AI in actual practice, I contribute to improvements in practical DX skills.
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My career and work as a data scientist featured in an article
Value Creation
1. Customer-oriented
I have streamlined business operations, reduced costs, and increased sales by leveraging data and AI. Under my lead with my strong capability to formulate hypotheses based on expert knowledge and rapidly apply technology to real business issues, the pace of business transformations was exceptional while I was solving complex customer issues and generating tangible results.
<Typical Success Cases>
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(Retailer) Leveraging AI to predict customer traffic and doubling the accuracy of human predictions
The model I built predicts customer traffic one month in advance according to the characteristics of all 160 stores. Working together with an automated ordering system, the model reduced the burden on store managers, reduced waste and lost opportunities, and optimized shift scheduling. - (Japanse site)
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(Retailer) Increased sales with a prediction model to automatically recommend orders for perishable goods
My model optimized the ordering of perishable goods. Combining various AI machine learning techniques such as clustering and regression prediction, the model learns from the order, sales, and other data of top-performing stores and recommends the optimal order quantities based on budget constraints. This reduced the burden on staff and led to increased sales.
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(Food wholesaler) Inventory optimization using AI-powered shipment prediction models
I built two models, one to predict the number of shipments of regular products through time-series machine learning, and one to predict the number of shipments of new products by utilizing product information and text data. They reduced workloads, reduced stockout risks, and optimized inventories.
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(Major manufacturer) Visualization and optimization of global production management
In two months, I achieved real-time visualization of changes in overseas production plans through automatic structuring of core systems and Excel data inside and outside Japan. Then, impact analyses and countermeasures could be automatically presented to Japanese factories, streamlining the coordination of production on a global scale.
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Improving quality and streamlining business operations with a traceability platform for the aviation industry
By integrating data such as the lot numbers, manufacturing processes, and inspection results of product materials across the ERP, PLM, and MES systems and building a traceable system, I reduced labor hours by 90%. This dropped returns from shipping destinations to zero and prevented production stoppages on factory lines.
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(Government offices) Enhancing policy-making by building an EBPM infrastructure
To strengthen competitiveness, improve productivity, improve management, and accomplish other aims of management entities in Japan, I integrated the distributed management entity information and application information to support data-driven policy formulation.
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(Government offices) Reducing costs through inventory optimization simulations
I integrated inventory, transport, procurement, and budget data for approximately 300,000 items into the inventory management system that was established in the 1970s and developed inventory and transportation optimization simulations. Quantified cost savings and optimized deployment strategies were the result.
2. Fujitsu internal-oriented
I built 30 business applications in three months to accelerate decision-making. The resulting data integration reduced costs and improved operational efficiency.