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After nearly eight years deploying a fault detection and diagnostics platform built around heavily customized rules, MacDonald Miller decided the model simply didn’t scale.
The contractor had made FDD a core part of its service offering, supporting owners like Hudson Pacific Properties. The problem wasn’t whether the technology worked. It did. The problem was what it took to keep it working.
“We had some of our smartest people working backend in the data, building and updating rules,” said Reid Powell of MacDonald Miller. “That hides the value—and it’s not where we want those people spending their time.”
Each building required custom logic. As systems changed, rules had to be retuned. Results depended heavily on which engineer was assigned, making delivery hard to standardize and renewals increasingly labor-intensive. “Even if you got them crisp and really nice, updating them over time… was just lots of human capital,” Powell said.
Leadership eventually concluded they couldn’t staff or capitalize an analytics platform fast enough to keep pace with customer expectations. “There’s just no way we’re going to bring the capital to bear to keep up,” Powell said.
That realization drove a deliberate shift toward buying an off-the-shelf FDD platform designed to support a service-led delivery model, rather than owning the analytics burden themselves. MacDonald Miller ultimately selected Clockworks Analytics, citing standardized data models and reduced onboarding effort.
For service providers watching margins tighten, the takeaway was: building and maintaining bespoke analytics may win early accounts—but it can quietly cap growth.
If you’d like to learn more, here are some ways to stay updated on stories like this:
After nearly eight years deploying a fault detection and diagnostics platform built around heavily customized rules, MacDonald Miller decided the model simply didn’t scale.
The contractor had made FDD a core part of its service offering, supporting owners like Hudson Pacific Properties. The problem wasn’t whether the technology worked. It did. The problem was what it took to keep it working.
“We had some of our smartest people working backend in the data, building and updating rules,” said Reid Powell of MacDonald Miller. “That hides the value—and it’s not where we want those people spending their time.”
Each building required custom logic. As systems changed, rules had to be retuned. Results depended heavily on which engineer was assigned, making delivery hard to standardize and renewals increasingly labor-intensive. “Even if you got them crisp and really nice, updating them over time… was just lots of human capital,” Powell said.
Leadership eventually concluded they couldn’t staff or capitalize an analytics platform fast enough to keep pace with customer expectations. “There’s just no way we’re going to bring the capital to bear to keep up,” Powell said.
That realization drove a deliberate shift toward buying an off-the-shelf FDD platform designed to support a service-led delivery model, rather than owning the analytics burden themselves. MacDonald Miller ultimately selected Clockworks Analytics, citing standardized data models and reduced onboarding effort.
For service providers watching margins tighten, the takeaway was: building and maintaining bespoke analytics may win early accounts—but it can quietly cap growth.
If you’d like to learn more, here are some ways to stay updated on stories like this:
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This is a great piece!
I agree.