Background and Context

This initiative supported a large-scale learning portfolio delivered across multiple districts, schools, and participant groups each year. Because the program repeated annually with new schools and stakeholders, the implementation model needed to be both consistent and adaptable.

Internally, the work required coordination across design, facilitation, school support, program operations, data, and leadership. Each team owned a different part of the delivery lifecycle, from content readiness and platform setup to scheduling, communication, facilitation, feedback collection, and post-session follow-up.

The Challenge

The central challenge was building a scalable implementation system where no centralized operational infrastructure previously existed.

When I began this work, individual contributors were responsible for scheduling their own professional learning sessions, tracking completion in their own ways, and managing follow-up independently. There was no shared source of truth for scheduling, no consistent way to monitor delivery progress, and no centralized system for viewing collective feedback across learning experiences.

As the program grew, this created several risks:

The system needed to answer a larger operational question:

How do you move a high-volume learning portfolio from individual coordination to scalable program delivery?

The System I Built

To support this work, I created a centralized implementation guide that served as the shared source of truth for the delivery process. The guide documented key dates, implementation windows, role responsibilities, scheduling procedures, Asana workflows, communication templates, Canvas processes, office hour structures, feedback systems, and post-session data review.

I also built the structures that helped move the program from individual coordination to shared implementation. Scheduling became more visible, responsibilities became clearer, communication became more consistent, and feedback could be reviewed collectively rather than in isolation.

Recognizing that internal stakeholders had different roles, schedules, and support needs, I built both synchronous and asynchronous support structures. Weekly office hours created a predictable space for live clarification, risk identification, and cross-functional alignment, while shared agendas and trackers allowed stakeholders to surface questions, document decisions, and receive follow-up support without requiring another meeting.

Implementation Lifecycle

The delivery model followed a structured lifecycle from planning through post-delivery review. Each phase clarified what needed to happen, who owned the work, and how teams would stay aligned across the implementation cycle.

Tools and Systems

The implementation system relied on connected tools, automation, AI-supported workflows, and human checkpoints to reduce friction, increase visibility, and support consistent execution across the delivery lifecycle.

With hundreds of schools, shifting schedules, and multiple stakeholder groups involved, the system needed to surface accurate answers quickly: what was scheduled, who owned each task, what deadlines were approaching, where support was needed, and what feedback was coming in.

I designed workflows that connected scheduling, project management, communication, data tracking, and continuous improvement. Integrations between TimeTap and Asana automated task creation using event details from the scheduler. Once a learning experience was scheduled, related tasks, subtasks, assignments, and due dates were generated without manual input, dramatically reducing the time needed to manage changing dates, times, and delivery details.

Tools

Evidence & Artifacts

This case study is supported by selected artifacts that show how the implementation system was documented, communicated, and managed. The centralized source of truth for timelines, roles, workflows, links, communication templates and support processes. The entire document is provided below.

Outcomes and Impact

This implementation system transformed a fragmented delivery process into a scalable, transparent, and repeatable program model.

Before this system, scheduling, tracking, and feedback collection were largely distributed across individual contributors. After implementation, teams had a shared source of truth, clearer ownership, centralized workflows, more consistent communication, and stronger visibility into delivery progress and feedback trends. This case demonstrates that large-scale learning implementation depends on more than strong content. It requires operational infrastructure that can align people, processes, timelines, tools, and data across a complex stakeholder environment.

The most important design decision was to treat implementation as a system rather than a series of individual events. By documenting workflows, clarifying roles, centralizing resources, and connecting tools, the work became easier to repeat, monitor, and improve over time.

Final Thoughts

This is one of the systems I am most proud of building because it created lasting infrastructure where none previously existed.

The work reflects my approach to program management: identifying where complexity is creating friction, building the systems that help people move through that complexity, and creating structures that can continue supporting the work beyond my individual role.

I am most energized by work that sits at the intersection of strategy, operations, learning, and people, where strong infrastructure makes meaningful delivery possible.