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The full details of this HR analytics case study and the statistical tests can be found here. Achieving an optimum staffing level. Another interesting HR analytics case study was about reaching optimum staffing levels. This was measured through A/Btesting. So did hiring older drivers as they were more experienced.
These data scientists design, define, and implement metrics, run and interpret experiments, create dashboards, draw causal inferences, and generate recommendations from modeling and measurement. In slightly bigger teams, each of these may be a role staffed by one or more individuals. Modeling Scientist Who consumes the output?
These are all very different strategic needs requiring different implementation approaches and performance metrics. When formal research trials aren’t practical, providers will need to embrace A/Btesting and learn to more rapidly evaluate the effectiveness and scalability of these technologies. The challenge is huge.
Citation metrics are widely used in faculty evaluations and routinely come up in tenure reviews. Amazon expands and shrinks by tens of thousands of workers at a time through the use of temporary staffing companies for its warehouses — it added 80,000 temporary workers for the 2014 holiday season.
There’s a long laundry list of skills that are critical, but not often considered core to the product: adtech integrations, signup funnel A/Btesting, optimizing notification delivery, testing price points, testing cohort curves, etc. This can work, but then the team needs to be staffed properly.
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