Nebula Platform

We supported a company which lacked a data-drive approach to plan its capacity proactively in reducing operations costs by improving demand forecasting and capacity planning. We designed and delivered a sustainable forecasting solution enabled by a machine-learning model based on extensive client historical data and advanced-analytics methodologies. This led to an organizational shift in data culture and accountability. The total labor waste because of inefficient capacity planning was estimated at $24 million to $30 million, out of which $8 million to $10 million was targeted for savings in the first year.

An organization faced escalating costs across several hospitals, driven by poor staffing practices because of a lack of data-driven insights and controls. We designed, developed, and deployed an end-to-end automated process to identify the hospitals that were not complying with staffing norms and needed assistance, which enabled intervention in near-real time. Within three months after deployment of the dashboard, the group saw its hospitals improve their staffing-compliance levels by around 15 percent.

As one team, we completed a long-term project to implement and fine-tune a government payer’s episode-based payment program. We then supported the payer in the next step on its path, exploring the differences in members’ medical journeys in different risk-stratification segments and developing insights that would guide intervention design for high-risk perinatal patients. We delivered an interactive perinatal-journey visualization and empowered the payer to drive its own analysis offline and test its own hypotheses to support vulnerable populations better.