Today’s total talent management strategies rely on analytics to execute workforce objectives. For extended workers who comprise nearly half of enterprises’ entire labor force (49%, according to our research), analytics are even more crucial to developing metrics and optimizing performance. Recent Ardent Partners and Future of Work Exchange research indicates that 81% of organizations cite the improvement of contingent workforce management (CWM) analytics as a priority, highlighting the importance of deeper, more insightful data and analysis.
CWM Analytics for Insights
According to Beeline, a leading contingent workforce solution provider, “For many organizations lacking formal analytics and reporting on their contingent workforce, identifying key metrics can even be challenging.” The focus on analytics goes well beyond hiring, scheduling, and payment data, to include deeper areas of concentration. The following are several analytic subsets imperative to contingent workforce management and performance.
Spend Management
Enterprises can utilize CWM analytics to help track and manage their spend on contingent workers. This includes data on billing rates, contract terms, and other expenses related to the use of contingent labor. Utilize data visualization tools such as dashboards and reports to make it easy for stakeholders to access and understand spend data related to CWM.
Beeline states, “Understanding bill rates, pay rates, and the margins between them per vendor, can be an incredibly powerful negotiation tool. Armed with this data (and more), you can have productive, data-backed discussions with vendors, enabling you to clearly understand what rates vendors should offer to make themselves more attractive and competitive than others.”
Performance Metrics
Measure the performance of your contingent workers with metrics for time-to-fill, retention rates, and quality of work. The Future of Work Exchange regularly reports how enterprises are pivoting to skills-based hiring. As those approaches increase, performance metrics for extended labor will be paramount to total workforce strategies and planning initiatives.
Such data can identify where talent gaps exist as well as which extended workers possess the skills for more critical projects. Also, don’t overlook analytical tools such as artificial intelligence and machine learning to synthesize and identify patterns and insights.
Legal and Regulatory Compliance
A global contingent labor pool means greater attention to legal and regulatory compliance. Analytics can help organizations remain compliant by tracking data on worker classification, hours worked, changes to regional laws and regulations, and other compliance-related metrics. “You need to know, for compliance, payroll, and project planning purposes, exactly how many employees are engaged in your projects at any one time – so you can track the costs, project status, and progress compared with statements of work (SoWs),” adds Beeline.
Workforce Planning
The Future of Work is not only focused on workforce needs today but the requirements for tomorrow as well. By analyzing historical data on contingent labor usage, organizations can make informed decisions about when and where to engage extended workers long term. Historical data combined with predictive workforce analytics can provide a holistic picture of future needs. Continuously monitor the data and adjust your strategies as needed to optimize your CWM requirements.
Organizations must take control of their CWM analytics if they hope to optimize their use of contingent labor, minimize costs, and improve the performance of their workforce. It’s a combination of being cost-effective while enabling data-driven decision-making to reach performance targets. HR and business leaders will only rely more on big data and analytics to accomplish enterprise workforce objectives. CWM will be at the center of those insights and decisions.
