In the Senior Housing industry, though Data is being collected there is no proper mechanism to collect, store, and analyze the data. Most of the data being collected is dispersed across siloes or in spreadsheets making streamlined decision-making difficult. Another challenge faced is wrt to the Workforce planning with the existing data capabilities.
The Institute of Aging recommends sensors embedded in Internet of Things (IoT) devices to help the elderly. By monitoring and finding trends in the data- For example. identified sleep heart rates that rise above 90 beats per minute can be taken as a red flag - can help the senior living caregivers opportunity to monitor and support the residents while preserving independence.
With analytics in Senior Housing, it is possible to identify the possible individual churn with the residents. It can be done by Bucketing or Clustering the profiles of various tenants based on their possible risk based on their profile and history of activities. Preventive measures can be taken on the clusters with high profile risk.
With connected Planning evaluate multiple potential development sites with multiple Key performance indicators to identify the optimal location and determine the best possible positioning for the site based on the parameters. You can also visualize the multiple competitor mapping and/or previous residence of the clients for a better understanding.
