Employee Engagement Analytics: How to Do it and Add Value
Employee engagement is a hotly debated topic. Let’s take a look at an example in sports. Tennis legend Rafael Nadal writes in his autobiography:
“I put the two bottles down at my feet, in front of my chair to my left, one neatly behind the other, diagonally aimed at the court. Some call it superstition, but it’s not. If it were superstition, why would I keep doing the same thing over and over whether I win or lose? It’s a way of placing myself in a match, ordering my surroundings to match the order I seek in my head.”
Rafael continues to describe how this gives him a feeling of control over his environment and points out that it is the singular most important factor for him for being mentally “engaged” in any match!
“A feeling of control over our immediate environment”. Human engagement is a complex emotional state and carries multiple connotations. But doesn’t the tennis legend nail its core essence?
Amusingly, the Oxford dictionary focuses on the term engagement in reference to marital relations and in this context its meaning is closer to “commitment rather than control” (I sure hope so!). But be that as it may, that definition is only a part of what engagement is.
A sufficiently encompassing technical definition from an organizational psychology perspective is generally accepted as:
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“Quantifying human involvement towards defined objectives”. Within the scope of this definition, a host of influencing factors could be identified, provided the objectives are well defined in the first place and involvement can be quantified (see picture below). Is that true for HR?
Let’s explore! Engagement through the eyes of HR A.K.A. “Employee Engagement”
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Tim Young, VP of Workday, writes “employee engagement is paramount to attracting and retaining talent – and remaining competitive in the global market. Research shows a direct link between employee engagement and corporate performance”.
Yes, of course, the crux of engagement in HR needs to be centered around employee productivity. Bills need to be paid, sans doute Monsieur Young!
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But there is also an interesting counter point here
Global pioneer of workforce analytics Greta Roberts says “Engagement is not performance”. She emphasizes that engagement doesn’t necessarily drive business KPIs and there could be dangerous correlations with other, unrelated factors. “It’s a tricky metric”.
This is possible. The tricky part is that the hypothesis of a relationship between engagement and productivity can only be validated after thorough employee engagement survey analysis, followed by long-term observation. This is often an accepted constraint in organizational psychology/HR and the global pioneer of workforce analytics is surely advocating the same here.
The overwhelming majority of research advocates a strong relationship. American Business Magazine writes “Research has shown employees who identified themselves as happy in their positions are productive 80 percent of the time at work. Comparatively, employees who identified themselves as unhappy were only productive 40 percent of the time.”
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Employee Engagement is the soul of HR and a human cultural aspect applied to business. Scoring it against short-term business productivity may severely limit its scope.
Estimating Employee Engagement
Maslow’s hierarchy of needs is an interesting starting point. Many of us are familiar with this through our business management courses. This time-tested theory of “human psychology” provides key insights for understanding human behavior in the workplace.
All the five aspects of the pyramid manifest in some form within the course of the professional career and specific needs of employees and their own workplace.
Interestingly these aspects could even manifest differently for star performers, senior level employees or specific personality types. Individuals might have different priorities, perceived status quo and rate the same aspects in the engagement survey differently. It’s useful to identify and study these subgroups.
The traditional approach has been to accumulate survey data on factors estimated to influence employee engagement levels and then calculate metrics/ ratios for evaluation of engagement health. Any hypothesis for improvement initiatives is based on variance (differing survey ratings) between different individuals and/or same individuals at different periods.
Key interest survey points have been traditionally centered around individual goals, personal space, work life balance, clarity of mandate, transparent assessments and judgments, channels of communication, compensation and benefits, career path, work recognition, etc.
The statistical significance of a process characteristic or component is evaluated on employee engagement (in this case) and measured for acceptable quality. Identification of specific, measurable critical to quality (CTQ) characteristics is essential for meaningful and measurable improvement in employee engagement.
This is the traditional flowchart to determine the CTQ for employee engagement:
Andrew Marritt writes about his work with Workometry “Perceptions change over time. As analysts we built a systems dynamics model for engagement and plugged our data in. It worked, our data pretty much validated the model. The great thing about systems dynamics models is that you can use them as simulators: make a change to the assumptions and the model will create predictions. We can therefore use it as a management simulator to understand what we need to change to improve what we care about – engagement.”
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The implementation on the technical side is complex. This can include different statistical techniques, like periodic paired T-Tests for observations over time, Principle Component Analysis or clustering for reducing the previously mentioned factors that make up engagement into a smaller numbers of principal components. In addition, no one size fits all. Re-engineering the HR policies based on the above findings should ideally be specific to identified groups and their behavioral patterns vis-à-vis organizational goals.
New Ideas & research pertaining to engagement in HR
An evolving idea is that the estimation of the implicit benefits like health improvement of employees, happiness index of employees, variances in grievances and legal cases, company brand value may not be necessarily correlated with short-term employee productivity and needs to be observed long-term.
A 2012 review of more than 200 studies found a connection between positive psychological attributes, such as happiness, optimism and life satisfaction, and a lowered risk of cardiovascular disease. – Psychological Bulletin, April 2012.
Josh Bersin adds to this, emphasizing that engagement programs help employees perform better in their daily jobs, improve their career planning and help them become happier and more engaged employees. Indeed, “Most major retailers, for example, now offer tuition reimbursement for hourly workers and early career management programs are becoming popular again.”
These aspects may also have implicit benefits in terms of reducing long-term attrition, improvement in referral programs, higher Glassdoor-ratings (company and HR brand value) and other long-term hidden benefits.
The diagram below shows the deploying Engagement Analytics over a period of time. From proof of concept till establishing analytics in an organization or culture.
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Let’s also explore a few advanced statistical techniques that can be periodically applied to employee engagement data. These are typically used by practitioners in organizational psychology for deep analysis and can be seamlessly adopted by HR. It is handy for HR to have a high-level overview.
HR Engagement Survey Data Challenges
So how do the HR Data Analysts/ Organizational Psychology Analyst keep themselves busy?
- Does HR have a hunch of many hidden subgroups of employees within the organization (different scoring patterns in the engagement survey)? – Discriminant Analysis
- HR needs to know the engagement survey factors that correlate with each other and with “employee productivity” or even a third explanatory factor – Deep insights required, like Factor analysis & Principal component analysis
- HR needs to check variance (variability) of identified factors in order to find its relevance or compare same surveys conducted at different times – ANOVA/MANOVA/T-Test/paired t-Test to the rescue
- Based on findings HR needs to progressively field-test new ideas in employee engagement and predict its impact – DOE (factorial Design of Experiments) & period review via ordinal logistic regression
- HR needs to tap deep insights into the employee mindset – open text descriptive answer-based questions and insights via deep Natural Language Processing (NLP). When done right, this can deliver a lot of value.
- Innovation – design creative ratios (an HR Statistical analyst can get really creative here!), metrics and employee engagement, gamification of the workplace
Summing up employee engagement
It’s critical to take a balanced, long-term approach to employee engagement and assess it from a holistic econometrics perspective and not from a perspective of short-term productivity alone.
The core idea of employee engagement analysis is to keep employees invested in the business both implicitly and explicitly. This also helps keep HR relevant and empowered within the organization itself.
It’s important to look out for over-complexity, emphasize on actionable intelligence and ease of implementation, and maintain proper and timely records.
The ethos and culture of the very origination is based is on the idea of engagement and it’s the primary responsibility of HR to be its guardian. This is precisely what engaged us to write this piece
Written by Raja Sengupta & Soumyasanto Sen
Soumyasanto Sen is a professionally Consultant/Manager/Advisor/Investor in HR Tech. He has 12+ years of experiences focusing on Strategies, Analytics, Cloud, UX, Security, Integration and Entrepreneurship in Digital HR Transformation.