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Unifying Machine Configuration
komatsu
CLIENT
Komatsu
SERVICES
UX Research
Project Management
TECHNOLOGIES
Figma / Aha! / Teams
METHODOLOGIES
Stakeholder Interviews
Contextual Inquiry
User Testing
Executive Summary
The Challenge: Machine configuration across global regions relied on a disparate, siloed ecosystem of product-specific tools. Deployment and system engineers faced a highly manual, time-consuming process—installing IP addresses, drivers, interfaces, and servers individually. This fragmentation created severe UX inconsistencies, increased human error, and delayed deployment timelines.
The Solution: As the Lead Product Designer, I spearheaded the research and design of a single, universal configuration interface. Integrated into the company’s new ecosystem initiative, this solution unified machine settings across all product lines and addressed the fragmented workflow.
The Impact: Consolidating workflows eliminated duplicate data entry, automated high-friction tasks, and reduced the cognitive load for global deployment teams, resulting in a measurable improvement in system usability.
Research & Discovery
To design a scalable system, we built a dual-track research framework that combined quantitative benchmarking with deep qualitative inquiry to capture the complexities of the global ecosystem and guide the next phase of design.
Quantitative Benchmarking
Methodology: System Usability Scale (SUS) Survey.
Execution: The team and I deployed a standardized SUS survey to engineering teams using the legacy solutions. This established an objective numerical baseline for current system satisfaction and a clear metric for later comparison.
Qualitative Inquiry
Methodology: Comprehensive Research Plan, Remote User Interviews, and Contextual Inquiries.
Execution: The team drafted a structured research plan targeting a diverse group of internal stakeholders. I conducted over 12 qualitative interviews and contextual inquiries with global Deployment and System Engineers across multiple regions.
Synthesis: To parse the dense technical feedback, we synthesized the raw data into a collaborative Affinity Map. This clarified behavioral patterns, isolated systemic pain points, and categorized user desires across different product environments.
Strategic Approach & Ideation
The research insights showed that engineers were bogged down by repetition and high risk of data loss. Balancing stakeholder technical requirements with UX best practices, we introduced a design strategy focused on efficiency and cognitive offloading.
Familiar Design Patterns: To minimize friction, reduce switching costs, and prevent user confusion, we retained the system mental models engineers trusted and wrapped them in a modernized, cohesive design language.
Bulk Configuration Engine: We introduced a simultaneous multi-unit modification tool, turning a highly repetitive, linear task into a streamlined parallel workflow.
Consolidated Data Ingestion: By mapping system architectures, we eliminated duplicate fields and centralized user inputs, minimizing human error.
Automation & Resilience: We introduced system-wide autosave states and increased backend automation, removing the risk of data loss during server/IP configuration.
Competitive Grounding: This strategic direction was vetted and validated against enterprise industrial standards through a comprehensive Competitor Analysis, ensuring our platform met top-tier market standards.
Execution & Validation
Evaluative Usability Testing
Upon finalizing the interactive high-fidelity designs, the team and I returned to our user base to validate the work and complete the research cycle.
Methodology: Task-Based Usability Testing.
Execution: We ran validation sessions with global stakeholders and deployment engineers, testing the new universal design against their traditional machine configuration methods to measure task completion speed, error rates, and qualitative satisfaction.
Outcomes & Key Takeaways
The Results
Positive Sentiment Shift: Follow-up interviews showed a sharp reduction in execution anxiety due to the new autosave and automated pipelines.
Quantifiable Success: The post-validation data showed an overall positive trend, resulting in a significantly higher System Usability Score (SUS) compared to the legacy benchmark.
Professional Reflection
This project underscored the importance of UX advocacy within complex, highly technical enterprise environments. I learned that designing a successful system requires more than technical design skills—it requires healthy, trusted relationships and ongoing rapport with global engineering teams and product stakeholders. By treating research participants as collaborative allies, we amplified their voices, uncovered deeper insights, and transformed a fragmented process into a unified, enterprise-grade solution.
