Turning operational
chaos into
systems that scale.

The team ran on an ad hoc task queue with no structure, no visibility, and no way to predict delivery. Work came in from every direction. Priorities shifted constantly. There was no shared language between the team and stakeholders. Throughput was low and trust was lower.

I built the agile delivery framework from the ground up. Replaced the task queue with a Scrum + Kanban hybrid, 2-week sprints, story point estimation, backlog grooming, and standardized intake templates. I sustained a release cadence of 90+ tickets biweekly, surfacing weekly prioritization reviews to leadership with tradeoff analysis and queue health visibility.

To drive adoption, I created internal newsletters called "The Drill Down," release notes, and stakeholder communications that made the framework feel like a resource, not a mandate. Adoption was tracked and iterated on continuously.

Power BI was deployed but barely used. Known mostly by leadership. The rest of the org was still sending ad hoc report requests, creating bottlenecks and inconsistent data across teams. The tool was there. The adoption wasn't.

I treated adoption as a data problem. I designed a structured enablement program for Sales, Customer Success, Operations, and leadership. Guides, FAQs, training videos, weekly virtual demo sessions, LMS-based courses, and internal newsletters. I served as the primary point of contact for 1,800+ internal users, resolving questions and feeding insights back into dashboard prioritization.

I also owned data governance, lineage, metric definitions, and source-of-truth decisions. Ensuring that when two teams looked at the same KPI, they saw the same number and trusted it.

1,500 users across 15 departments were running on a CRM patched together as the company scaled. No workflow governance, inconsistent data, and nothing built for the solar industry's lifecycle. Leadership made the call to migrate to Lightspeed. There was no existing playbook and a hard deadline tied to the Podio contract renewal.

I owned the program end-to-end. I started by mapping existing Podio workflows across all 15 departments — understanding what each team actually needed versus what they were used to, because those aren't the same thing. From there I built the project plan, established cross-functional governance cadences, coordinated workflow design with engineering, managed UAT cycles, and sequenced a staggered rollout to minimize disruption.

I created process flowcharts, requirements documentation, and Figma mockups to align stakeholders before a single line of code was committed. Adoption was tracked and visible from day one.

Onboarding was tribal. New hires learned by watching others, knowledge lived in people's heads, and there was no scalable system for bringing people up to speed. In a 6-month window, 353 employees separated against 633 new hires — a 56% separation rate. Exit data showed dissatisfaction, performance failures, and early abandonment were the primary drivers. All three are addressable through structured onboarding.

A rising TRIR (safety incident rate) added urgency: insurance premiums were at risk if the trend continued.

Before proposing any solution, I quantified the cost. I modeled the direct onboarding time lost to each separation (80.5 hours per employee across 7 departments), plus the cost of replacing each person who left. The total came to $792K in onboarding waste and approximately $4.99M in combined exposure when replacement costs were factored in.

I grounded the eLearning case in external research: Brandon Hall Group data showing 40-60% less study time via eLearning, IBM's $200M savings after switching to online delivery, and revenue per employee data from companies with structured training programs. Leadership had the data they needed to decide.

After securing buy-in, I designed and built the LMS in EdApp. Role-based learning paths, microlearning modules built for completion, a dedicated safety training track to address the TRIR risk, completion dashboards for manager visibility, and a feedback loop for continuous improvement. The design principle: knowledge should live in the system, not in a person.