Tokyo, 104-0044,
Japan
Tokyo System Research
Tokyo System Research, a prominent reseller, system integrator, and consulting company, that plays a vital role in numerous system integration and digital transformation initiatives. Tokyo System Research collaboration with software players such as IBM empowers organizations to embrace disruptive technologies and accelerate their journey to the cloud, thus reshaping their business models.
| Reseller and SI | Vendor | Application | Category | Market |
|---|---|---|---|---|
| Tokyo System Research | IBM | IBM Watson Explorer Content Analytics | Analytics and BI | Analytics and BI |
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Product | Category | When | Insight |
|---|---|---|---|---|---|---|---|---|---|---|
|
|
Honda | Automotive | 30000 | $60.0B | United States | IBM | IBM Watson Explorer Content Analytics | Analytics and BI | 2016 |
In 2016 Honda deployed IBM Watson Explorer Content Analytics to analyze very large volumes of unstructured customer feedback for quality assurance in Japan. The IBM Watson Explorer Content Analytics deployment sat in the Analytics and BI category and was focused on automated extraction and classification of parts and symptom issues from customer reports and warranty comments.
The implementation relied on Watson Explorer content analytics capabilities, including text indexing, natural language processing based extraction, and automated classification and categorization workflows to surface recurring failure modes. Configuration work emphasized taxonomy development, rule sets for symptom and part identification, and search and exploration interfaces for QA analysts to validate classifications.
Implementation was led by IBM Global Business Services with Tokyo System Research as the implementation partner, and the solution ingested high volumes of unstructured feedback from Honda operations in Japan for centralized analysis. Outputs from the content analytics environment were operationalized into quality assurance workflows to route classified issues to parts and symptom specialists for investigation.
Project governance established standardized classification labels and review processes to ensure consistent issue tagging across teams, and rollout included analyst training and iterative refinement of extraction rules. Honda reported that the use of IBM Watson Explorer Content Analytics reduced the time to interpret and classify feedback by about 80 percent, a benefit captured directly from the implementation case details.
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Buyer Intent: Companies Evaluating Tokyo System Research Services
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