Pharmacy Revenue Prediction for OptioRx with Azure Pipeline
Josh MiramantNovember 18, 2020
OptioRx, a private equity-backed owner and operator of specialty compound pharmacies, needed to predict quarterly pharmaceutical revenue to improve revenue planning and predict fraud. The primary challenge was that the data contained significant seasonality with irregularities occurring in both doctor and pharmacy level data.
Blue Orange was brought in to create a production model that could be integrated into price forecasting. Due to our success in the prediction project, OptioRx engaged Blue Orange on a separate project to scale its pharmacy ingestion data pipeline.
Vertical: Revenue Forecasting
On the initial prediction project, our data scientists worked collaboratively with technical client stakeholders through Jupyter notebooks and feedback sessions to develop a production forecasting model. Our solution implemented ensemble learning and built on AWS and open source prediction frameworks to outperform previous approaches.
Blue Orange was brought in to create a production model that could be integrated.
A second major data challenge OptioRx faced was the integration of newly acquired pharmacy data systems. Highlighting our cross-cloud expertise, Blue Orange developed a scalable Azure data pipeline for ingesting new pharmacy data. After gaining familiarity with the previous pipeline, we developed a full project backlog, integrated two initial new pharmacies, and implemented an efficient data lake and data cataloging pattern to simplify future integrations.
Josh Miramant is the CEO and founder of Blue Orange Digital, a data science and machine learning agency with offices in New York City and Washington DC.
Miramant is a popular speaker, futurist, and a strategic business & technology advisor to enterprise companies and startups. As an example of thought leadership, Miramant has been featured in IBM ThinkLeaders, Dell Technologies, Global Banking & Finance Review, the IoT Council of Europe, among others. He can be reached at firstname.lastname@example.org.
They help organizations optimize and automate their businesses, implement data-driven analytic techniques, and understand the implications of new technologies such as artificial intelligence, big data, and the Internet of Things.