Nov 01 2021

8 Steps to becoming HR Analytical

“It is clear that all HR professionals must be fluent in HR analytics, if the function is to be effective at helping to achieve business goals. This fluency includes gaining basic analytical & data management skills etc”

by  Dr. Fermin Diez, PhD, SPHR, CCP, IHRP-MP, Adjunct Professor , SMU & NTU

A 2018 survey by David Green and Ian Bailie, at myHRfuture, identified “People analytics” and “digital HR/HR technologies” as the top two most important skills HR professionals need to develop in order to prepare for the future. 

It is clear that all HR professionals must be fluent in HR analytics if the function is to be effective at improving individual performance, enhancing the employee experience, and helping to achieve business goals. This fluency includes gaining basic analytical and data management skills, including basic knowledge of visualisation, finance, and statistics. 


There is no shortage of data for HR professionals. From recruitment data to promotions, productivity, absenteeism, timesheets, expenses, and retention metrics, data that can be used to craft better workforce strategies is being created every day. Yet many HR leaders struggle to realise the power of people analytics, choosing instead to rely on instinct and experience. If you really want HR to be a strategic business partner, then you need to persuade with data.

Yet many HR professionals are reluctant, having joined the profession because they like working with people, not statistics. In addition, a lack of quality data and analytics skills are among the biggest barriers to embracing data analysis, according to webinar surveys by the artificial intelligence talent management platform Pymetrics.

“It’s easy to become overwhelmed. How do we bring the data together in a meaningful way?” asks Pymetrics’ Global Head of Consulting Psychology Michelle Hancic.

“Many companies are still storing data across different systems,” observes Future of Work expert Adrian Tan, who works with companies to drive productivity. “You have the HRIS. You have an Excel sheet here, another one-trick pony over there. There’s a lot of duplication and human error. Trying to centralise all this into a single source of truth is a key challenge I’m seeing for many businesses in Singapore right now.”

Eight Steps to Better Insights

How can HR leaders overcome data paralysis and embrace analytical solutions? My book, “Fundamentals of HR Analytics: A Manual on Becoming HR Analytical,” details an eight-step process for HR departments to provide better insights and more precise recommendations in answering business questions through an HR  lens:

  • Define a business problem: That might sound basic, but HR leaders often start with a human resources issue, like how to reduce attrition. That’s a means to an end, not a business goal. Think instead about how to improve corporate profits or revenue.
  • Formulate a simple hypothesis before digging into the data:  Looking at the numbers too soon could lead HR professionals in the wrong direction. An example of a hypothesis that can be tested is: “Adopting an incentive system will increase branch profitability.”
  • Collect data: Don’t stretch the team too thin—only collect the data needed for the analysis.
  • Analyse data: Use the right statistical tools for the analysis
  • Reveal insights: Keep an eye out for insights that reveal whether the hypothesis is valid.
  • Make an HR recommendation to improve the business situation: Each insight should lead to a single recommendation for improvement. For example, “There is a single source of talent that will drive our sales higher.”
  • Tell a story: To make an effective data-driven argument, craft a powerful story. The best presentations are often short, featuring a proposed solution on slide one and the data-driven rationalization on slide two.
  • Monitor the impact: Implement the recommendation, then measure to see if the intended outcome is achieved.

There are analytics capabilities built into most new and upcoming software offerings, which have increased our ability to collect and analyse data. This data holds the promise to help HR analytics teams understand how they can improve the employee experience.

Real-time sentiment and emotion recognition analysis is a fast-growing field, which is increasingly being used to measure how employees are feeling. There is technology to analyse a person’s facial nano expressions and gauge their emotions such as happiness, anger, or sadness. It can also predict if the person is truthful or surprised. Similar technology for voice analysis is already available.

Biosensors and wearables are widely available for personal health and fitness, providing data for physiological metrics (heart rate, sleep patterns, blood pressure, etc.), as well as various environmental metrics (distance, altitude, etc.).

Similar devices are used in the workplace to help improve health & safety – for example, devices can be worn by truck drivers to alert them if they are falling asleep while driving. Other devices are being used in high-volume work settings to help improve productivity by alerting employees when they are not focused or when their stress levels are too high.

However, future applications do not need to be so individualised. Improving any HR process is a good opportunity to apply a design-thinking mindset; get feedback from users, supervisors, vendors, and other stakeholders; use the feedback to redesign the process; pilot the new approach; and collect data to see if it is better than the old process. Is it cheaper/faster/better and does it help to increase productivity/revenues/profits? Does it make the employee experience better?

Many questions remain about this ability to track and use data. We need to overcome the lack of skills to analyse the data. Technology, and the resulting data, must be validated, especially when it comes to interpreting feelings and thoughts.

The new technologies have access to sensitive areas, raising concerns about data storage and usage, and there may be some who want to hoard or misuse this data, which will lead to regulation at some point on how it can be used and interpreted.

Personal data protection legislation is already in place in many jurisdictions and will likely continue to evolve rapidly as technologies become more powerful and available.

There will also be many HR professionals and employees who will resist change. The handling of sensitive information on an employee’s health or feelings must be handled with extreme care.

The HR function will need to continuously monitor and update its policies and communicate these to employees – about what type of data is being collected, for what purpose, for how long, where it is stored, and the data protection mechanisms in place.

In summary, HR practitioners need to become more analytical if they wish to keep pace with the new demands on the profession and be an integral part of a more data-driven, yet human-grounded, future of the HR profession.

 

Dr. Fermin Diez has more than 35 years of experience in HR, which includes Consulting, Corporate and Academic roles across continents.

He is an Adjunct Professor at Singapore Management University (SMU) & at Nanyang Technological University (NTU). He is the co-author of three books: ‘Human Capital and Global Business Strategy’; ‘The Remuneration Handbook: International Edition’ & ‘Fundamentals of HR Analytics’.

As a consultant, he has advised Public & Private sector organisations at the Board & C-Suite levels. He has also managed the P&L in several geo locations & businesses. As an HR leader, he has been Regional Head of HR for two large MNCs in AsiaPac and in Latam.

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