CAST Case Study: Establishing a Center of Excellence for Intelligent Automation
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New CAST Case Study: Data Analytics Transform Decision-Making
Overview
Ingleside, a network of continuing care retirement communities in Washington, D.C., partnered with NuAIg to transform its data analytics capabilities and improve decision-making across its operations. The initiative aimed to address challenges like fragmented data, inefficient manual processes, and limited real-time insights into key metrics. By leveraging AI-driven solutions, the organization was able to integrate data from multiple sources into a unified platform, enabling real-time monitoring of census and financial data, healthcare metrics, and donor information.
Business Challenge
Fragmented data across multiple systems – PointClickCare, Excel, and Raiser’s Edge
limited visibility into key operational and healthcare metrics
Manual data entry and inconsistent reporting processes
Increased administrative burden for staff
Ingleside was struggling with siloed data that hindered timely interventions in resident care, leading to difficulties in tracking health indicators like readmissions and falls. Ingleside also lacked real-time insights into financial performance and donor engagement, which impacted budgeting and fundraising efforts. These challenges underscored the need for an integrated, real-time data analytics solution to drive better outcomes and decision-making across its communities and foundation.
Impact
25%
Improvement in response time
40%
Reduction in staff time
NuAIg Solution
NuAIg’s approach centers on transforming fragmented, manual data processes into a unified, real-time analytics ecosystem tailored to aging services.
We begin by identifying key performance indicators through stakeholder consultations, then design role-specific dashboards that integrate data from systems like PointClickCare, Excel, and Raiser’s Edge. By automating data extraction, consolidation, and visualization using secure SQL databases and Power BI, we empower providers to make faster, data-driven decisions that enhance operational efficiency, care quality, and financial performance across their communities.
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