Predictive Analytics and Employee Engagement
From Personnel Development, to Strategic HR and then finally Talent Management, HRM has been continually evolving in the past decades. It has changed from a Business Function, to a Business Integration as a part of the organisational strategy.?
The pandemic exposed some of the shortcomings of the organisations across the world. Industry leaders struggled to keep their employees engaged. A bird’s eye view of this problem revealed how engagement was indeed not an induced problem, but a shortcoming rooted in the modern HR practices itself.?
Gallup in a recent article, announced that employee engagement in the United States had increased to 34%, but settling for these numbers can be tricky at this point.??
So what is this Employee Engagement and how is it different from employee satisfaction? – Researchers, Human Resource Professionals and Global Leaders, all have different definitions for engagement. Some define it as the emotional commitment, some as the extent of enthusiasm and dedication to work, and others as a working condition. This proves that engagement is an exhaustive topic. It can’t be a limited checklist of behaviours or deliverables at the workplace. As the context changes from organisation to organisation, the definition too would vary across employees in that organisation.?
There is no doubt that it is imperative for Human Resource Management to be Data-Driven and Predictive Analytics is the next big thing. However, given the hype around people analytics, the execution is somewhat negligible. Let’s understand why.?
The goal of predictive analysis in people management is simple - Manage Talent Better. This includes workforce planning, predicting future performance, effective succession planning, improving quality of career and performance metrics in conversations, predicting the learning and development needs and finally WINNING THE WAR FOR TALENT.?
Employee Engagement is not just an initiative, it is an amalgamation of many things; Attracting the right talent pool, Hiring the right Talent, Performance Management Systems, Feedback Mechanisms, Learning and Developmental Needs, Leadership, Succession Planning and the Perception of Justice in the organisation, which ultimately translates to meeting Talent Needs.?
So why are organisations not satisfied when they use data to run their Talent needs??
Data can only tell you half the story. Predictive Analytics for People can’t be implemented without people.?
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Let’s simplify this thought using basic human behaviour. A person is more likely to accept a solution or a decision when he/she is involved in the process. In a world where empowerment and empowering is the norm, no one likes to be told what to do. In the organisational context, the intimation of this behaviour is seen everywhere. For example, an employee is more likely to effectively undertake an L&D intervention when not just the organisation, but the employee himself feels that it is required for his career growth in the organisation and understands the implications of the same in his professional and personal life. The funnel down of these decisions need to be personal and accepted.?
Another prominent example is the use of sentiment analysis by few organisations across the world to gauge their employee behaviours upon the announcement of a new Leader or CEO or upon any major policy changes. Understanding what and when phrases and words are being used can help reduce employee ambiguity and ensure a good response even from the fence sitters.?
If organisations want to successfully build Predictive models to drive employee engagement, the first step towards it is understanding that they need to change their approach from building-algorithms-to-make-decisions-for-people to building-algorithms-to-help-people-make-better-decisions.?
People need to feel empowered in an organisation. Over-engineering this process can have negative implications. What is required is for organisations to enable their employees to become decision makers by providing them with relevant information. Using this data, employers need to tell employees how they have performed, show them the roadmap, the plans the organisation has for them, and how they can progress and stabilise their careers. It has to be a two-way conversation.?
Google, a tech Giant, known for its People Analytics Initiatives in their engagement framework, derived a program called gDNA from a longitudinal study. The results of the same were astonishing. But what was it that they did so differently, which made this program successful? They transformed their approach from making decisions for their employees to making their employees the decision makers. As Prasad Setty, The VP of Digital Work Experience at Google, said “People should make People Decisions”
Employee Engagement is not an isolated function of HRM anymore. With HRs as facilitators, employers across domains and functions have to participate and drive engagement on an individual, team and organisation level.?
Employers need to watch out for Dangerous Correlations and Feel-Good Metrics. Vanity Metrics look good on paper, but they can’t accomplish much. Engagement cannot be accomplished by a mechanistic method that manipulates employees' loyalty and emotions in order to obtain discretionary effort. Employees can easily see through such efforts and become cynical and disillusioned. They need actionable metrics that are personal and customised.?
Organisations have to become better at connecting the dots, understanding, analysis and drawing meaningful insights from data – they have to become powerful story tellers. Analytics that needs to be introduced should be from the perspective of the employees capabilities and potentials and building an environment for them to nurture their careers whilst building a successful organisation. As Steve Wayne rightly said, “ Human resource isn’t a thing we do, it’s the thing that runs our business.”