Do’s and Don’ts of HR Analytics

By: Together Abroad 02-04-2019

Categories:* Daily employment news, ** HR Analysis, ** HR daily news, ** HR Learning & Development , ** HR Strategy,

Do’s and Don’ts of HR Analytics

People are the core of business. It is known that, among executives’ global business concerns, human capital is the top issue. Organizations that can attract the right skills, manage talent and utilize its capacity effectively, and retain employees will be paving their way for long-term success. Today, however, human resources departments (HR) of most organizations are generating enormous amounts of data that can be difficult to assimilate. The question is how to turn this data into valuable insights that support decision making. Here is where HR analytics comes into play.

Human resource analytics (HR analytics) is the discovery, interpretation, and communication of meaningful patterns in the human resources’ data in a way that promotes effective decision making, helps improve employee performance and increases return on investment. HR analytics relies on statistics, computer programming and operations’ research to quantify performance within recruitment, HR processes’ optimization, payments, and workforce development.

Among HR functions, recruitment has the highest business impact. This is why the benefits of data driven recruitment are so valued. Dr. John Sullivan—an internationally known HR thought-leader from Silicon Valley, best-selling author, and professor—cites Google, one of the most valuable firms in the world, as an example regarding its data-driven approach to people management decision-making. He quotes Google’s chairman: “All people decisions are based on data and analytics. We apply the same level of rigor, analysis and experimentation on people… as we do the tech side.” Analytics promotes decisions based on facts, rather than intuition. It increases hire quality, improves candidates’ experience, enables diversity monitoring and embedment, and supports workforce planning to avoid over-hiring that can be costly and under-hiring that can reduce productivity.

According to Bernard Marr—author of Data-Driven HR, speaker, and strategic business & technology advisor—the most important HR analytics tools managers should use to understand the people-related side of their business are those focused on talent availability, competency acquisition, capacity, employee churn, corporate culture, recruitment channels, leadership, and employee performance. But analytics would only become powerful if it meets the strategic preferences of each organization. In other words, it is fundamental to present significant talent data in the most impactful way for the core of the business. John Sullivan suggests the following HR analytics approach:

  1. Monetary value: Money is the language of business. Metrics transformed into their correlated monetary impact have the greatest value. For example, a turnover metric of 20% will reduce the sales revenue by €2,3 million.
  2. Revenue: Metrics showing hires that increase revenue have the highest value. For example, top-performing hires that have a multiyear, long-term impact.
  3. Innovation: Innovators may have 25 to 100 times greater business impact. The best metrics will focus on the recruitment, retaining and development of innovators.
  4. Strategic impact: Metrics related to the corporate strategic goals are the most valued. They will determine action.
  5. Predictive: Metrics and data analysis that help foresee future behavior and trends will be the most impactful ones.
  6. Results: Metrics should demonstrate results and outputs to the business. 
  7.  Actions: Together with the metrics, provide a list of the required actions.

One way to succeed with talent acquisition analytics, for example, is to choose those recruiting metrics that have the greatest strategic impact in the business. Some important metrics are:

The benefits of HR analytics, nevertheless, are not always evident, graspable, or easy to be produced. There are pitfalls interwoven in the use and application of technology that might counteract the desired results. Applicant Tracking Systems (ATS), for example, stops its usefulness at the point of hire because the data is usually kept in various systems. When data is siloed, or contained within several different systems, it becomes very difficult to collect and organize historical information, which limits the forecasting ability as well. Investing in technology systems—market Cloud-based solutions—that collect all the data in one place allows access to the whole recruiting pipeline and the historical information, enabling better and faster hires.

Besides technology, a thorough combination of HR analytics and strategic vision will be key for success. David Creelman—CEO of Creelman Research and Fellow of the Centre for Evidence-based Management in Europe—comments on the mistakes in HR Analytics when the wrong people is accountable for the analysis. He says: “Since many HR leaders don’t have a good sense of how to get value from analytics, they move it off their plate by passing it to the HR reporting team or to some newly hired data scientist.” It is important to remark that analytics and reporting are not the same, although both areas should work together. People leading analytics should be business people who understand the goals and key performance indicators of the organization. And both, analytics and reporting teams, should be closely linked to average HR professionals that can handle everyday analytics on their own and know how to use reports’ data.

HR analytics will be most successful when it can rely on technology and, at the same time, is aligned with the strategic vision of the company to support decision-making. Analytics, woven into all HR functions as a whole, will help human resources to become a business-focused and data-savvy department, an asset for the organization, and an impactful source of benefit to all employees as well.

Do you require HR support? Do not hesitate to contact us!

Written by Paula Arellano Geoffroy for Together Abroad.