Plumbing Company Stops Losing Jobs to Slow Quotes

The Challenge

Tom’s plumbing company had a quote problem.

When a customer called for an estimate on a bathroom remodel or water heater replacement, here’s what happened:

1. Office takes the call, writes down details on paper
2. Paper goes in Tom’s inbox
3. Tom (eventually) reviews and creates quote—often 2-3 days later
4. Quote gets emailed to customer

By day 3, half those customers had already hired someone else.

Tom knew this was costing him jobs. But he was the only one who could create accurate quotes. His 15 years of experience meant he could estimate jobs quickly and accurately—but that knowledge lived entirely in his head.

His office manager couldn’t quote. His technicians couldn’t quote. Only Tom could quote, and Tom was busy running a company.

What We Did

We focused our Operations Audit specifically on the estimating process, extracting Tom’s pricing knowledge into a systematic framework.

Knowledge Extraction We sat with Tom through 30+ quotes, documenting:

• How he assessed job complexity
• What factors affected pricing
• Common job types and their typical ranges
• Red flags that increased estimates
• Questions that determined scope

Quote Builder System We created a structured quoting tool that:

• Walks through standard questions for each job type
• Calculates estimates based on Tom’s actual pricing logic
• Generates professional proposals automatically
• Tracks quote status and follow-ups

Process Documentation

• When to quote immediately vs. when to schedule a site visit
• How to handle price objections
• Follow-up timing and scripts
• Escalation criteria (when does Tom need to be involved?)

Training We trained Tom’s office manager on the system with clear guidelines:

• Jobs under $2,000: Quote immediately using the system
• Jobs $2,000-$5,000: Site visit, then quote using the system
• Jobs over $5,000: Tom reviews before sending

The Results

Week one:

• Office manager sent her first quote without Tom’s involvement
• Customer booked the job same-day
• Tom didn’t find out until the end-of-day review

After one month:

• Average quote turnaround: 3 hours (down from 3 days)
• Close rate increased from 35% to 47%
• Tom’s personal time on quotes dropped by 80%

After three months:

• 85% of quotes handled without Tom’s involvement
• Additional $12,000/month in revenue from faster response
• Office manager confidently handles most customer pricing questions

The math:

• Previous: 40 quotes/month × 35% close rate = 14 jobs
• After: 40 quotes/month × 47% close rate = 19 jobs
• 5 additional jobs × $800 average = $4,000/month
• Plus jobs previously lost to competitors: ~$8,000/month
• Total revenue impact: ~$12,000/month

Key Takeaway

Tom’s quoting expertise wasn’t magic—it was pattern recognition built over 15 years. Once those patterns were documented, they could be applied by anyone with the right system.

The bottleneck wasn’t capability. It was that knowledge was trapped in one person’s head.

This case study represents a composite of typical client engagements. Specific details have been adjusted to protect client confidentiality while accurately representing the types of challenges we solve and results we achieve.