Five key areas to apply innovative people analyticsby
By embracing more innovative people analytics to impact the full employee lifecycle, HR and the wider business will see more meanginful change.
You don't hire for skills, you hire for attitude. You can always teach skills.
Attitudes can predispose us to a particular set of behaviours or influence the decisions we make. The point Herb Kelleher, a US billionaire airline bussinessman, was making in the quote above is that without the right attitude, employees cannot or will not deliver their full potential. I would argue that this goes beyond an employee's ability to learn or to perform well, and touches every aspect of their working life.
It is vital that we understand what makes our employees happier, more confident, productive and loyal. To meet the demands of the future, people analytics has to cover every aspect of an employee’s lifecycle.
Yet compared with other disciplines within the business, people analytics still has plenty of room for improvement.
A data platform for people analytics tends to be insular – focused on data about employees, their performance or the progress of specific processes.
Most of the people analytics packages currently available seem to rely on operational reporting, with some basic diagnostic capabilities; and a few use these insights to support workforce planning and resourcing. Few also seem to offer any significant capabilities to understand what is driving HR measures, and almost none offer the ability to support managers in making nuanced decisions.
The use of people analytics among HR professionals must evolve to better meet the demands of both the business and the people within it. But how?
Here are five key areas in which innovative people analytics can be applied to help improve the full employee lifecycle.
1. Talent acquisition
Pundits talk about 'the war for talent' and 'the shortage of labour' and about the changing expectations of employees. In addition, organisations and employees are also having to cope with the changing face of work – with more emphasis on soft skills, as well as creativity, problem-solving and adaptability.
Whilst experience and qualifications are obviously important, these are beginning to contribute less to an employee's long-term contribution. Job descriptions (and resumes) need to change to reflect this, which makes the recruiters job harder. We've gotten so used to thinking about the quantifiable attributes of a candidate we're overlooking their behavioural potential.
Analytics can help by giving insights into what makes an 'ideal' employee or, better yet, an ideal team. Once we know what these characteristics are, how they are exhibited, and where they are likely to be found, we can start to improve the quality, not just quantity of applications.
Leading organisations start the onboarding process before the candidate's first day. Automation can play a valuable role in orchestrating the lead up to joining, but it needs to be smart, responsive and able to tailor the joining experience to the needs of each employee.
It can accelerate the journey to productivity by enhancing initial training, such as providing opportunities to rehearse duties with smart, interactive training that is tailored to the individual's needs. It can also get them to the resources and support they’ll need more quickly.
Similarly, analytics can identify where the onboarding process may need attention – addressing unmet needs or challenges by evaluating feedback from new joiners and their actual performance during initial deployment.
The objective here is to offer a tailored onboarding process that can deliver just what each new hire needs. For some, that will mean an accelerated process, for others a slightly more intensive programme.
Tools do exist to surface both what employees truly value, and why.
For training, analytics can match the capability requirements of the organisation, as well as the learning needs of individual employees. Used in combination with a learning management system, it can also identify when attention is needed.
Increasingly a greater emphasis is placed on humans engaging in creative knowledge-working with 'micro-learning' or knowledge management systems supporting on-the-job performance.
With new Predictive Behavioural Analysis tools available, soft skills, emotional intelligence and underlying attitudes can also be evaluated and addressed.
For those who commission training, there’s the ability to link training effectiveness to business outcomes. We need not rely on course evaluation forms or anecdotal reports to understand whether the learning opportunities on offer are meeting needs.
4. Engagement and motivation
Some of the tools for talent acquisition and training do embed analytics but are primarily focused on automating a process. This is for scenarios where there is significant scope for standardised, modular steps, and where analytics can provide the insights supporting orchestration.
However, for many organisations there remains a significant challenge – maintaining employee motivation and engagement, which contributes to productivity and outcomes. The problem being that there is no such thing as a 'standard employee'.
Late in the 1950's Frederick Herzberg published his ‘two-factor theory of job satisfaction’. In it, Herzberg states that there are independent causes of satisfaction and dissatisfaction, and that one is not the opposite of the other. Some of the factors that contribute to job satisfaction being emotional.
Until now, we've tried to measure these using formal research techniques. Unfortunately, we know that these provide limited insight into what employees really think and feel. As I am fond of saying; 'if you want to know how somebody is feeling, don't ask them how they are feeling'.
If you want to understand why employees do what they do, you need to listen to their authentic voice.
However, tools do exist to surface both what employees truly value, and why. Add that to operational data available elsewhere, and information about the employees themselves, and we can develop real insights into what is driving employee engagement.
It's usually a combination of rational factors (pay, hours, family commitments, etc.), emotional ones (stress, lack of advancement, cultural dissonance and so on), internal biases and external influences, as well as prior experience and what's going on right now.
Convert individual employee experiences into an ongoing journey and you have not only a good predictor of engagement and productivity, but also of when an employee might be considering leaving.
Why do organisations lose some of their most talented and valuable people, especially when offering industry-leading pay and benefits? There's an oft-quoted phrase "people don't leave bad companies; they leave bad managers!" but it is neither fair or accurate to wholly blame managers for staff attrition.
There may be several causes of job dissatisfaction, as well as other factors that might prompt an employee to leave. For example, in one organisation I have worked with, the birth of a second child is known to correlate to an uptick in resignations – but why? If you know the ‘why’ early enough, you may be able to take a proactive step to pre-empt and avoid that unplanned departure.
A more holistic view of business needs, alongside team and individual capabilities, can also give you insights into where you are strong and where further investment in people is needed.
The future of people analytics
More organisations are adopting people analytics, but the analytical tools they are using need to offer more than reporting of metrics or basic diagnostics.
If you want to understand why employees do what they do, you need to listen to their authentic voice, through which attitudes, beliefs and emotions are expressed. Because these are the very things that drive behaviours and outcomes.
Done well, advanced people analytics can enhance recruitment, streamline the onboarding experience, optimise training and development, enhance employee engagement and motivation, and reduce staff attrition.
Done badly, it can hamper diversity, focus on measures not outcomes, erode trust, and fuel a dysfunctional culture or poorly performing teams.
Peter is the inventor of Predictive Behavioural Analytics and a thought leader in Customer and Employee Experience Management. Peter has spent many years as an expert in the field of analytics related to customer and employee experience and is also a renowned speaker on the topic of CX/EX and the experience economy.