They Requested It. I Built It. Nobody Ever Used It.
The article discusses the challenges faced by data professionals when delivering predictive models that go unused. It highlights the importance of explainability in models, especially in healthcare, where stakeholders prefer trusted clinical processes over complex algorithms. Additionally, it emphasizes the need for timely delivery to prevent stakeholders from seeking alternative solutions.
- ▪Data professionals often face the issue of delivering models that are ultimately ignored by stakeholders.
- ▪Explainability is crucial in healthcare, as clinicians prefer trusted methods over complex, opaque models.
- ▪Timely delivery of models is essential, as delays can lead stakeholders to abandon the project in favor of other solutions.
Opening excerpt (first ~120 words) tap to expand
Data Science They Requested It. I Built It. Nobody Ever Used It. Why good data work gets ignored after delivery. Hayden Kastens May 27, 2026 6 min read Share Illustration by Alghozy on Unsplash Stakeholders came to us asking for a model. We built a proof of concept. Got the green light. Delivered the model. Weeks of work…all to hear nothing. It’s a tale as old as time, and one that plagues data professionals everywhere, from analysts to ML engineers. So, what happened? Your Model is a Mystery Our profession is one rooted in modern computer science and technological advancements. Many of the most powerful solutions at our fingertips are ones that would have been too computationally expensive decades ago.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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