I spent about 25 years running industrial operations and kept running into the same problem:
By the time the dashboard shows something is wrong, it's already too late.
Revenue misses, backlog collapses, production slowdowns - the signals were actually in the operational data weeks earlier, but spread across CRM, ERP, and maintenance systems.
I built a dynamic system called Huckle to detect those signals earlier.
It connects to operational systems and looks for patterns that often precede operational problems - things like pipeline velocity changes, backlog compression, maintenance clustering, and service demand shifts.
The goal is to surface issues 30–90 days before they show up in traditional metrics.
I spent about 25 years running industrial operations and kept running into the same problem:
By the time the dashboard shows something is wrong, it's already too late.
Revenue misses, backlog collapses, production slowdowns - the signals were actually in the operational data weeks earlier, but spread across CRM, ERP, and maintenance systems.
I built a dynamic system called Huckle to detect those signals earlier.
It connects to operational systems and looks for patterns that often precede operational problems - things like pipeline velocity changes, backlog compression, maintenance clustering, and service demand shifts.
The goal is to surface issues 30–90 days before they show up in traditional metrics.