
The workforce management function is one area that benefits greatly from the application of analytics, and HR organizations are well-positioned to implement and share the results with management. Labor is the most expensive cost to the employer. Making sure that scheduling and staffing is appropriate for the particular projects or programs underway helps keep costs contained and objectives met. Additionally, analytics can empower organizations to become agile and responsive through workforce tracking. Being able to influence cost and productivity levers through the availability of timely analytics allows management to have control over labor costs such as overtime.
Specific use cases where the deployment of analytics relating to workforce management add value include:
In addition to regular monitoring of ongoing timekeeping and scheduling, analytics can be powered by artificial intelligence (AI) and machine learning (ML) to identify patterns and offer predictions to improve future operations. Examples include examining behavior such as regular late arrival, Friday call outs, or early trench-out behavior. By having access to this information, management can head off labor problems and resolve issues before they become acute.
There are very real cost savings benefits associated with tracking and managing time and labor with analytics. Analytics can also help with the shortage of trained talent, a problem many industry sectors are facing right now. Despite some economic weakness, unemployment in the U.S. still remains very low, and organizations everywhere are finding it difficult to staff up to optimal levels. In the face of labor shortages, companies have to be confident that they are staffing intelligently to make sure that each shift has the right balance of talent. Analytics can lead the way toward having the right information on hand to make sound business decisions.
HR teams and their business partners on the front lines can both reap the benefits of improved oversight and visibility through the development and deployment of workforce analytics. These two stakeholder groups should come together to understand where their own analytics efforts currently lie in order to plot a course for further adoption of this technology to help mitigate existing pain points. What gets measured gets better.
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