Capabilities

We audit policy and protocols with rigorous analysis and reporting to measure their effectiveness at achieving business goals. We then advise where and how to target pain points for improvement.

We work with data of all kinds, from SQL to proprietary databases such as ARM, to csvs, to utter disasters. Our data engineers are highly skilled at reshaping everything into a tidy tabular format, and can help you organize your data management and storage to avoid those messy disasters in future.

We help managers to control and contain spread by helping them to anticipate risk, so they can intervene before the outbreak.

All models are wrong, but some are useful – validation helps us quantify just how useful a model really is at predicting outcomes. We ensure our clients know how confident they should be in the tools you’re using.

Deployment is all about the end-user. We handcraft apps with your end-user needs in mind, so they can confidently interface with the predictive models built to guide their decisions. We host in the cloud, so these tools are accessible whenever and wherever they’re needed.

Experiments are expensive. Industry standards like t-tests are easy to do, but powerful methods like mixed models can reduce necessary sample size – and costs. We guide sample size for these methods using power simulations, so you can answer business questions efficiently.

Cause-and-effect, and correlations – quantifying the strength and direction of patterns is the core of what we do. We have deep expertise in analyzing relationships between biological indicators and their predictors in the field, including longitudinal, spatial, and time-series data.

We use SEMs to tease apart nuanced relationships among many variables that feed into business metrics, helping out clients to zero in on the factors that really matter to their bottom line.