AI Efficiency Makeover Before a Sale — $95M Field Services Business

Intro

Buyers don’t discount you because they hate your business. They discount you because they don’t trust your plumbing. Dispatch chaos, slow invoicing, and inconsistent documentation scream “future surprises.”

This anonymized case study shows what BuildClub would implement ahead of a strategic sale—and the results you should expect when the work is executed fast and tied to KPI proof.

Profile (anonymized)

• ~$95M annual revenue
• Multi-location industrial equipment / facilities services provider
• 11 branches across 5 states
• EBITDA margin ~9%
• Strategic sale in sight within 9 months

The situation

This company would have sticky contracts and long-term customer relationships, but operations would be old-school.

Dispatch & scheduling

• Whiteboards, spreadsheets, and phone calls
• Techs would zigzag across town while nearby jobs were planned “later”
• First-time fix would be stuck around ~63%

Billing

• Invoices would go out ~10–20 days after job completion
• Change orders would be missed or under-billed

Customer experience

• No unified asset history
• Key accounts would complain about inconsistent updates and surprise invoices

Potential buyers would like the revenue base but would already be talking about a discount.

BuildClub Solution

1) AI dispatch & routing

• Consolidate data:
  • ~3 years of work orders (~220k jobs)
  • Technician skills, certifications, and home bases
  • SLAs and site access constraints
• Add an AI layer that would:
  • Suggest optimized daily routes (minimizing travel, honoring SLAs)
  • Match jobs to techs based on skills and past fix performance
  • Flag likely repeat-visit jobs so parts could be pre-staged

Expected results (after ~6 months)

• Tech utilization: 62% → 72% (billable vs paid hours)
• First-time fix: 63% → 76%
• Truck rolls per job down ~12%

Expected financial impact

• Efficiency equivalent to ~14 tech FTEs at ~$95k fully loaded
• Growth absorbed with the same team (instead of cutting headcount)
• EBITDA benefit: ~+$1.0M/year
• Fuel and maintenance savings: ~+$280k/year
• Total dispatch EBITDA impact: ~+$1.28M/year

2) Quote-to-cash automation with LLMs

• Deploy an LLM “job-to-invoice” assistant that would:
  • Convert field notes + photos into structured line items
  • Generate clear descriptions and recommended pricing, including change orders
  • Draft customer-ready work summaries and follow-up emails
• Back office would review and post invoices quickly, with fewer disputes and fewer missed billables

Expected results (after ~5 months)

• Time from job completion to invoice: 11.5 days → 2.7 days
• Properly billed change orders up ~18%
• Write-offs tied to bad documentation down ~$350k/year

Expected financial impact

• Working-capital benefit from faster billing ≈ $1.4M
• Extra recognized revenue ≈ $1.1M/year
• At ~30% incremental margin → ~$330k EBITDA
• Reduced write-offs: +$350k EBITDA
• Total quote-to-cash EBITDA impact: ~$680k/year

3) Customer & asset intelligence layer

• Combine service history, asset-level issues, and SLA performance per account
• Make it queryable in natural language, e.g.:
  • “Summarize the last 12 months at Site 14.”
  • “Which assets are driving the most emergency calls?”

Expected results

• Clearer proof of recurring revenue quality
• Evidence of upsell/cross-sell opportunities
• Lower perceived churn risk in key accounts
• A “data-rich platform” story instead of a “nice tuck-in” story

Expected pre-transaction outcome (run-rate, ~9 months)

• Revenue: ~$95M → ~$101M
• EBITDA: ~$8.6M (9.0%) → ~$11.0M (~10.8%)

What typically drives the EBITDA delta

• Dispatch: +$1.28M
• Quote-to-cash: +$0.68M
• Overhead & small wins: +$0.4M

Valuation impact (illustrative)

• Before: ~8.5x on ~$8.6M → ~$73M enterprise value
• After: ~10x on ~$11.0M → ~$110M enterprise value

Even with conservative attribution, this would typically protect/create ~$20–30M of value by fixing operational plumbing before a buyer prices the risk.

If you’re heading into a process

If you’re going to market soon, fix dispatch, billing, and documentation first. It’s the difference between “premium platform” and “please holdback 20% in escrow.”

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