Playbooks
The Playbooks.
The problems we fix most often, and how we'd attack each one. No promised percentages - just the approach, so you know exactly what working with us looks like.
The close that takes two weeks
The problem · Books close on day 12. By the time you see the month, you can't do anything about it, and half the month's decisions were made blind.
How we'd attack it · Map every step between the last transaction and the final number. Most of the delay is three or four manual reconciliations waiting on one person. Automate those, move the rest to a hard cut-off, and accept a flash close that's 95% right on day 3.
What you end up with · A flash P&L within 72 hours of month end, and a documented close calendar that doesn't live in someone's head.
Pricing built on old cost assumptions
The problem · The price list was built when labor, materials and insurance cost what they cost three years ago. Nobody rebuilt it. Margin erodes quietly and gets blamed on volume.
How we'd attack it · Rebuild unit cost from current actuals - fully loaded labor, real material cost, real overhead absorption. Then re-price against it and find where you're underwater. Usually it's concentrated in a few line items, not spread evenly.
What you end up with · A current cost model you can re-run, a revised price list, and a defensible story for the customers whose price moves.
The back office that can't take another customer
The problem · Invoicing, AP, collections and payroll all run on someone typing. Growth means hiring another someone, so margin doesn't improve with scale.
How we'd attack it · Time-study the transactional work, find the highest-volume repeatable steps, and automate those first - not the interesting ones, the boring frequent ones. AI matters here for document handling and matching, not for strategy.
What you end up with · Documented workflows, the top two or three automated end to end, and a headcount plan that no longer scales one-to-one with revenue.
Job-level profit you can't see
The problem · You know total revenue and total cost. You don't know which jobs, crews or customers make money - so you can't fire the bad ones or bid the good ones harder.
How we'd attack it · Attribute real labor hours and materials down to the job. Most of the work is getting time capture honest, not building a report. Then rank every recurring account by contribution margin.
What you end up with · A ranked list of your accounts by what they actually earn you, and the three you should re-price or let go.
The week that falls apart when it rains
The problem · One weather day cascades. Crews idle, routes get rebuilt by phone, and the recovery costs more than the lost day did.
How we'd attack it · Establish what a disrupted week actually costs you - idle hours, windshield time, the jobs that slip past their service window. Then build the recovery rules before you need them: what gets protected, what slides, who decides.
What you end up with · A written disruption playbook your foremen can run without calling you, and a real number for what weather costs per event.
Customers who quietly stop calling
The problem · Attrition doesn't announce itself in this business. A property drops off the route and it takes a season to notice the revenue is gone.
How we'd attack it · Define what "still a customer" means in service intervals, not in feelings. Flag accounts that have gone quiet past their normal cadence. Most recoverable churn is a missed follow-up, not a lost bid.
What you end up with · A churn definition that fits how this trade actually works, and a weekly list of accounts worth a phone call.
Don't see your problem here?
We scope the work in the first week of every engagement - these are just the most common starting points.
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