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Ford Motor Company - GDI&A (MWATS)
Background
In 2024 Ford motor company spent over 5 billion on warranty repair costs. These problems fall into several buckets, supplier error, manufacturing issues, or under-designed parts. Worst still some of these problems are caught and not properly documented leading to the potential for the issue to pop up again on the same vehicle, a sister vehicle line, or another vehicle line using a similar part. With Fords rate of production roughly 5-6 vehicles per minute globally with some factories producing a vehicle every 50 seconds problems compound quickly.
Objectives
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Reduce the time for a problem solver to find the root cause of a program.
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Increase adoption of the product.
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Democratized the data available to problem solvers by helping users make sense of the data in real time.
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Reduce the back and forth between our qlicksense dashboard and our web tool.
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Reduce the problem solving burden on the global 6 sigma team.
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Decommission old tools by bringing them into our web application.
Research Methodology
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Conducted extensive user interviews were conducted with more than 20 business partners to understand everyone's problem solving journey.
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3 key personas were identified, Global 6 sigma team, Plant quality engineers (PVTs) and executive level.
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We then did follow up interviews with key business partners to determine the overlap of the different problem solving processes and where the key pain points were.
*AI generated image to obscure real internal process
Key Findings
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For most plant level personal they need results in real time.
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Most plant personal only care about their specific commodity for the vehicles run in their plant.
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For most PVTs they would only investigate a few problems a year with our tool, meaning there is little opportunity to use the tool. But when they need it it's critical
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For the Six Sigma team trust in the data and the ability to slice and dice data to tell a compelling story was critical.
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For executives they do not necessarily have the stats background to understand they data so easy to follow non technical visualizations are critical.
Strategic Roadmapping &
Continuous Alignment
To ensure the vision remained actionable, I translated the high-level flow into a comprehensive Figma framework. This "wholistic tool" map allowed the team to pause and resume specific feature designs—sometimes 3 to 6 months later—without losing contex.
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To maintain agility, I facilitated quarterly prioritization workshops with the Product Owner, Lead Data Scientist, and Tech Anchor.
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By syncing design with developer velocity and data science milestones, we created a living backlog that stayed resilient to shifting business requirements.
Lessons Learned
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Journey mapping is great for breaking down complex processes but for management it's best to give them a summary in the form of User Personas
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