"Before I get into the numbers, I want to start with a story.
Last week, a machine was pulled apart for maintenance. Standard procedure. Except nobody in the maintenance department knew that machine was scheduled to be on a job site two days later. By the time we realized the error, it was too late. The job was delayed. The scramble cost us sixty thousand dollars.
Not because anyone did anything wrong. Because the left hand didn't know what the right hand was doing.
That's the problem we set out to fix. And today I want to walk you through exactly how we're fixing it — and what it means for this business."
"Let's start with maintenance — because that story isn't unusual, it's just unusually well-documented.
Historically, maintenance and job scheduling lived in two different places. Maintenance techs didn't have visibility into the job board. Schedulers didn't know what machines were flagged for work. The result? Conflicts. Delays. Expensive ones.
What we built is a shared maintenance dashboard — a single view where every machine's status, scheduled maintenance, and job assignment is visible to everyone who needs it. A machine tagged as "on a job" cannot be pulled for maintenance without a flag and approval.
The $60,000 mistake? [pause] We can't go back and fix that one. But we can make it the last one."
"When you're blasting, the phones ring. Residents nearby have questions. Are they safe? Is there more blasting today? Why is their window rattling?
Our admin staff were handling two or more hours of these calls every single day. Explaining the same things, over and over. Valuable time that could have been spent on billing, customer follow-up, or job prep.
We built a new website with a dedicated blast information page — an FAQ that answers exactly what residents want to know: schedules, safety protocols, noise expectations, contact info. We directed all inbound blast-related inquiries there.
The result: those two hours of daily admin time? Gone. That's roughly 500 hours a year returned to the business. More importantly, it's time that can now be spent creating value instead of answering repeating questions."
"One of the most expensive things a company can do is make a decision too late.
Hiring someone when you're already desperate. Renting a machine when you should have bought it six months ago. Turning down a contract because you don't know if you have the capacity.
Forecasting changes that.
What we've built is a pipeline forecasting tool that takes our current jobs, pending bids, and seasonal patterns — and tells us, months out, what our labour demand and equipment needs are going to look like.
It means we can hire ahead of the curve, not behind it. We can identify the exact windows where renting a rig makes sense versus when buying one pays off faster. We can walk into a bid knowing exactly what capacity we have to take it on.
We're not making decisions based on gut anymore. We're making them based on data we already have — we just never had a way to see it."
"Here's something that might surprise you about how job costing has worked historically in field services: it hasn't.
Not really. Field employees were expected to fill out daily activity reports by hand, at the end of a long day, on paper. Those reports were submitted late. Sometimes lost. And when the receipts came in, there was no reliable way to match them to a specific job site.
So we'd get a fuel bill and not know: was that Tank A or Tank B? Job 47 or Job 52? We were guessing. And when you're guessing your costs, you cannot know your margins.
We rebuilt the DAR system from the ground up. Mobile-friendly digital forms. Automated reminders to supervisors when a DAR isn't submitted. GPS tagging links costs to locations automatically.
Now every dollar of cost gets attributed to the right job. For the first time, we actually know what jobs cost to run. That sounds basic. For most companies in this industry — it isn't."
"Now here's where it gets interesting — because accurate job costing doesn't just fix an accounting problem. It creates a completely new opportunity to align your workforce.
If we bid a job at $500,000 with a projected cost of $350,000 — we're targeting a $150,000 gross margin. We now know that number with precision.
So here's what we can do: offer the crew on that job ten cents for every dollar they bring in under projected cost. If they run it at $320,000 instead of $350,000, that's $30,000 in savings — and they earn $3,000 in bonuses, split among the crew.
Suddenly, the workers on that job care about the efficiency of that job. They track their consumables. They don't leave equipment running unnecessarily. They flag potential waste before it happens.
This isn't about replacing people. It's about giving people a reason to think like owners. In an industry where margin compression is constant, the companies that win are the ones where every person on a job site understands that their decisions affect the bottom line — and shares in the upside when they get it right."
"Finally — customers.
Most companies in construction and resource services operate with a simple mental model: you know your big customers, you know your relationships, and you react when something goes wrong.
The problem is that customer decay is almost always gradual. A client who used to give you four contracts a year is now giving you two. You didn't notice because nothing dramatic happened. They just quietly shifted spend somewhere else.
What we've built uses AI to track customer revenue trajectories over time — flagging accounts that are growing, accounts that are steady, and accounts that are drifting. So that instead of reacting after a client is already gone, our account team gets an early warning and has time to reach out, rebuild the relationship, and find new opportunities.
This isn't about replacing salespeople. It's about replacing the part of their job that's data entry and list-checking — so they can spend their time on what actually matters: conversations."
"Every single one of these modules does one thing: it gives us information we already have, in a form we can actually use.
The $60,000 maintenance mistake happened because we didn't have visibility. The admin hours on phone calls happened because we didn't have a better channel. The hiring delays happened because we couldn't see the pipeline. The margin uncertainty happened because we couldn't trust our cost data.
That's not a talent problem. That's not a culture problem. That's an information problem — and information problems are solvable.
We've solved them. And the revenue impact isn't theoretical. It's in this business, right now, waiting to be captured.
Thank you."