When the Director couldn't log in but still bought the tool

What tipped them over

Jonas's team had a credibility problem, not a competence problem. The analysts were sharp, but every markdown recommendation arrived as a spreadsheet whose logic lived in one analyst's head. When a buyer asked why a jacket line was cut 30 percent while a competitor held firm, the answer took two days to reconstruct. The Commercial Director trusted the outcomes but couldn't see the reasoning, and neither could finance.

Jonas started using MyDataWork to catalog the team's pricing estate first: the competitor scrape tables, the markdown models, the elasticity assumptions, the store and e-commerce sales feeds. Nothing left their existing tools. MyDataWork held only the metadata, the names, types, paths, relationships, and stakeholders, so the SQL, Excel, and Power BI stayed exactly where the analysts already worked.

The first problem they solved

The first real moment came in a markdown review. A merchant challenged a proposed cut, and instead of promising to circle back, Jonas's analyst opened the mapped use case, showed the value framing, the stakeholders attached to it, and the lineage from competitor pricing feed through to the recommendation. The reasoning was on the table in the meeting. The Director, watching, realized the team's work had become something he could defend upward without having to understand every query.

"The person who unlocked the budget never logged in once. He just needed to trust what he was signing his name to, and now he could."

Scaling from here

That trust is what tipped the purchase. The Director doesn't do data work and was never going to be a user, but he holds sway over the budget that IT controls. After seeing how clearly the team could account for its pricing calls, he became the champion who pushed procurement to approve and fund the platform. Jonas's analysts are the actual users on a Team plan; the Director is the sponsor. It's a quietly common pattern: the influencer who benefits from the outcomes, not the one clicking around the app, is the one who gets it bought.

The payoff showed up when the CFO questioned the season's markdown strategy. Using the aggregates-only Architecture and Value rollup, the Director could show the shape of the pricing work, how much value was framed against it and who owned it, and defend the strategy with confidence. He never saw a single analyst's private work, because the rollup only surfaces aggregates. Accountability without surveillance. The analysts kept their private-by-default workspace; leadership got a credible view. Reconstructing the logic behind a contested markdown dropped from days to under an hour.

Toward agentic & generative AI

With the estate cataloged and governed, Jonas turned to a longer-standing ambition: an agent that monitors competitor pricing continuously. Rather than build first and govern later, the team scoped the use case in Agent Studio, deciding exactly what the agent should watch and touch before writing any code. Then they used Agent Access to give the approved agent read-only metadata context through MCP, so it understood the pricing estate's structure without ever reaching actual data. The AI-ready foundation was a byproduct of work they were already doing, not a separate project.