Handyman services Operations Questions
The questions that recur in handyman services share one shape: the job is small but the drive is not. Sub-$200 tickets go unprofitable once drive time is honest, platform bookings carry five times the no-show rate, and a second tech halved margin instead of doubling revenue. The answers below cost the hour honestly before pricing the job.
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Platform bookings carry 5× our no-show rate at identical job sizes. What does the platform customer owe us that the direct customer does not?
Nothing, and that is the answer. The direct customer made a relational commitment (conversation, referral chain). The platform customer made a click. Commitment is an input you can engineer: deposits, confirmation calls, and narrower windows convert platform demand into committed demand.
§13 behavioral ops, §2.3 accommodating demand, §8.1 abandonment psychology
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Our best customers eventually hire a specialist directly. Which service is the gateway they stop calling us for first?
The highest-stakes one. Usually electrical or plumbing work where perceived risk exceeds generalist trust. That is rational: your order winner is convenience for low-risk jobs. Specialists own high-risk ones. Decide whether to refer out gracefully (keeping the relationship) or lose the whole customer by fumbling the handoff.
§1.1 OrderWinner, §6.1 perceived quality, §11.2 make-vs-buy logic
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Do we lose money on sub-$200 jobs once drive time is honest, and why do we keep taking them?
Allocate drive time and the answer is usually yes. You keep taking them for relationship seeding and schedule-filling. Legitimate if priced as marketing, ruinous if priced as revenue. Create a minimum charge or bundle small jobs into route days.
§4.1 financial resource, §10 routing, §2.3 backlog accommodation
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Why does materials markup vary by which hardware store is nearest rather than by policy?
Because there is no policy. Markup is decided per-trip by whoever drives. That is an ungoverned pricing activity producing random margin and occasional customer distrust. Write the price book: markup schedule plus a sourcing rule, and the variance disappears.
§0.3 governedBy, §5.1 consumables, §13 standard work
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Which do we chronically underbid: trades-adjacent jobs or odd jobs nobody quotes?
Trades-adjacent: you estimate them with handyman heuristics against specialist risk (code, inspection, callbacks) you do not price. Odd jobs are priced by pure judgment but carry no hidden tail. Audit margins by job class. The regulated-adjacent work will show the leak.
§9 risk, §6.2 external failure, §4.4 work measurement
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Average ticket grows yearly while jobs-per-day falls. Emerging strategy or failing scheduling?
Check the cause: if bigger jobs are chosen (mix shift), it is emergent strategy. Codify it. If drive time and gaps are growing, scheduling is failing and ticket size is just mix noise. Decompose jobs-per-day into drive, gaps, and on-site hours.
§1.1 deliberate vs emergent strategy, §7 scheduling, F1
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What percentage of "I will text you a price tonight" jobs do we win, and why do we keep doing it?
Track it: typically under half the on-the-spot quote rate, because evening quotes land after the customer's urgency cooled and competitors quoted live. You keep doing it to protect the day's schedule. If the win-rate gap is real, the schedule is eating the pipeline.
§1.1 OrderWinner speed, §2.3, §8.1
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Customers ask for half-day/full-day packages. We persist hourly. Packaging failure or pricing fear?
Pricing fear. Hourly feels safe because it transfers overrun risk to the customer, but customers read hourly as open-ended cost anxiety. Day-rate packages convert overrun risk into a premium you can price. Test one packaged SKU against hourly on matched jobs.
§2.3 pricing/demand shaping, §6.1 perceived quality, §13
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Adding a second tech halved margin instead of doubling revenue. Which constraint did we hit: sales, scheduling, or supervision?
Diagnose by the invariant: if the pipeline did not double, you hit demand (A2: throughput is capped by min(capacity, demand), and you elevated the wrong constraint). If jobs were there but days fragmented, scheduling. Post-hoc, the P&L split will show idle hours vs. missing jobs.
A2, A3, §16 TOC exploit → subordinate → elevate
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When a customer becomes a repeat, what was the first job, and should we engineer more of those?
Pull the cohort data: repeat customers almost always trace to a first job that was urgent, small, and flawlessly executed. The trust trial. If so, treat that job class as your acquisition product: price it to win, staff it with your best, and instrument the 90-day callback rate.
§2.2 cohort analysis, §1.1 OrderWinner, §6.3 SERVQUAL reliability
How these answers work
Each answer names the operational mechanism the question is circling, then states the directive that follows from the ontology in Part One of the book. Bracketed citations point to the ontology sections and axioms that produced the answer. Figures inside the questions describe each stipulated scenario. They are not industry benchmarks.
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