The FullStory
Programme

A powerful tool, capturing almost nothing

The business had committed to a new behavioural-analytics platform to replace a legacy tool that no longer scaled. On paper: unlimited seats, session replay, StoryAI, a data pipeline to the warehouse. In practice, it launched fully masked by default — for good, deliberate privacy reasons — which meant it could see too little to be analytically useful.

So the real work was never “install the tool”. It was three harder things at once: get the governance right so we could safely see what mattered, build the capability so teams could use it, and roll it out without breaking trust on a platform handling ~10,000 agent sessions a day.

No line authority over any of these functions — the job was to align them. I set the direction, framed every decision so the right owner could say yes, and kept an exec sponsor informed at the altitude they needed. This is influence-without-authority at programme scale.

“Just unmask it” was never an option; “leave it all masked” made the platform pointless. I worked with the DPO and Cyber to define a two-tier masking policy that everyone could stand behind — the framework that turned a stalemate into a repeatable decision.

A platform nobody knows how to use delivers nothing. So a core part of the programme was enablement: I authored a 20-guide knowledge base — from a “101” through features, access and element tagging — and staged it for both the internal training hub and the learning-management platform, iterating it across multiple versions as the product and the audience matured.

From shelfware risk to an adopted capability

The programme moved a powerful-but-blind platform to a governed, enabled, and rolling-out capability — with the privacy framework, the training and the operating model all in place. It gave the business behavioural evidence to reduce cost-to-serve, to challenge or confirm what customers say with what they do, and to make investment and deprecation calls on data rather than instinct.

For me, it’s the clearest evidence of leadership at scale: aligning governance, engineering, product, research and the executive around a single direction — and doing the unglamorous enablement work that makes adoption actually happen.