Workforce Analytics

WorkforceOptimizer – What is Workforce Analytics

By 18 October 2018 No Comments
Workforce Analytics and Predictive Analysis

Workforce analytics is a combination of software solution and statistical methodology that applies certain work patterns and models to staff-related data. These sets of prefixed data allow business leaders and decision-makers to optimize human resource management. In the previous few posts, we explored how mobile technologies disrupted workplace.

These technologies have grown a lot more sophisticated in recent years. With big data analysis on workforce movement and shift in patterns, it produces data beyond hiring and adjustment of department structures.

Why is Workforce Analytics important for your business?
Workforce analytics is all about human data analysis, at the level of acquiring and managing staff resources, including their time and skill sets. It is associated to workforce-planning issues, such as operational and strategic aspects. The ideas behind workforce analytics is beyond the fundamentals of staff data analysis; It offers far more insights into staff data. With current analytics technologies, workforce analytics digs deeper, wields more influence and presents data more visually than previous versions.

Modern workforce analytics allow HR practitioners to test and provide information that business leaders and decision-makers may have never thought of. The data from workforce analytics in turn, leads to greater potential to provide a positive statistical return on human resource planning decisions, such as hiring and labour planning.
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Workforce Analytics and Predictive Analysis
Workforce Analytics has a direct linkage to predictive analysis of staffing. Like with many forms of business forecasting, predictive analysis is an important piece to human capital management. For example, by combining workforce analytics data and predictive analysis business forecasting, a HR practitioner can examine organization’s turnover rate, and this may help various companies to predict which departments to shoulder the most risk of key employees leaving, allowing HR managers to get ahead of the problem.

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