Every Employee Quit (On The Same Day!)

Business-focused summary (Lindley Home Services roll-up / ETA playbook)

Company strategy & roll-up thesis

Nathan Lindley is building an HVAC roll-up primarily in the Southern US / Texas (DFW + Austin) under a unified brand, aiming to rapidly create value by:

• Systematizing KPIs and operational playbooks across acquired locations (rather than depending on the seller’s historical performance).
• Buying “at-bats” (traffic / leads / booking volume) instead of focusing on the target’s historical EBITDA/SDE.
• Replacing mispriced, discretionary, or structurally constrained revenue, such as:
  • contractor-dependent channels
  • new construction lines that aren’t supported by the acquiring ops model

He frames the roll-up as a value-creation engine:

• Economies of scale
  • dispatch
  • removal of duplicated admin/CSR functions
  • insurance and overhead consolidation
• Multiple expansion
  • combining several smaller, lower-multiple shops into a larger, systematized entity

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Core operating playbooks & frameworks mentioned

Incentive alignment (commission-first operating model)

• After finding weak incentive correlation (pay not tied to revenue/output), he shifts from hourly/salary to straight commission.
• The goal is to ensure sales effort is driven by the same outcome metrics the business needs.

KPI development before scaling

• Early-stage mission: define and refine operational KPIs, including:
  • booking rate
  • call productivity
  • conversion
  • gross margin dynamics
• Once KPIs stabilize, the acquisition logic shifts from “buy EBITDA” to buy opportunity/at-bats.

The “at-bats” framework (batting average → expected outcomes)

• Acquire enough lead/phone volume (the “at-bats”).
• Then estimate outcomes using internal conversion and profitability ratios.
• Rationale: seller results reflect many prior decisions, while the buyer can change the chain of decisions, including:
  • booking
  • conversion
  • pricing
  • overhead allocation
  • training
  • staffing

Pricing & overhead unit economics

• He challenges naive pricing like “cost + 15%” as insufficient for service businesses.
• Instead, he computes overhead per service call and uses it to evaluate:
  • break-even contribution per job
  • parts vs. installed solution unit economics

Management layering & culture reset

• Expect key employees to leave; treat churn as part of integration.
• Use turnover as a mechanism to install the buyer’s culture rather than inheriting the seller’s operating norms.

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Concrete examples & decisions (what changed and why)

1) First acquisition (Feb 2020): new industry + weak partner vetting → early catastrophe

Business profile

• Revenue: ~$850,000–$1,000,000/year (target)
• Price/financing: $850,000 via SBA 7(a)
• Debt service: ~$9,000/month
• SDE multiple: described as about 3x range

Key issue

• Revenue depended heavily on a small set of general contractors, which he lost immediately post-acquisition.

Integration failure driver

• His technical partner was strong technically but weak on business operations.
• No established KPI benchmarks; COVID removed reliable baseline expectations.

Result

• Struggled through 2020–2021, with problems intensifying after scaling.

2) Second acquisition (Nov 2020): faster scale → working capital burn

• Deal size: $285,000 cash

Integration issue

• Revenue leaned on new construction, but the buyer’s model wasn’t set up for it.
• He cut out some revenue; kept about $1.5M out of what he realized would be misaligned.

Outcome

• In 2021, he burned ~$250k–$300k (described as “insane”).
• Burned cash and working capital; needed new outside capital (friend invested $100k, which he also burned).

Incentive misalignment

• Hourly/salary structure was unlinked from revenue, leading to volatile periods (example: payroll high while revenue low).

3) “Every employee quit” turning point (March 1, 2022): forced commission + immediate execution

By March 2022

• Checking account: ~$2,000
• Last payroll had just been made

Decision

• Switch everyone to straight commission
• He describes that day as effectively the point where the team had to leave, and everyone quit.

Then

• He had previously extended an offer to a sales candidate who wanted commission.
• New hire started shortly after; he temporarily had near-zero staff before ramping.

Reported transformation

• The first commission sales rep could produce roughly $3k–$5k/day early on.
• Previously, total company activity was far lower despite having other technicians.

4) KPI-based operating targets: fewer calls but higher quality per call

• He got hands-on in the field and set a guideline:
  • Technicians only run ~3 calls/day
• If technicians run more, revenue per tech declines due to:
  • less time for quality experience
  • lower conversions / opportunity capture

Impact

• Higher conversion + more pre-booking stability reduces feast/famine volatility.
• He models headcount growth while protecting fewer calls to cover more demand.

5) Acquisition “strike zone” evolves into repeatable math

• Early thinking: ~$250k revenue/tech/year to justify SBA payback.
• After KPI refinement: revised lens to about ~$1M revenue/tech/year.
• As in-house KPIs improve, the seller’s “out-of-the-box” metrics matter less than the new system.

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Key metrics & numbers mentioned (sales/ops/finance)

Financing, deal sizes, and debt strategy

• Deal #1: $850,000 (SBA 7(a)); debt service ~$9k/month
• Deal #2: $285,000 cash
• Deal #3: ~$350,000 total (stated: $150k cash + $200k seller note)
• Deal #6: $700,000 (SBA note) closed Aug 2024

Revenue per technician expectations

• “Dying” period: $200–$500/day per technician (stated range)
• Later expectation: $800k–$1M/year revenue per tech

Debt-service target

• Aim for debt service ~10% of revenue
• Example given: if ~20% net margin, then 100–200% debt coverage feels manageable

Operational call productivity

• 3 calls/day per technician (operator guideline/KPI)
• Overhead per call: ~$400/call (allocated overhead estimate per serviced call volume)

Commission output example

• New commission rep: $3k–$5k/day in early consistent selling output (claimed)

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Acquisition tactics (what he actually buys)

He emphasizes he’s not paying for the seller’s operational excellence—he’s paying for:

• customer lists
• databases
• lead volume
• brand/phone funnel

Examples of “value” extraction:

• Subcontractor-heavy model (Deal #4): 100% subcontractors, almost no assets
  • structured as percentage of revenue because value is effectively the lead generation
• Bankruptcy case (Deal #5): bought phone number + database for $37k cash after underwriting wasn’t bankable

Lead-gen uncertainty structures

• Revenue share: year one 15% of revenue, years 2–6 10% of revenue (as described for the subcontractor lead-gen deal)

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Playbook for buyers: due diligence philosophy & execution responsibility

Delegation not abdication

• Don’t rely on banks/attorneys/CPAs as guarantees of deal quality.
• He warns that:
  • banks can approve bad loans
  • buyers can still sign PGs (personal guarantees)

Expert verification

• Trusted experts can help, but “expert” quality must be tested.
• He advises continuing underwriting and due diligence even when using professionals.

Due diligence is the buyer’s job, not the lender’s or advisor’s.

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Roll-up integration lessons (what breaks in M&A)

• Employee turnover (primary issue)
  • key employees will likely leave, especially when compensation/expectations change
  • turnover is painful but enables culture reset
• Key employee retention should not be assumed
  • even “20-year” sellers’ people may leave once comp/process changes
• Inherited suboptimal performance
  • older/satisfied sellers may run “contentment ops,” causing avoidable inefficiencies to be inherited
• You must learn the job in the field
  • operating knowledge helps uncover pricing/process leaks, such as:
    • cost structure blind spots
    • inventory waste
    • dispatch failures

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Additional operational tactics he highlighted

• Inventory tracking discipline
  • shuts down logistics/inventory workflows when parts are ordered incorrectly or in excess and end up obsolete
• Route / daily operational learning
  • learns frontline pain points before designing better processes (comparison: learning how lawn mowing works)
• Avoid “side business” delusion
  • warns against absentee/passive expectations; even if physically absent, the owner remains mentally responsible

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Reported growth / organization build

By the post-turnaround period (after Mar 2022), staffing was described as:

• ~7 technicians in Dallas
• 2 in Austin

Pipeline context:

• An additional Austin deal was described as APA signed, targeting “six or seven” technicians as a future acquisition focus.

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Actionable recommendations distilled from his guidance

• Build your KPI system before expecting roll-up results
  • booking, conversion, gross margin requirements
  • overhead per call
  • technician throughput (e.g., calls/day rule)
• Align incentives with outcomes
  • use commission or equivalent performance-based structures to connect effort → revenue
• Use “at-bats” thinking
  • model acquisition value from lead volume + your conversion profitability, not seller EBITDA
• Make pricing unit-economics explicit
  • include overhead and labor/service delivery, not just part cost + markup
• Plan for churn
  • expect departures after comp/process changes; treat it as an opportunity to install your culture
• Own underwriting decisions
  • don’t let bank optimism or advisor outputs replace buyer understanding

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Presenters / sources

• Presenter/Source: Nathan Lindley, CEO, Lindley Home Services (HVAC roll-up across the Southern US / Texas)
• Other people referenced: No additional primary presenters in the provided subtitles; other figures (e.g., “Walker D,” search fund references, LinkedIn commenters/figures like Kira Hamilton) were mentioned as context only.