The Rise of Human Resource ( HR ) Analytics and the HR Role

The Rise of Human Resource ( HR ) Analytics and the HR Role

By: Ambalavanan Baskaran   |     December 1, 2017
Preparing for a Downturn
  In God we trust. All others must bring data

~W. Edwards Deming~

The above quote from W. Edwards Deming, widely considered as the father of quality management, tells the importance of data and its value for making decisions. The need for increased productivity requires that businesses have data-driven insights.  Data-driven insights have exploded in the last few years, but it has roots that go back a long time. Human Resources or HR was not far behind in quantifying and measuring data according to Jac Fitz-Enz, a pioneer in the Human Resource benchmarking. He talks about quantifying and accurately measuring  the productivity of all major HR functional areas in his 1984 HR classic book “How to Measure Human Resources Management” (now in its’ 3rd edition). The technological advancements, cloud-based HR systems, advanced analytics, AI, chatbots, VR, AR, gamification, automation, blockchain etc., have taken the HR world by storm and has transformed the way HR works. Of the many tools, we will discuss is People Analytics and its impact on the organization. In their book “Competing on Analytics” authors, Tom Davenport and Jeanne Harris say “the organizations competing to identify, retain and nurture the right talent are looking for distinctive business processes as a point of differentiation this has shifted the spotlight to talent management and on HR Analytics”.

 

What is HR Analytics?

HR Analytics is the process of analyzing the available people-related data to measure the effectiveness of the HR programs and identify patterns in order to make meaningful business decisions. The advent in analytics has helped HR grow from being transactional and reactive to strategic and proactive, by helping to grow from basic reporting to Business Intelligence tools that include dashboards, data warehouses and advanced analytics. HR Analytics gained prominence as software providers like SAP, Workday, Oracle and UltiPro offered the HR Analytical tools with their HRIS offerings. The terms talent analytics and workforce analytics are often used synonymously. HR Analytics uses mostly people-related data i.e.., payroll, HR etc., and encompasses people-related data and the business operational data.

 

Different Types of Analytics

There are four broadly defined types of analytics as described by Gartner’s Business Analytics Maturity model in Figure 1 below.

Adapted from Gartner’s Data Analytics Maturity Model

Fig.1 Adapted from Gartner’s Data Analytics Maturity Model

  1. Descriptive Analytics: Considered as the foundation of the business intelligence, primarily focused on what happened for i.e., employee turnover, new hire report, time to hire, number of openings etc.,
  2. Diagnostic Analytics: Focuses on why did it happen? It takes a deep dive at the data to understand the causes of events and behaviors: i.e. For employee turnover, the diagnostic analysis would help identify the type of separations voluntary vs Involuntary and/or the regions or the business units tied to the actual location or by managers, to review the hiring process or onboarding process or even training the managers.
  3. Predictive Analytics: Is the advanced stage of the analytics model and basis of Big Data. The predictive analytics focuses on statistical analysis, forecasting, co-relations and build predictive models based on the historical people-related data. In essence, it’s a future-focused analysis that predicts the future patterns based on the historical data: i.e., For identifying the flight risk employees helps to reduce employee turnover and improve the bottom line. The other example is in hiring, identifying applicants with a propensity to join or who can be successful at the organizations, thus helping the talent acquisition team to fill the position quickly.
  4. Prescriptive Analytics: Considered as the future of the Big Data, prescriptive analytics focuses on prescribing potential actions to guide towards a solution. Prescriptive analytics uses machine learning and artificial intelligence to understand future events and determine the best outcomes based on various scenarios, helping organizations to mitigate future risks. Prescriptive analytics is in its infancy.  According to 2014 Gartner’s prediction, it will take 5-10 years before prescriptive analytics is embraced by all. Currently, it’s used widely in transportation, oil and gas industries, travel industries.

 

Areas People Analytics Used

People analytics has wide application within the HR and the business context and the areas of applications are likely to grow multifold in the years ahead. The growth of people analytics is global and not confined to one country. Figure 2 shows the percentage of respondents rating people analytics as very important or important is globally very high. According to Deloitte’s Human Capital Trends, the highest percentage comes from fast-growing economies, around 82%, and the lowest coming from France at 48%.

Adapted from People Analytics Recalculating the route 2017 Global Human Capital Trends

Fig 2. Adapted from People Analytics Recalculating the route 2017 Global Human Capital Trends

The areas of application for people analytics are wide within the organization.  They include talent acquisition in identifying the right talent, minimizing bias in hiring, employee retention, increasing employee engagement, measuring culture, workforce readiness, and employee experience to name a few. For example, Google has turned people analytics into a winning culture with project oxygen. The tech giant has turned into one of the best companies for which to work, hiring the best, and retaining them with the highest engagement rate. Many sports teams use people analytics as well, the most famous being the Oakland Athletics. The team uses analytics to perform baseball player evaluations, which was well documented by Michael Lewis in his book “Moneyball”. New England Patriots, 5 time Super Bowl Champions, deploys people analytics extensively in selecting its players.

 

Should People Analytics Stay within HR

As an HR professional, I would shamelessly say it should remain with HR, but looking pragmatically and strategically the response is no. In a changing mobile world – millennial demographics, digitalized environment and exploding automation, organizations are looking for ways to innovate and prepare the workforce for the future of work. So, a network of teams is gaining popularity alongside the traditional team structures. Additionally, the people analytics in addition to the people/ HR data also combines the business data to get the groundbreaking new insights as shown in Figure 3. So, people analytics should be a shared responsibility with other business leaders.

Adapted from Bersin by Deloitte – The Geeks Arrive in HR- People Analytics is Here

Fig.3 Adapted from Bersin by Deloitte – The Geeks Arrive in HR- People Analytics is Here

How HR Can Contribute to People Analytics Success?

Focus on the right Problems: It’s absolutely important in understanding the business priorities, pain points and identifying the right problems. Work with the business leaders to identify the right problems.

  • Build a Strong Coalition: People Analytics success depends on and involves cross-functional teams and data across the operations,.  It is important to build a strong, cohesive cross-functional team that is skilled with the required data function, institutional knowledge, data visualization and consulting skills.  Create a cross functional HR Analytics Team
  • Leadership Buy-In:  People Analytics involves investment in terms of money and execution.  This requires Leadership!  The action matters most after the findings.
  • Develop an Analytics Roadmap: Develop an analytics investment roadmap for a wide spectrum of analytics
  • Enhance Analytics Fluency: Understanding the complex data points and insights are critical for the right follow-up actions: so train and prepare group of important leaders and managers
  • Avoid GITO: Ensure the right process. ensure clean people-related data, because the analysis is as good as what goes inside, “Garbage In Toxic Out” leads to the wrong outcome and creates data havoc.
  • Establish Data Strategy: People analytics rely on the intersection of data across the organization and external sources, so it’s important to have a data strategy to align/integrate the structured and unstructured data.


 

Baskaran Ambalavanan is a business-focused HR/Workforce Technology leader and the data analytics leader in Group50’s Organization Design and Development Practice.  This posting is an updated version of the article posted on the HR Exchange Network.  You can find out more about Group50’s HR Analytics program by calling 909-949-9083, dropping us a line at info@group50.com or requesting more information here.

 

 

 

This entry was posted in Continuous Improvement, Information Technology, Organizational Development, Talent Management, on December 1, 2017
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