The trades have been built on a mix of skill, experience, and gut instinct. The best contractors have an almost sixth sense for what a job will cost, how long it will take, and what it will take to get the job done right. But instinct, no matter how refined, has its limits.
Margins are tighter than ever. Material costs keep climbing. Skilled labor is harder to find. The companies thriving right now aren’t just relying on what’s worked in the past – they’re making decisions with a sharper edge. That edge?
Data.
Take equipment failures. Thanks to data, breakdowns no longer have to be a surprise. Not long ago, service businesses simply reacted when something failed. Now they can predict failures before they happen. It’s not a crystal ball—it’s asset history, performance tracking, and analytics working together. Instead of rolling a truck when something breaks, contractors can address problems before they disrupt operations. That means happier customers, fewer emergency calls, and a stronger bottom line.
The trades in 2025 aren’t just about fixing problems. They’re about preventing them altogether.
The same transformation is happening with dispatch—historically, a controlled chaos. Who’s closest? Who has the right skills? Who’s available? Answering those questions used to mean flipping through stacks of paper, checking a whiteboard, or, worse, relying on memory. Let’s be honest—that wasn’t exactly efficient.
Today, dispatchers can use technology to analyze technician performance, traffic patterns, and job complexity—automatically, in seconds. That means getting the right tech to the right job at the right time—almost on autopilot. And this level of precision doesn’t just make life easier for dispatchers—it makes businesses more profitable. The faster a job is scheduled and completed, the sooner the next one can begin. Multiply that across hundreds or thousands of service calls, and the impact is undeniable.
Data even levels up the job before it begins. In the past, contractors priced jobs based on experience, intuition, and sometimes a little bit of luck. But underbidding kills profitability, and overbidding loses deals. Now, with fingertip access to historical job data, labor trends, and material costs, contractors can create precise, profitable quotes. Pricing isn’t guesswork anymore—it’s strategy. It’s knowing exactly what a job will take and pricing it accordingly.
That kind of confidence changes how you operate.
And it’s not just about job pricing. Data is giving businesses a new way to understand operations at every level. Who are your most profitable customers? Which jobs consistently take longer than expected? Where is time being wasted? What parts of the business need investment? What’s draining resources? Being able to answer these questions isn’t just helpful—it’s often the difference between staying afloat and scaling up.
At the end of the day, the trades are about action. Fix the thing. Install the system. Get the job done. But the way decisions are made is shifting. The companies that are really growing aren’t just working harder; they’re working smarter. They’re using data not because it’s trendy, but because it delivers results.
This data evolution isn’t about replacing instincts or gut feel. It’s about refining them. Backing them up. Turning good decisions into great ones.
About the Author
Duncan Grazier is the Chief Technology Officer at BuildOps, where he leads the company’s engineering and product development initiatives. With a strong background in AI, machine learning, and system performance optimization, Duncan is passionate about driving next-generation innovation in the commercial contracting industry. Prior to joining BuildOps, Duncan served as VP of Engineering at Weedmaps, where he scaled the engineering team from 30 to over 300 and led major technological advancements that supported the company through its IPO. At BuildOps, Duncan focuses on developing seamless integrations, leveraging AI to optimize workflows, and enhancing the overall efficiency and resilience of the platform for commercial contractors.
