Case Study
Rebuilding Creative Operations at Blue Yonder
An agency operating model, a 60-day platform rollout, and end-to-end process redesign: the transformation AI consulting promises, delivered with operational discipline.
The problem
Blue Yonder's creative team served the entire marketing organization, and beyond it, Sales, Product, and Customer Success. Demand was high, but the operating model hadn't kept up. Requests arrived through email, chat, and hallway conversations. Priorities shifted without a system to absorb the change. Designers spent their time chasing context instead of producing work, and nobody could say with confidence what was in flight, what was blocked, or when anything would ship.
The symptoms were familiar to anyone who has worked inside a creative function: redundant intake steps, no standardized briefs, unclear ownership, and turnaround times that made the team look slower than it actually was.
The approach
The fix wasn't a tool. It was an operating model, with a tool to run it on.
1. Map the real workflow. Before changing anything, I documented how work actually moved end to end: every intake path, handoff, review loop, and approval. The redundancies were only visible once the whole system was on paper.
2. Rebuild it as an agency model. I architected an agency operating model for Creative Operations: standardized intake and briefs, defined service tiers, clear ownership at every stage, and processes designed to be measured. Redundant steps were eliminated rather than automated in place.
3. Deploy the platform in 60 days. I procured and implemented Wrike as the system of record: evaluated, selected, and rolled out across multiple teams and departments in 60 days. Speed mattered: a long rollout kills momentum and gives old habits time to reassert themselves.
4. Make adoption stick. I directed a project management team of four and led the change management effort: cross-training on the platform, KPI reporting to leadership, and steady reinforcement until the new workflow was simply how work got done.
AI agents don't fix broken processes. They accelerate them. This transformation worked because the process was redesigned first.
The results
Team productivity increased 80%. Project turnaround time dropped 15%. On-time completion reached 94%. And the numbers held, because they came from a durable operating model rather than a burst of effort.
Beyond the metrics, the team's standing changed. With standardized intake, visible pipelines, and reliable delivery dates, Creative Operations went from a bottleneck to a function other departments modeled their own processes on.
Where it's going: the 7-agent playbook
That operational foundation is the basis for my current focus: an AI agent workflow playbook that automates the coordination work humans shouldn't be doing. Seven agents, each mapped to a pain point the Blue Yonder transformation surfaced:
- Intake checker: validates requests for completeness before they enter the queue
- Request router: assigns work to the right person and service tier automatically
- Deadline risk alert: flags projects trending late before they're late
- Campaign status reporter: compiles status updates nobody has to write by hand
- Naming convention enforcer: keeps assets findable at scale
- Approval follow-up nudger: chases the sign-offs that quietly stall projects
- Project kickoff auto-setup: spins up workspaces, tasks, and templates on day zero
The lesson of the case study applies directly: each agent automates a step that was first mapped, standardized, and proven manually. That's the difference between AI that demos well and AI that ships.