Optimizing a Modern Workforce Requires Analysis

Today’s HR executives need more than great people and management skills. They are also increasingly expected to have sophisticated data analysis and data technology skills.The modern workforce is a whole new creation—a mix of older workers and Millennials who couldn’t be more different. Toss in a constantly shifting matrix of full-time and part-time employees, “gig” freelancers, and contingent contractors—and it quickly becomes challenging to examine how the workforce is performing and producing, as a whole and in parts. That’s where data analytics enter the picture.

Demand Is Growing for Skilled HR Data Analysts

According to SHRM, 54% of organizations already require employees with data analysis skills in the HR department. More than half of HR departments are already using big data in their strategic decision making processes, especially in the areas of:

  • Sourcing, recruitment and selection of candidates
  • Identifying causes of turnover to create employee retention strategies
  • Managing talent and performance

In spite of sharply rising demand for data analysis skills in the mid to upper levels of management, 78% of HR professionals surveyed reported having a hard time finding and recruiting employees with the right data skills.

What Analytics Can Offer HR

Data analytics and technology go hand-in-hand. You need technology to capture large amounts of information (big data) and store it in a centralized repository where it can be accessed. Then you can apply business intelligence technology to help you spot patterns, identify trends, analyze what it all means and use those insights to help you make more informed workforce decisions.Analytics is part science and part art. The numbers are certain, but what they mean and how to tell the story to decision makers requires instincts and experience.There are three types of workforce analytics that HR departments could apply to problems:

  1. Descriptive analytics tell the story of what is happening or has happened. Descriptive analytics are focused on facts by-the-numbers and outcomes. Two examples in HR benefits would be the YOY cost of employee healthcare and what percentages of employees took single coverage versus spousal or family coverage. In recruiting, source of hire is an example of descriptive analytics. These analytics can often be sliced and diced in different ways so you can analyze by business unit, product line, functional teams, etc.
  2. Diagnostic analytics seek to explore ‘why’ a trend is occurring. These analytics test and measure processes and causes. An example from HR would be the reasons given during exit interviews for why employees were leaving the company or the results of a survey conducted among Millennial employees about preferred recruiting methods.
  3. Predictive analytics build on the things learned through descriptive and diagnostic analytics to build a model that empowers you to predict the outcome of future strategic decisions. Taking recruiting for an example, descriptive analytics revealed the best sources of hire and recruiting costs, and your Millennial survey discovered the most effective recruiting methods. Combining these data can build a model to predict how future recruiting costs and outcomes might be impacted by a shift in recruiting methods.

Technology Delivers Data You Can Use

HR executives need to be able to generate meaningful insights about how to optimize workforce utilization and labor costs. They also must be able to produce compliance reporting at a moment’s notice. Human Capital Management (HCM) software can consolidate all HR-related information about every employee in a single central repository of information, making it easier to ensure accurate, reliable reporting. Learn more about how Asure Software’s Human Resource Management solutions can place the data you need at your fingertips.

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