Inside a Bohaus Sprint: A Garage Door Company

The situation

The client is an owner-led garage door and overhead door company doing residential repairs and installs, plus some commercial overhead doors. Five service trucks, an install crew, a warehouse corner with parts and doors, a dispatcher, and an office manager. Housecall Pro or ServiceTitan runs dispatch and invoicing. QuickBooks runs accounting. Parts are tracked, loosely, in a spreadsheet.

Two problems show up every week. Techs arrive at a broken spring or a stripped opener and the right part is not on the truck, so the job becomes a second trip. And quoting on site is slow: the tech calls the office for a price, or guesses, and the homeowner waits in the driveway.

The owner wants AI to fix quoting. Every conversation ends the same way: our parts data is a mess, so we should clean it up first.

What the sprint finds

In Discover, we look at the data honestly.

It is messy, as almost everyone's is. The same torsion spring appears under three names. Opener models are listed by old and new part numbers. Some prices in the field service platform are current; others are from two price increases ago. The spreadsheet of truck stock was accurate once. Nobody knows what is actually on each truck.

A full cleanup of every part, vendor and historical job would take months and compete with service calls. It would stall.

In Diagnose, we turn the question around. On-site quoting and truck stock rank first. So what do they actually need? The parts that make up most repairs and installs, current prices, standard repair packages, and what each truck should carry. They do not need clean data for discontinued doors or every commercial part ever ordered.

That makes the cleanup defined and finishable.

What it builds

In Build, we clean what quoting and stock depend on. Common springs, cables, rollers, openers and door models are de-duplicated and given one name and number. Prices are confirmed with the owner. Standard repairs are built as packages: spring replacement, tune-up, opener install.

Then we build on-site quoting inside the field service platform. The tech picks the repair, and the system offers good, better and best options from the price book, with photos. The homeowner approves on the tech's tablet.

Each truck gets a standard stock list. Parts used on a job are deducted from that truck's stock. At day's end, the system builds a restock list for the morning.

When a tech uses a part that is not in the clean list, the system flags it. Each flag is a small fix for the office manager.

Hand over

In Hand over, the office manager and the lead tech learn the system in depth. Techs get a short session on quoting with packages and logging parts. The playbook covers the price book, the restock routine and simple rules to keep data clean: one part, one name; new parts added only by the office manager; prices reviewed when a supplier changes them.

The team gets a dashboard of quotes presented and approved, second trips and restock needs, plus a roadmap.

What changes

Techs quote in the driveway without calling the office. Homeowners see clear options and decide on the spot. Second trips for parts become less common because trucks are restocked from what was used. The parts list improves as a side effect of using it. The owner stops waiting for a cleanup that was never going to finish.

What this means for your business

Waiting for perfect data is waiting forever. Choose the first system, clean only what it needs, build checks that flag problems, and fix the process that created the mess.

A garage door company cleans its parts and truck stock. A small distributor cleans its item list and customer pricing. An electrician cleans the price book.

Every Bohaus Sprint includes a tool and data inventory in Discover so the first system is built on data good enough for the job. Six weeks, fixed scope, one live system, and a team trained to run it.