I worked as a consultant for a global Google vendor, alongside the team that runs that account: a large-scale operation, with teams in several countries, managed through an internal system built over the years.
The engagement covered the discovery and design of the platform for its next stage, with more automation and AI: understanding how every team worked and delivering a development-ready specification.
client
Google (end client)
industry
Technology
date
Oct 2025 - Feb 2026
url
Not available
The Challenge
The internal system had supported the operation for years, but the account was changing: multi-step workflows, more AI-driven automation and ever higher standards for deadlines and quality. The starting question was whether to rebuild it from scratch.
Answering it required evidence: each team saw a different part of the problem, and the wrong decision could cost months of development in the wrong direction.
My Role & The Process
I led the discovery end to end, with a functional analyst from 12ninjas, and treated the rebuild as what it was: a hypothesis to validate.
- Interviews across every team: more than 20 recorded interviews, in English and Spanish, with operations leadership, project managers, capacity planning, onboarding, quality, BI, finance, PMO and the people who do the work every day.
- AI-assisted cross-analysis: I cross-referenced the transcripts with NotebookLM to find the patterns that repeated across teams and separate symptoms from root causes.
- Leadership checkpoints: I presented progress to the account and technology leaders to validate each finding before designing.
- Iterative design: I prototyped the interfaces in Figma and refined them with the client's team until every screen answered a problem surfaced in the discovery.
Outcome
The discovery showed that the problems shared a common cause: the system had been built for single-step workflows, while the operation already worked with multi-step ones. The recommendation was to evolve the existing system and strengthen the team behind it instead of rebuilding it. The effort focused on the two points holding back growth: automatic work assignment and multi-step workflows.
The deliverables:
- A report with twelve improvement areas, each with its evidence, its impact and prioritized solutions.
- Six interfaces prototyped in Figma.
- The specification of the automatic reassignment rules, ready for the client's development team to build.
The client chose to evolve the existing system and expanded the engagement with the design of an assignment and capacity planning component.
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