“Many leaders can’t easily answer basic questions about their own operations in real time.” That is something that SiteStack CEO Scott Cannon learned over several months traveling and meeting with contractors across the country.
As contractors scale across more sites, fragmented systems and inconsistent processes are making it harder to maintain visibility into spend, vendors and decision-making. As projects become more complex, the gap between perceived control and actual visibility becomes more apparent.
In parallel, SiteStack has begun rolling out a set of self-diagnosis tools and reality-check questions.
Cannon sat down with Construction Executive to shed light on these tools and on why the industry still runs on “heroics,” where that model breaks down and what more operationally aligned organizations are doing differently.
Why does construction still rely so heavily on what you’ve described as “heroics”?
Because for a long time, it worked. Construction has always been a relationship-driven, execution-focused industry. When something breaks down, experienced teams step in and fix it, whether a delivery is late, a vendor falls through or pricing doesn’t match expectations. People make calls, move things around, lean on relationships and keep the job moving.
That ability to adapt is a strength. But it also masks underlying problems. When enough experienced people are constantly stepping in to solve problems, the system and the process itself doesn’t get fixed. The work gets done, but it gets done through effort, not structure.
Over time, that becomes the operating model. This doesn’t happen by design, but by necessity.
At what point does that model start to break down?
That model usually can’t survive at scale. If you’re managing a handful of projects, experienced operators can stay on top of things. They know their vendors, they understand pricing and they can manage issues as they come up. But once you start managing dozens or hundreds of jobsites at once, the approach can’t continue working.
Complexities compound quickly. Different vendors, different pricing structures, different service levels, different timelines—all being managed across multiple teams. At that point, no single person has full visibility and coordination starts to break down.
That’s when you see what I’d call “slow leakage.” Not one big failure, but small inefficiencies everywhere. Extra days are billed, there are missed pickups, inconsistent pricing, duplicated work. Individually, they’re manageable. Collectively, they become a real issue.
Where do you see the biggest gaps in how companies understand their own operations?
Visibility is the biggest issue. If you ask most teams how their projects are performing, they’ll give you a general answer. They’ll tell you whether things are on track and where they’re seeing pressure. But if you ask more specific questions, it gets harder to answer. Questions like “What are we actually paying across vendors for the same category?” or “Where are we seeing the most cost variation?”
In many cases, that information exists—but it’s fragmented across systems, spreadsheets, emails and people. There isn’t a single, reliable view of what’s happening across the operation in real time. That gap becomes more obvious as organizations grow.
Do most teams have an accurate sense of where they stand operationally
In our experience, most overestimate their level of control. That’s not a criticism but rather a reflection of how the industry has evolved. Many teams have invested in systems, defined processes and built strong operational habits. On paper, things look standardized.
But in practice, a lot of decisions are still happening outside of those systems. Work gets done through email chains, chat apps, phone calls and individual judgment. That’s where inconsistency creeps in.
We’ve started asking leaders a handful of basic questions about their operations—things they should be able to answer easily. In many cases, the answers aren’t readily available or they require pulling data from multiple places. That’s usually the moment where the gap becomes clear.
With so much technology available, why hasn’t this problem already been solved?
Because most technology in construction has focused on individual parts of the workflow, not how everything connects. You have systems that are very good at financial management, others that handle project documentation, others that support procurement in specific categories. Each one solves a piece of the problem.
What’s often missing is the operational layer that connects the day-to-day coordination of vendors, pricing, logistics and execution across jobsites.
So even with good systems in place, teams still rally on workarounds to bridge the gaps. That’s where the heroics come back in. Technology supports the process, but it doesn’t fully replace the need for manual coordination.
What separates organizations that operate with control from those that rely on workarounds?
In my opinion, consistency. The organizations that operate with control aren’t necessarily using more tools, they have systems that are stronger and more repeatable. They’ve defined things like how decisions get made, how vendors are selected, how pricing is evaluated, how work flows from request to completion.
Even more importantly, those processes are followed consistently across teams and jobsites. That consistency creates predictability. It reduces the need for intervention because the system itself handles most of the coordination. Issues still happen, but they’re the exception, not the norm.
Where does AI actually fit into solving these challenges—and where is it falling short today?
AI has a role to play, but I think it’s often misunderstood. A lot of the conversation around AI has been about capability or what the tech can do, how advanced it is, how it’s changing industries. But for most construction teams, the simpler question is whether it actually makes outcomes more predictable.
In many cases, the answer today is still unclear. We’re seeing organizations experiment with tools, run pilots and introduce new systems, but those tools aren’t always integrated into how work actually gets done. That’s where you start to see friction instead of improvement.
The value of AI in this industry isn’t in adding another layer of technology—it’s in helping reduce variability, scale the expertise of talented people and bring consistency to processes that are currently dependent on individuals. If the right AI is implemented intentionally, the tech should feel almost invisible. It should quietly improve how work flows across jobsites, not require teams to learn entirely new ways of operating.
For leaders who recognize these challenges, what’s the first step toward fixing them?
My advice is to start with an honest assessment. Before changing tools or processes, leaders need a clear understanding of how their operations actually function day to day (not how they’re supposed to function). That means looking at where decisions are being made, how information flows and where teams are relying on workarounds.
In many cases, the biggest opportunities aren’t in adding new technology, but in aligning existing systems and standardizing how they’re used. From there, it becomes easier to identify where additional tools can add value, not as standalone fixes, but as part of a more cohesive operating model.
Construction will always require adaptability and the goal isn’t to stifle that. But the more structure you can build into the system, the less you have to rely on individual heroics to keep things moving.
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