When Ridgeway Industrial Fabrication invited our AI discovery agent “Dave” into the shop, the goal wasn’t to judge performance—it was to map reality: how information actually moves from RFQ to shipment, where handoffs wobble, and where a little automation could free people to do their best work. Over several weeks, Dave conducted structured conversations across the company—26 confidential employee interviews spanning production, engineering, sales/estimating, administration, and leadership.
The Discovery Method: Short Conversations, Big Signal
Dave’s process is simple and fast:
- 10–15 minute interviews with employees in every function.
- A consistent question set that uncovers roles, responsibilities, success metrics, dependencies, and bottlenecks.
- Live capture of pain points and examples (e.g., where a quote stalls or a drawing gets reworked).
- Synthesis into a single source of truth leaders can act on immediately.
At Ridgeway, these conversations highlighted a familiar pattern for growing manufacturers: people are doing great work while fighting disconnected tools—manual spreadsheets for quoting, paper-based production schedules, and engineering rework caused by Sales–CAD misalignment. None of this is about effort; it’s about flow.
What We Found (and Why It Matters)
From the interviews, five high-leverage opportunities stood out:
- Quoting delays from starting every request from scratch.
- Scheduling conflicts driven by paper systems.
- Engineering rework when RFQ details don’t sync with quotes/POs.
- Vendor surprises due to weak lead-time visibility.
- Knowledge loss risk as craft know-how lives in veteran heads, not systems.
Employee sentiment was encouraging: 77% were open or enthusiastic about AI, with a smaller group concerned about job impact—an important signal to design change with people, not at them.
The Collateral You Receive
Every engagement generates plain-English, decision-ready deliverables you can put to work immediately:
- AI Discovery Briefing—a narrative summary of how the organization actually operates today, in the team’s own words.
- AI Organizational Discovery Report—consulting-style slides that quantify the pain points, name internal champions, and lay out a sequenced roadmap.
- Champion Map—the cross-functional group (at Ridgeway: Production, Engineering, Admin, Sales) ready to lead pilots.
- Before/After KPI targets—cycle time, error/rework rate, on-time delivery, and throughput improvements tied to each pilot.
The 12-Month Roadmap (Built for Busy Teams)
Ridgeway’s plan is pragmatic and paced for a 26-person shop:
Phase 1 – Foundation (Months 1–3)
Form an AI Sponsor Committee, run two short workshops (“AI for Manufacturing” and “How to Prompt”), and clean the data you already have—ERP exports, quote sheets, production logs.
Phase 2 – Pilot (Months 4–6)
Launch two low-risk, high-signal pilots:
- AI-Assisted Quoting (learns from past quotes + material costs to recommend pricing).
- Tribal Knowledge Capture (structured interviews with senior machinists to preserve expertise).
Both pilots keep humans in the approval loop and measure time saved, rework avoided, and quote hit-rate lift.
Phase 3 – Scale (Months 7–12)
Roll out predictive scheduling once cleaner data is flowing; integrate Sales–Engineering handoffs to kill rework; stand up a live operations dashboard for quoting accuracy, utilization, and lead times. Recognize early adopters publicly to lock in culture change.
Expected Results (What Good Looks Like)
Based on Ridgeway’s baseline and targets:
- Quoting speed: from 5–7 days to 48–72 hours.
- Print-to-BOM errors: cut to <2% with automated extraction and checks.
- Rework tickets: down to ≤1/month as Sales–CAD alignment improves.
- Throughput: +10–15% from scheduling and documentation discipline—without adding headcount.
Equally important, the report frames AI as a friction remover—not a headcount reducer. Clear guardrails (privacy, usage, accuracy checks) and transparent communication address concerns about jobs and model reliability.
Why “Dave” Works for Fabricators
Success here isn’t about “perfect data.” It’s about repetitive pain points that your people already know by heart. Dave captures those realities fast, turns them into measurable pilots, and gives your champions the structure to win small and often. That’s how Ridgeway moves from AI-curious to AI-capable—without losing the craftsmanship and customer relationships that made the company successful in the first place.
Download the full deliverable:
Ridgeway Industrial Fabrication - Organizational Discovery Report
