Automotive R&D Decision Support Ford Motor Company

Engineering Knowledge Search and Decision Tool

A VBA-based search and decision support system designed to reduce time lost to fragmented documentation, repeated investigation, and duplicated effort inside an engineering R&D environment.

Overview

This project addressed a knowledge access problem inside an engineering R&D environment, where critical information was distributed across documents, systems, and individual experience. Engineers were spending valuable time searching for past decisions, validating information, and recreating work that had already been done.

Rather than treating this as only a search problem, I approached it as a workflow and decision-making problem: where does knowledge break down, how does that slow engineering judgment, and what kind of support would fit naturally into the way engineers already work?

Problem Statement

The team relied on fragmented documentation spread across multiple sources, which made it difficult to locate trusted information quickly and confidently. This created delays, introduced avoidable uncertainty into decision-making, and led engineers to repeat analyses or retrace work unnecessarily. The challenge was to design a system that reduced this friction without requiring engineers to adopt a completely new way of working.

Key Challenges

  • Understanding how engineers searched for and validated knowledge across messy, real-world workflows
  • Designing a solution that improved speed and confidence while fitting into existing tools and habits closely enough to drive adoption

Research Process

Step 01
Workflow mapping and knowledge breakdown analysis
I began by mapping how engineers moved through the broader process of locating, checking, and applying technical knowledge during decision-making. This helped surface not only where information lived, but where breakdowns occurred between documentation, memory, trust, and action.
Step 02
Reframing retrieval as decision support
Rather than assuming better search alone would solve the issue, I examined how engineers judged whether information was reliable, how they compared sources, and where uncertainty caused them to pause, repeat work, or seek confirmation from others. This reframed the problem from document retrieval to decision support.
Step 03
Requirements translation and integration design
I translated workflow pain points into design requirements focused on reducing friction at the moment of use. A key design consideration was integration: the solution needed to fit within the team's existing environment closely enough that it would feel like a natural extension of their workflow rather than an additional layer of process.
Step 04
Iterative usability testing and refinement
Through iterative usability testing, I evaluated how well the system supported real engineering tasks, where interaction issues introduced hesitation, and what changes were needed to improve clarity, speed, and trust. Each round helped refine the tool so that it better aligned with engineers' mental models and day-to-day demands.

Impact

Efficiency Gains

Saved more than 200 hours annually for a 12-engineer team by reducing time spent searching, validating, and recreating prior work.

Rapid Adoption

Validated a workflow-integrated system that eliminated decision friction and supported rapid team adoption because it respected the realities of the engineering environment rather than forcing behavior change.