Employee engagement is all about the emotional connection an employee feels towards their job and their workplace. You can easily differentiate an emotionally charged culture from an unemotionally charged one. I’m sure we have all been in an organisational setting and experienced a sense of negativity. This can be identified verbally and through the body language of employees, as they are engaging with their clients or communicating between themselves.

Unfortunately, emotional culture management is almost non-existent in the majority of companies. This is particularly worrying since it is a positive emotional culture that ultimately engages employees to their workplace, higher job engagement leading to better staff satisfaction, loyalty and job performance and also ensures higher employee retention rate.

The difficulty with properly managing and improving engagement lies in finding a way to monitor its ever-changing levels. This is now possible with the introduction of big data tools and predictive analytics, which allow companies to collect large amounts of data in real-time and automatically analyse it using advanced algorithms.

The term ‘big data’ refers to large datasets as leveraged by industry drivers. Big data in HR seeks to evaluate and improve practices that include recruitment, talent development, retention and employee engagement among other things. It integrates and analyses internal metrics, external benchmarks, social media data and corporate data to deliver an informed solution. Once insights are extracted from the data, HR professionals can then start to understand what employees are feeling, what changes need to be brought about and discuss and implement strategy with managers and leaders.

The marriage of analytics and HR is transforming the way employees are appraised. HR is becoming less dependent on anecdotes as a tool to communicate employee satisfaction, performance and loyalty (“an employee said she is feeling this way”, “I noticed an employee was not performing”).

Furthermore, monolithic end-of-year engagement surveys are quickly becoming a thing of the past, with the industry moving towards regular bite-sized pulse checks that cover various aspects of human resources. In parallel with this trend, HR is driving towards becoming increasingly data-savvy, taking advantage of real-time analytics to understand and establish a fruitful relationship between employer and employee, and to act on warning signs in a timely manner.

Unfortunately, emotional culture management is almost non-existent in the majority of companies. This is worrying since it is a positive emotional culture that ultimately engages employees to their workplace

Successful fields like experimental psychology and other social sciences are founded on the assumption that certain aspects of human behaviour can be quantified and analysed. If you are in pain, a doctor might ask you to rank your pain on a scale of one to 10, and your answer is bound to be meaningful and useful to the doctor.

Analytics in HR aims to measure and predict similar subjective measures, be it happiness, job satisfaction, engagement or productivity. The way this is carried out is multifarious. At the most basic level, HR platforms offer employers toolsets that simplify creation and collection of pulse check data.

More advanced platforms might offer analytics on top of pulse checks and help visualise trends and anomalies that are relevant to HR. A particularly recent move is the integration of HR applications with office productivity frameworks and social platforms like Slack, Yammer and Confluence. This opens doors that were shut before, such as the possibility of performing real-time sentiment analysis or collecting chat participation data.

What, specifically, would an HR platform measure? How would it come up with a figure for employee engagement or happiness? Among a host of things the platform could measure are numbers derived from answers in surveys or pulse checks, such as likelihood of recommendation, foreseen tenure in number of years, current level of job satisfaction and immediate happiness.

It could also automate the collection of individual metrics that deal with participation in voluntary events and public online communication, out-of-hours contribution and the regularity of updates on project management platforms.

A good platform might aggregate these measures on the scale of teams or the entire company, including observed measures of retention, voluntary attrition rates and actual tenure.

This information is presented to HR and management on web dashboards that summarise the employee pulse at a glance. If real-time information is captured by the system, HR professionals can be alerted to key events as they happen, and integration with multiple services and mobile apps means that the HR is ubiquitous. Moreover, multiple sources of data and high volume allow predictive analytics to be applied, much as it has been successfully applied to other areas like retail demand and churn prediction.

The big data boom in HR is a few clock ticks away. It will not be long before forecasts of employee turnover, productivity and engagement can be made using a company’s historical data, and this together with the ability to quickly finetune and experiment with HR strategy will realise possibilities that until recently could only be dreamt of.

Nicole Caruana is a neuroscientist and co-founder of Massivemind, a data science, big data and artificial intelligence start-up. Maria Zahra is managing director of SurgeAdvisory. She has over 14 years of human resources and business advisory experience.

Independent journalism costs money. Support Times of Malta for the price of a coffee.

Support Us