Turning repetitive infrastructure work into software.
Owned the roadmap for an internal GIS/CAD network design tool used by 200+ engineers, and turned repeated operational bottlenecks into automation adopted company wide.
What was not working
200+ engineers relied on an internal GIS/CAD tool for network design, but the workflow around it was manual: downstream signal recalculation, BOM assembly, and equipment error checking all depended on someone doing the same repetitive steps correctly, every time.
What the user actually needed
The bottleneck was not the design tool itself. It was everything engineers did by hand around it. Interviews with 30+ designers kept surfacing the same two time sinks: recalculating signal levels after a change, and manually pulling bills of materials.
What I owned
- Product owner for Spectrum's internal GIS and CAD network design tool used by 200+ engineers, translating feedback from 30+ users into prioritized improvements and aligning Design, Construction, Operations, and Engineering teams, cutting design turnaround time 40%.
- Identified manual downstream signal recalculation as a key design bottleneck and defined a 3 click automation for tracing, recalculation, and verification: recalculation time down 90%, manual errors down 25%, about 2 engineering hours saved per project across 3+ regions.
- Identified manual BOM generation and equipment validation as recurring pain points through designer interviews and launched Auto BOM, which tracks equipment changes automatically: report generation time down 50%, better network upgrade budgeting, about $700K in savings per regional operation.
- Owned the prioritization model for a 30 person cross functional unit, ranking requests by volume, urgency, and dependency.
- Led a 20 person audit of 1,000+ optical nodes for DOCSIS 4.0 readiness.
What had to be true
- Any automation had to slot into an existing, already adopted GIS/CAD workflow. Engineers would not switch tools, so the tool had to come to them.
- Errors in signal recalculation or BOM data have real field consequences, so automation had to be at least as accurate as careful manual work, not just faster.
- Prioritization had to serve a 30 person cross functional unit with competing, legitimate priorities.
Finding the bottleneck through interviews
Rather than assuming what to automate, I interviewed 30+ designers about where their time actually went. Manual downstream signal recalculation and BOM and equipment error checking came up repeatedly, independent of region or seniority.
Designing a three click automation, not a new system
Because designers would not adopt a separate tool, the automation was built as a lightweight layer that traced, recalculated, and verified signal levels in three clicks inside the existing workflow, cutting recalculation time significantly and manual errors by 25%.
The same pattern, trace, compute, verify, was reused for Auto BOM, which recorded equipment changes automatically instead of requiring a manual pull.
Scaling adoption
Both tools were rolled out incrementally across regional teams. The recalculation automation was adopted by 3+ regional teams, and Auto BOM went company wide once report generation savings of about 50% were demonstrated in the first region.
What shipped
- A three click Python automation for downstream signal tracing, recalculation, and verification, embedded in the existing design workflow.
- Auto BOM: automatic recording of equipment changes as designers made them, replacing manual bill of materials assembly.
- A prioritization model for the 30 person cross functional unit that ranked requests by volume, urgency, and dependency instead of first come first served.
How it was built
- Python automation layered on top of the existing GIS/CAD tool's data model, so designers kept their existing workflow and tool of record.
- Change tracking hooks that captured equipment modifications at the point of design, rather than reconstructing them later from disparate records.
Trade offs I made on purpose
- Prioritized automating the two highest frequency manual tasks (signal recalculation, BOM pulling) identified directly from user interviews, over building new design features.
- Chose incremental regional rollout over a single company wide launch, using early results to build the case for wider adoption.
Takeaways
- The highest leverage product opportunities were hiding inside operational workflows nobody thought of as a product. They just looked like how the job was done.
- Automation that respects an existing workflow spreads faster than automation that asks people to change how they work.