When leveraged effectively, workforce data analytics can be a powerful tool for reducing labor costs. It’s no secret that driving down premium labor expenses is one of the most effective ways to balance the budget. However, reducing premium labor costs is easier in theory than it is in practice. Often, putting staff into overtime or using external contract labor can seem to be the best option available for filling last minute staffing holes. Without visibility into all possible labor resources, the best decision for the organization isn’t always the easiest decision to make. But, using data analytics makes it easier to determine and act upon the best staffing decision.
A recent survey conducted by API Healthcare and HealthLeaders asked more than 100 healthcare leaders what workforce tactics successfully enabled them to reduce expenses, and at the very top of the list was monitoring and reducing overtime. The use of workforce data analytics makes this tactic particularly effective. The ability to project overtime can enable an organization to generate significant cost savings.
Software that analyzes employee data, like hours already worked and hours scheduled to work, allow for proactive adjustments that can eliminate overtime before it even happens. By providing this data to managers on a real-time basis, it allows them to make more cost-effective decisions during those last minute situations that require schedule adjustments. However, not all overtime falls neatly into this category. Incidental overtime presents an equally frustrating challenge.
The accrual of small or incremental overages across a period of time can be just as detrimental to an organization’s budget as traditional overtime. When an employee clocks in a few minutes early, skips lunch or stays late, these costs slowly but surely add up over time. When taken cumulatively, across an entire organization of thousands of employees, the costs can easily equal millions of dollars each year. In this scenario, data analytics can help identify patterns that help managers develop policies that can eliminate these small, but costly activities. It is worth a reminder that in addition to providing data analytics, any technology vendor should have experience navigating state and federal labor laws to help ensure policy changes do not place the organization at risk for lawsuits or labor law violations.
Fluctuations in census and acuity can present challenges to even the most efficient organizations. In a common scenario, a hospital may look to external resources to fill open shifts when internal resources are tapped out. The cost of this premium resource can quickly get out of control. Hospitals that focus on sizing their staff to avoid both under- and over-staffing are better able to cost-effectively manage their resources. One such way is by creating an internal resource pool. By looking to available internal resources before incurring overtime or external premium costs, an organization can generate a significant cost savings without compromising high quality care delivery.
Data and analytics provide a big picture view of patient needs and available resources. By matching resources with needs it is easier to make optimal staffing decisions for the entire organization.
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