If you run a trades business, you are likely running two of them.
During the day: the work that defines you. Getting the right person, with the right skills and the right parts, to the right place, at the right time — and doing the job well, first time, profitably.
After hours: the business behind the business. Quoting. Invoicing. Reordering supplies. Chasing payments. Responding to the emails that stacked up while you were on the tools.
Most industries have a clean separation between those two worlds. In the trades, they collide constantly — and that collision, the friction between field and back office, is where most of the profit disappears.
It is not a people problem. It is an operational one. And for most trade businesses, it has been running unchecked for years.
The average trade business earns 6% net profit. The highest performing earn about 24%. The gap between those two numbers has nothing to do with effort, craft, or how early you wake up. It comes down to execution capacity — the ability to run the 27 things a profitable trade business has to do well, simultaneously, while the day tries its best to fall apart.
Most businesses run 7 of those 27 things. The other 20 are roles they would need to hire for, at margins that will not support the headcount. That is the gap we are talking about. And it is the gap that the next decade of the trades will either close or widen permanently — depending on which side of it your business ends up on.
The Chaos Variables
Every trade business owner has lived a version of the same day.
A technician calls in sick at 6 a.m. The morning schedule reshuffles. The reshuffle pushes a job to the afternoon, which is already full. One of those afternoon jobs needs a part that is not on the truck. The technician drives back to the warehouse. An hour gone. The customer in that slot calls to reschedule. The day that was already fragile is now genuinely unrecoverable — and the invoicing for yesterday still has not been touched.
These are what Corey O'Donnell, Simpro's Chief Brand and Strategy Officer, calls chaos variables — a term that captures something every trade business owner recognises immediately but rarely has a name for. There are potentially a thousand of them on any given day: a change in weather, a broken-down truck, a missing part, a subcontractor who didn't show, a customer who isn't home. The list is endless, and it is not going away.
What makes chaos variables particularly dangerous is that they come in two flavours. The first kind you feel immediately — the truck breakdown, the no-show tech, the weather event that shuts down the whole week. You respond to it. Imperfectly, reactively, at great cost to your schedule, but you respond.
The second kind is quieter. Cash flow slipping because invoicing has been running two weeks behind. Unbilled time accumulating into invisible write-offs. A vendor still charging you monthly for a service they stopped providing half a year ago.
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There are some chaos variables you are acutely aware of — you feel them the moment they happen. And then there are others that have sort of happened quietly in the back office and go unnoticed until they really blow up in your face.
The quiet chaos is the most expensive kind, because it compounds. By the time someone notices it, it has usually been running for months.
The story is not unusual. It is the kind of thing that happens when a business is running too fast, across too many disconnected tools, for anyone to have a clear view of the whole picture.
The deeper issue is structural. Most trade businesses are not running on a designed system. They are running on an accumulated one — a stack of five, six, seven separate software tools, each introduced to solve a specific problem, each with its own database, none of them talking to each other. Nobody decided to build this stack. It just grew.
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Most businesses build their operational process — they didn't design a system, they accumulated one over time. It's the disconnect between these tools that prevents you from having one unified workflow. Meanwhile, chaos is taking place.
The result is that the human — usually the owner, sometimes a lone admin person — becomes the connective tissue between all these systems. Their job, effectively, is to take something from one place and move it to another. To carry job completion data from the field app into the invoicing system. To manually reconcile the schedule against the payroll. To cross-check the inventory against what was actually used on site.
It is the most expensive integration money can buy. And it is exhausted, error-prone, and doing the job at midnight.
What Changes When AI Actually Has Context
The transformation AI makes possible in the trades is not about replacing the craft. There will always be a technician in the field doing the real work — pulling cable, fixing the pipe, commissioning the system. That is not where the problem lives.
The problem lives in the 18.5 hours a week of administration happening around that work. The scheduling that does not account for parts availability. The invoicing that goes out ten days after the job closes. The parts order that gets forgotten until the technician is already on site. The customer who does not hear from anyone between jobs and quietly calls someone else the next time they need a service.
AI fixes all of that — but only if it has the context to do so. And context is the key word.
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AI has a problem. It is very hungry for context. If you put together a platform or connected system where all of those individual stacks of tools are unified and combined, then AI suddenly can say: now I have context. I understand all of the what, where, and why of the business. And because of that, I can respond to chaos variables in a way no human can — because I can stay ahead of them.
A bolt-on AI feature sitting on top of five disconnected systems knows nothing — it cannot make intelligent decisions about a business it cannot see. But a unified platform, where all the operational data lives in a single connected source of truth, gives AI the foundation it needs to actually work. And what it can do from there is a different category of capability entirely.
The clearest way to understand this is through a concrete example. When a truck breaks down mid-morning, the question is not whether chaos has arrived — it has. The question is how fast and how intelligently the business responds.
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The system is smart enough to say: that truck broke down — I can reassign this truck, here's what the impact will be on all the other jobs for today, here's all the people I need to communicate with. In terms of who I send, I need the right tech with the right parts and the right skills to the right place at the right time. And I need to do that profitably.
That response — knowing the ripple effect across every job, every technician, every customer commitment, and the margin cost of each option — would take a skilled dispatcher 20 to 30 minutes to work through manually. An AI with full operational context does it in seconds. And it does this not just for the truck breakdown, but for every chaos variable that hits, across the entire operation, every day.
The distinction Corey draws between AI as a feature and AI as a foundation matters enormously here. There is no shortage of software products adding an AI button or a chatbot to their interface. That is not what is being described.
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It is not a feature. It is the new foundation for how a software platform has to work — and then soon, how a business has to work. I'm going to leverage that AI to be the fabric of how every decision is made.
Getting there does not happen overnight — nor should it. The trust-building arc matters. AI earns autonomy incrementally, starting with guardrails and recommendations, moving to independent action as the business confirms its judgment is sound. Consider inventory reordering: in the early days, the system asks. Would you like me to place that order? Over months, as the owner watches the AI's decisions and grows comfortable with them, the guardrails loosen. That is the right pace.
The Operators Already Building for the Decade Ahead
The businesses that will define the next decade of the trades are not waiting for the transformation to become obvious. They are building the foundations — the platform discipline, the data infrastructure, the operational maturity — right now. Here is what three of them are doing.
Sally Higgs, Alykan Electrical — Melbourne, Australia
Nine field staff. Two admin. And the ability to quote a $250,000 commercial construction job in under an hour.
Sally Higgs, GM and co-founder of Alykan Electrical, runs a business that competes against and regularly beats companies three or four times its size — not by working harder, but by having done the unglamorous process work that makes everything downstream faster and more accurate. She spent twelve to eighteen months getting pre-builds and templates right in Simpro before worrying about anything else. That groundwork is what enables the speed now.
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Revenue is a vanity metric. We see businesses pumping out $20 million a year, making less than us. It's actually all about profit. We've got nine field staff and two admin. I know equivalent-size businesses that probably have six or seven admin people. Good software and good processes are the difference.
Sally presented on AI technology stacks at Simprosium in Sydney. Her opening question to the room was simple: what is your definition of success? Not because the answer is complicated, but because it determines everything else — whether AI is the right tool for a given problem, whether the timing is right, whether the process foundation is there for the technology to run on. Process clarity first. Technology second. That sequence is not accidental.
Her business has funded the purchase of at least half a dozen homes for team members. That is what getting the economics right looks like when it compounds over years.
James Ewart, Aotea Group — New Zealand
$450 million in revenue, 26 operating companies, 1,700 staff. Three years ago, those 26 companies were running on nine different job management systems and eight different financial systems — 17 separate platforms for one organisation to operate across.
James Ewart, Aotea's CEO, spent the last three years rationalising that stack. Today, 80% of the business runs on a single platform — Simpro. He is currently building a data lake that will consolidate all financial and operational data across every operating company — within roughly twelve months, he expects to benchmark any one of his 26 businesses against every other, in real time. The operational intelligence that unlocks is the compounding return on three years of hard rationalisation work.
His position on AI is clear-eyed and direct.
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You're not necessarily going to lose your job to AI — but you'll lose your job to someone else who can do your job and understands AI. There is real risk in ignoring the opportunity.
Aotea has a formal AI policy, a protected Microsoft Copilot deployment, and one operating company already using AI for high-volume contract review. When Ewart ran an internal survey, 70% of staff reported using AI — and 70% of those were doing it without their managers knowing. His response was not to restrict it. It was to build a safer environment for it and start capturing learnings at an organisational level. That is what operational maturity looks like at scale.
Dawn Lawrie, Ignite Consultancy — United Kingdom
When the SFG20 Facilities IQ API, the UK’s authoritative standard for building maintenance schedules, changed and the integration that around twenty UK customers needed was not being built, Dawn Lawrie built it herself. Through Ignite Consultancy, her own practice, with a developer she hired. SFG20 demoed it and liked it. Lawrie, Managing Director of Ignite Consultancy Services, saw a gap in the ecosystem, had the skills to close it, and turned it into a service.
Her pattern recognition from working inside businesses that have the software but are not getting the value from it is consistent across every organisation she has worked with.
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You need to have a champion of the system. It can be challenging if you don't have one — you end up with multiple people dabbling with the back end and nothing lands properly.
Without a champion, the tools get underused, the workarounds accumulate, and the gap between what the platform can do and what the business is actually extracting from it quietly widens. The champion is not an IT role. It is an operational leadership role — someone who owns the platform, advocates for it, and ensures the business is running the system rather than working around it.
The Heart, the Brain, and What Lightning Actually Is
Simpro is the operational heart of a trades business. It pumps the work: scheduling, dispatch, job management, invoicing, the backbone of how the business runs day to day.
Cooper – or COOP – is the brain. It is Simpro's AI, purpose-built for the trades, sitting on top of the FSM and doing the work the business has never been able to staff for. Together, they are Lightning — the AI-first operating platform. Nothing gets replaced. The heart stays in place. The brain is added on top, already connected to the platform, already trained on operational data, and ready from day one.
At launch, COOP delivers four full-time roles — and JustAsk, a conversational interface to the entire FSM data lake, so any operational question can be asked in natural language and answered from the data the business has been generating for years.
The four agents include:
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FieldReady — Training and onboarding. Ensures every technician has what they need before they leave the yard.
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JobReady — Job preparation. Full customer history, the right parts list, site-specific instructions — delivered to every technician before every job.
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JobScribe — Documentation. Field notes, photos, and form data become professional job summaries and compliance-ready records automatically.
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JobBrief — Customer summary. Professional, accurate post-job communications sent to every customer without anyone having to write them.
The economics of this are worth being direct about. A receptionist costs around $40,000 a year. An AR clerk, around $50,000. A procurement manager, around $90,000. A scheduling supervisor, around $65,000. COOP fills those roles — all of them — for roughly $2,000 a year. At 6% margins, none of those hires are possible. The business runs lean, the owner does everything, and the night shift never ends. COOP is what makes 24% achievable. And 24% is what makes those investments viable. The logic compounds in one direction.
Every future COOP agent — smart dispatch, AR and AP automation, preventive maintenance, customer marketing — ships under the existing Simpro Lightning upgrade at no additional cost. Annual increases are capped at 3% plus local CPI for life, while the rest of the AI market raises prices 20% to 25% a year. The brain gets smarter. The price stays predictable.
What the Decade Ahead Delivers
The craft does not change. The pipe still needs to be fixed. The panel still needs to be wired. What changes is the 18.5 hours a week of administration that currently happens around the real work — and the compounding cost of running that administration on disconnected tools, with a human being as the integration layer.
The businesses that build execution capacity now will compound advantages that, within a few years, become structural. Not a gap you can close by working harder. A gap you can only close by starting sooner.
Fred Voccola, Chairman and CEO of Simpro Group, has studied this more deeply than almost anyone — he spent months researching and writing a book on AI's disruption, and what he found shaped how the company thinks about what it is building. Most software companies are threatened by AI — the technology can replicate or replace what they do. Simpro is the opposite.
The vision is that within the next few years, every commercial contracting business running on Simpro's platform is operating at 15% to 25% profit margin — not because the market got easier, but because the execution capacity got better. Right worker, right job, right time, right parts, right instructions, every time.
For the owner, that looks like real-time visibility into revenue, jobs in progress, and cash position from wherever they happen to be — without having to be the one holding it all together. For the operations team, it looks like managing exceptions rather than fighting fires. For the technician in the field, it looks like arriving prepared instead of improvising. For the admin team, it looks like the system doing the routine work while they do the valuable work.
That transformation is available now. It does not require waiting for the decade to arrive. It requires making the right decisions in the next 90 days.
The Sequence Is Everything
Before the AI. Before the platform. Before any of it — do this.
Start with the audit. Do the honest inventory of what your business is actually using, what it is paying for, and which tools require a human to carry data between them. You will find things you forgot you were subscribed to. You will find disconnections you did not know existed. That inventory is the foundation everything else is built on.
Then map the workflow — not just the perfect day, but the chaos-variable day. The day a technician calls in sick, the truck breaks down, and two customers need to reschedule simultaneously. What does a good response to that day look like? What would need to be true for your system to respond that way automatically, without you in the loop?
Then connect. The FSM is the heart. If it is not unified with your accounting, scheduling, inventory, and customer history in a single source of truth, that is the first thing to fix. COOP cannot work intelligently from disconnected data. Neither can anyone else.
Then turn on the brain.
The businesses in this piece — Alykan Electrical in Melbourne, Aotea Group in New Zealand, Ignite Consultancy in the UK — did not arrive at operational maturity by accident. They did the necessary work first: the inventory, the workflow mapping, the platform rationalisation, the champion who owned the system and made it matter. The decade rewards that work. It just requires starting it.
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You can get to a place over the next decade where you've transformed entirely the profitability and efficiency of your business. We're talking about doubling, tripling or more — if you connect your workflows, harness the power of AI, and build the kind of operation that can respond to everything the day throws at it.
The full conversation — 45 minutes of the clearest thinking we have seen on where the trades are heading, what the best operators are doing right now, and the specific steps to move from reactive to proactive — is available in the webinar. Watch it.
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