Industry: Government - County; Health & Human Services Department
Location: Minnesota
Project Type: Data & Analytics
Reduction in Staff Time Looking into SSIS Data due to SSIS data availability in an easy to interpret dashboard. |
Improved Caseload Management due to managers ability to quickly see metrics and then manage accordingly. |
Improved Budgeting and Forecasting due to better access to data at a summarized level, with the ability to drill down when needed. |
A large Minnesota county Health and Human Services (HHS) department provides a variety of services to county residents consistent with other counties in Minnesota, such as housing support, child welfare, and home and community based care. Leaders in the HHS department wanted to increase the ability to access and use data to improve operational efficiency and planning, thereby lowering administrative costs and improving service. The department uses a combination of manual and automated systems in the execution of its work, including the Social Services Information System (SSIS) provided by the state and Excel spreadsheets. There was no centralized store of data for use in analysis and reporting and it was difficult to get useful information out of these systems.
Superior Consulting Services built a reporting and analytics solution using the Microsoft Business Intelligence stack, including data extraction and transformation processes and Power BI dashboards, allowing the HHS staff to comprehensively view and analyze data.
Save HHS staff time currently spent manually collecting detailed data from multiple screens. | Save HHS management in manually collecting and summarizing data for use in planning. | Provide a central "source of truth" for reporting and analytics. |
This large Minnesota county HHS department now has a series of dashboards that allow staff to execute tasks more efficiently and allow managers to better monitor quality assurance and plan for the future. In addition, the county has a data warehouse and analytic data model which allow for streamlined access to quality data and the automated processes needed to refresh the data on a daily basis. The analytic data model and refresh processes are structured to allow expansion and modification as needed moving forward.
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