Occasional posts on topics I'm thinking through that are mostly at the intersection of organizational research, developer experience, data quality, and applied analytics.
A blog-style article arguing that People Analytics maturity is not a single predictive ladder. The framework separates awareness, capabilities, and system readiness so teams can see where production ML is strong, exposed, or under-governed.
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In development
This piece will unpack maximum entropy regression as a practical way to model outcomes from constraints while keeping uncertainty, calibration, and assumptions visible.
In development
This article will compare interpretation frameworks for workforce models, separating technical explanations from the decision-use explanations leaders need before acting on predictions.
In development
This piece will outline a reporting format that pairs model performance with uncertainty, practical importance, and signal checks so stakeholders can see when a result is strong enough to act on.
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These posts are loosely connected to my research and applied work. If you'd like to discuss any of these topics directly, feel free to send a note.