Maven Clinic · 2025–Present
Building
the Brand OS
Maven Clinic was growing — more teams, more services, more places where the brand could get stretched or compromised. Production work was consuming nearly half the design team's capacity, an inconsistent brief intake was generating rework cycles, and without visibility into capacity and roadmap changes, brand design kept showing up downstream in execution rather than upstream where it could shape the work. As Creative Operations Manager, I'm building the systems to change that.
Approach
01 — Plan
I started with symptoms: rework cycles, inconsistent briefs, and creative bandwidth absorbed by production work that shouldn't have needed brand design at all. I looked at the data to understand where the patterns were concentrated — which deliverable types, which team relationships, and where brand design kept showing up in execution when it should have been shaping strategy. With that picture in hand, I brought the brand design team together to identify the real opportunities and agree on focus areas before building anything.
The issue wasn't bandwidth. It was position. Brand design was showing up too late to shape the work.
The vision that took shape was built around three outcomes. Scale: brand tooling that deploys without requiring brand design on every output. Governance: quality embedded in the process, not policed after the fact. Strategic leverage: less downstream execution, more upstream influence in campaign shaping and go-to-market planning.
02 — Build
Infrastructure. I introduced two new tools to evolve the operational backbone.
Brief Builder
A conversational intake agent that guides stakeholders through submitting a design request, fills gaps through dialogue, pressure-tests the brief, and files the Jira ticket automatically when it's ready. It reads live team capacity, routes by project type, and surfaces lead times.
Operational Signal Hub
A unified view of capacity, demand, and spend for the brand design team and executive leadership. I built the underlying capacity model: mapping request volume, team bandwidth, and project type to a live 30/60/90 availability outlook, with budget tracking alongside: spend by vendor, project type, and requesting team, estimated vs. actuals. A suite of automations keeps it current without manual input.
Brand Tooling. With the operational foundation work started, I championed a 3-day brand design hackathon to develop the tooling layer that reduces production-led work and frees brand design to focus upstream. Some of the brand tools built using AI included an Ad Generator for on-brand display and social assets, a Brand Deck Generator that creates on-brand slides and documents from plain-language briefs, a Gradient Generator for on-brand visual treatments, and a Redline Tool that catches brand inconsistencies in fonts, colors, and copy. Governance is built into each. Output is on-brand by design, not reviewed after the fact.
03 — Adopt
We start with marketing and growth because they have the greatest external impact on business goals. When the tools work there, the results are immediately visible and the case for broader rollout makes itself.
Each rollout starts with context before anyone touches the tool. We share the vision, run a live demo, and make sure everyone understands what this changes and why. A dedicated channel goes up the same day so feedback flows directly to whoever built the tool, and friction surfaces quickly rather than quietly accumulating. From there, it's iteration. We evaluate at defined intervals and only move toward broader rollout when the tool is genuinely working for the workflows it was built for. The real measure of adoption isn't the doc. It's whether the new behavior is embedded where people already work. When a tool fits inside existing workflows, it sticks.
04 — Measure
Measurement is built into every layer. I track core metrics weekly (request volume, rush rate, ad turnaround, and capacity by team) and run monthly calls with pilot team leads to surface wins, friction points, and emerging patterns. As each tool rolls out, I run 30/60/90 evaluations to assess adoption and impact. Feedback flows are built directly into the tools so iteration is continuous, not reactive.
Impact
Expertise