stakeholders
4 stories filed under stakeholders on Beyond Market Intelligence. The newest of them: “How to Build a UX Investment Case That Gets Funded”, “From Code to Influence: Shaping Outcomes Beyond Engineering”, and “Why stakeholders expect zero errors from models designed to improve decisions”. A strong UX idea rarely sells itself. Great engineering usually stops at the code, but Brad Grantham argues it shouldn't end there. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every stakeholders story on Beyond Market Intelligence, newest first.
How to Build a UX Investment Case That Gets Funded
A strong UX idea rarely sells itself. In this piece, Alex Williams walks through a worked example showing how to define business value, calculate costs, and test causality before presenting to leadership. It is a practical approach for building a case that holds up. For more on designing with intent, our piece on the death of the button offers a useful counterpoint.
From Code to Influence: Shaping Outcomes Beyond Engineering
Great engineering usually stops at the code, but Brad Grantham argues it shouldn't end there. In this talk, he maps the journey from individual contributor to technical leader, focusing on how to translate deep expertise into business and legal fluency. It's a practical push to communicate with non-technical stakeholders and trade ego for team empowerment. If you're looking to broaden your influence, this offers a clear path forward. For a related read on expanding technical horizons, explore our piece on Spritely's architecture.
Why stakeholders expect zero errors from models designed to improve decisions
There's a moment every data scientist knows well: the model performs safely in validation, stakeholders sign off, and then one wrong call triggers a cross-examination. It's frustrating, but it's also revealing. The expectation of a 0% error rate isn't about math; it's about trust and how we frame machine learning's limits. We never promised perfection, yet we often present models as if they're infallible. That mismatch is worth examining.
Build Platforms Developers Embrace and Business Leaders Champion
Platform teams know the frustration: build something impressive, watch developers ignore it. Lucas Hornung and Christian Matthaei tackled this head-on, offering lessons that feel refreshingly practical. Their advice is direct, get visible to management, listen to stakeholders, and measure what matters with DORA metrics. Make the hidden pain personal, and suddenly the value becomes undeniable. It is a human-centered approach to a technical problem, and that is exactly why it works.