A Spaid engineer rides with your top performers, documents every diagnostic and close decision, and converts it into a system any tech can use — delivered through the FSM job card they’re already looking at.
Tribal knowledge isn’t just a retention risk. It’s a daily performance gap that compounds every time you hire, every time a veteran tech is out sick, and every time a new branch opens without a playbook.
New techs operate at 60–70% of veteran GM and callback performance for 6–12 months. At $20K–$40K in slow-ramp cost per hire, a shop hiring 8–10 techs/year is bleeding $160K–$400K annually in below-target performance before the new hire reaches full productivity.
$20K–$40K in slow-ramp cost per new hireEvery branch runs differently because the “standard” is in the DM’s head. One branch runs 38% GM. Another runs 28%. Nobody can explain the gap in a way that’s trainable.
8–12 pt GM spread branch to branchWhen a lead tech leaves, callback rates climb, GM drops, and the next hire starts over. No system captures what made the top performer effective — it walks out with them every time.
3–6 month recovery window per senior departureMost knowledge transfer programs fail because they’re built from generic content. Ours is built from what your top performers actually do — job by job, objection by objection.
Off-the-shelf HVAC or plumbing training that doesn’t reflect how your best tech runs a job in your market.
New tech follows a veteran for two weeks. No structure, no documentation, no way to replicate at scale.
Based on how management thinks jobs should go — not how the best performers actually run them.
Content libraries that nobody opens. Completion rates high, behavior change rates low.
Engineer rides with your best tech and documents every diagnostic decision, pricing logic, and close technique — not what they say they do, what they actually do.
Converts observed patterns into a structured system — each job type has its own decision tree, objection handlers, and documentation standard. Built from your data, not generic best practices.
Surfaces the right knowledge for the specific job type before the tech arrives — parts checklist, prior job history, callback risk, customer LTV. No new app, no new login.
New hire ramp time cut by 50% because the knowledge is in a system, not a person. Same applies to CSRs — top-CSR scripting baked into onboarding.
Ride-alongs plus software. The knowledge graph gets more complete with every job type documented.
Engineer spends Days 1–5 in the field with your top performer and in the call center with your best CSR — documenting every diagnostic step, pricing decision, objection response, and close technique. This is the raw material for everything that follows.
Converts observed patterns into a structured knowledge base organized by job type — what to check, what to bring, how to price, how to close. Built from your actual operation, not generic industry content. This is how top-performer knowledge reduces callbacks at scale. Gets more complete with every job type documented.
Pulls job-specific context from the knowledge graph and delivers it via the existing FSM job card before the truck rolls — parts checklist, prior job history at this address, callback risk flag, customer LTV. Techs see it as part of normal workflow.
Structured onboarding content built from the knowledge graph for each job type. New tech ramp time drops from 8 months to 3 when the standard is explicit and consistent, not tribal. Same framework applied to CSR onboarding — top-CSR patterns encoded into the first 30 days.
Our Full-Operation Audit (Days 1–30) maps every revenue leak — field and back of house. If we don't identify at least $200,000 in recoverable annual revenue, we refund Phase 1 in full. You keep all audit deliverables.
After kickoff, we ask for about 30 minutes a week of your ops leader's time.
We'll start with a recent export or sample call data from your FSM and call system, show you the biggest leaks, and scope the engagement. Full access happens only if you proceed to the audit.