Walking into S&OP knowing exactly what fed the number

What tipped them over

The month it tipped, a plant manager asked where the inventory target came from, and Arjun realized the honest answer was scattered across three analysts, a Snowflake query nobody could immediately find, and an Excel model with a tab labeled "final_v4." The number was right. He just couldn't prove it in the room.

For years the work had felt like a carpenter carrying his tools across the job site in both arms, dropping the important ones somewhere between the truck and the wall, then walking back to look for them. MyDataWork was the toolbox he could actually carry to the job. Same tools, same SQL and Excel and Tableau, but now they had a place, a name, and an owner.

The first problem they solved

He started small in Explorer over a weekend, cataloging the assets behind one S&OP deliverable, the queries, the workbooks, the dashboards, and framing them as use cases with the business value and stakeholders attached. Because it only captured metadata, names, paths, owners, relationships, and never the data itself, he didn't have to clear it with anyone to begin.

The lesson came fast: he'd assumed his analysts knew who owned what. Mapping the lineage showed two dashboards quietly depending on a supplier extract that one analyst maintained by hand and had never documented. Fixing that before it broke mid-cycle was worth the whole exercise.

For the first time I walked into S&OP able to point at exactly which files, queries, and owners fed the plan, and I didn't flinch.

Scaling from here

Buying the Team plan was almost boring, which was the point. No procurement saga, no IT budget cycle, just a card and his cost center. His four analysts each kept their work private by default, which mattered to a team that guards its models, while the "Architecture & Value" rollup gave Arjun an aggregates-only view of where value and dependencies concentrated, never anyone's private working files.

When IT came in later for the security review, the conversation was easy. He wasn't asking them to own a tool. He was showing them one his team already ran.

Toward agentic & generative AI

Getting AI-ready turned out to be the natural next rung. With the estate cataloged and lineage mapped, Arjun had exactly the metadata layer an assistant needs to be useful without being dangerous. He scoped an "S&OP prep" assistant in Agent Studio first, defining what it should pull together before every cycle, rather than building blind and hoping.

Then he used Agent Access to give an approved planning copilot read-only, metadata-only context, so it could see how assets connected without ever touching the underlying numbers. The team stayed in control of what was exposed, and Arjun could explain, to the VP and to IT, precisely where the line was.