Two words sum up why the employee experience (EX) was the most talked-about topic in HR circles in 2018: HR data. Yes, after years of patient wishing and hoping, HR professionals finally have at their fingertips a depth of insight that’s almost taken for granted by other departments – and it’s all thanks to data.
Why has this explosion happened? The answer is likely all around you. Your organisation may have gone through, or be preparing to launch into, a digital transformation. Digital transformation is on the minds of executives from organisations big and small; they are faced with the same critical goal of evolving manual processes to suit a completely digital organisation across all functions, including HR.
Regardless of the scope of the transformation, the increasing use of technology means HR professionals are being given a valuable commodity in today’s data-obsessed world – that is, their own data that they can utilise to spot trends, identify risks, improve productivity and efficiency, and build an Employer of Choice-worthy EX.
Most organisations are already adept at using data – it’s a foundational part of doing business and has helped shape the customer experience for years. Now it’s time to apply similar rigour to HR data.
As outlined a whitepaper by our parent company, ELMO, the EX covers every touch point an employee will have with an employer, from hire to retire. It’s a mix of technology, purpose and the physical workplace itself, and it encapsulates what people encounter, observe or feel over the course of their journey at an organisation. It looks at more than engagement and culture and brings together all the workplace, HR, and management practices that impact people on the job. Little wonder HR teams globally are being rebranded as EX teams.
So where does data fit into this? Employee data – whether it’s obtained via engagement surveys, pulse surveys, employee Net Promoter Score® or other technology – makes personalisation possible. It enables HR to create bespoke experiences for every employee. This is an important consideration as a “one-size fits all” approach is the antithesis of a desirable EX. Instead of standardisation, HR should look at consistency – ensuring there are guidelines in place so that decisions are fair and transparent.
As the EX is formed and shaped through every part of the employee journey, from recruitment through to performance management and everything in between, there are countless touch points to potentially focus on. Below we look at 3 of the most data-intensive areas.
- Professional development
On-demand learning and the rise of eLearning means it’s now more cost-effective to personalise learning to suit individual learners. We’re only at the start of understanding what self-directed learning means, with terms like micro-credentials and social learning just taking root. However, fuelled by data, a new era of so-called “adaptive learning” technology allows courses, activities and test questions to be personalised to suit the learner’s preference and pace of learning.
Remarkably, adaptive learning adapts to both the confidence and the understanding of the learner. A standard learning path gives all learners a similar experience of the course, with the same screens and questions to be answered in the assessments. Usually it’s a step-by-step process up the knowledge chain, with step one needing to be completed in full before the learner can move on. Adaptive learning means all learners might start with the same content but depending on their responses to the questions, the platform will subsequently only feed them relevant content they need to master, instead of all the content.
Greater engagement and less boredom during professional development – surely that’s the dream of employers and employees?
2. Performance management
We’ve all heard of the drawbacks of traditional performance management: it’s too infrequent, it’s too time consuming, and it’s too marred by bias. Although traditional performance management has long been disparaged by managers, it’s fair to say employees suffered as well. The intention of data-driven performance management is to bring to the fore employee strengths and weaknesses in the most objective way by bypassing the biased opinions that managers, peers or direct reports might have. Through data analysis we can more easily identify what constitutes “high performance” and “poor performance”, whether that’s defined through KPIs or desired behaviours. This can help take some of the guesswork out of assigning arbitrary performance ratings to employees, and therefore make the link between performance, compensation and/or promotions clearer.
To make data-driven performance management work, consider doing more than annual reviews. Studies from the likes of Gallup (“Managers: Millennials want feedback, but won’t ask for it”) show that staff today expect more feedback. They want greater responsiveness and transparency (how their efforts feed into a bigger picture), and to feel that their opinions count. Regular employer/employee check-ins are the answer. Not only is more data collected and more timely feedback provided, but goals can be easily tracked and updated – keeping in mind that the SMART (specific, measurable, actionable, relevant, time-bound) and OKR (objectives and key results) goal setting approaches are the best ways to ensure performance data is obtained and acted upon.
Also remember that data can provide insights into broader issues – for example, if multiple staff members in the same team are having performance problems, can it be traced to a manager? Does it highlight that additional training is required?
For those using more sophisticated data mining techniques, it will be readily apparent that most HR departments are sitting on large piles of unanalysed, written performance reviews. With more advanced technology it’s possible to use an emerging field called Natural Language Processing – which takes Boolean text analysis and keyword searches to the next level – to analyse these reviews to create employee competency profiles or automatically generate performance scores for both employees and managers.
3. Recruitment and onboarding
It’s a blurry line between the candidate experience and the new employee experience – in fact some would say they are one and the same. Fortunately, there are ample opportunities to gather data during recruitment, and later again during onboarding. Information on qualifications, skills, experience level, aspirations, personality & behaviour, likes/dislikes, and so on can all be obtained during these stages.
Data from your existing workforce can be extremely useful in recruiting. It’s one thing to know that 30% of employees came from a particular job channel, but even more helpful is knowing the key competencies that are shared amongst previously successful employees – for example, resilience, the ability to take initiative or use creativity to resolve complex problems. Knowing these attributes enables you to widen your net when looking for fresh talent; you can look beyond typical “must-haves” such as previous experience or qualifications.
The onboarding experience for successful candidates should not be underestimated as a data source. Data obtained from pulse surveys during and after the onboarding process can help refine the experience for future employees.
Data also underpins any form of machine learning, and with artificial intelligence increasingly being utilised in HR, chatbots will soon be commonplace in the recruitment and onboarding process. These ‘bots can be used to personalise the candidate experience by answering simple (and increasingly complex!) questions, facilitating assessments, and scheduling interviews and training.
Disparate sources of data may eventually prove to be the most valuable for shaping and enhancing the EX. Although it’s still in its infancy, organisations that can “cross-pollinate” data sets – for example, HR data, sales data, commission data, customer satisfaction data – will find themselves ahead of the field in terms evaluating and leveraging the true value of a positive EX.
The race will also be on to employ those who can interpret this data. According to a whitepaper by IBM, Burning Glass and BHEF, titled “The Quant Crunch”, by 2020, the demand for data scientists will increase by 28% – and HR will be just one of the many disciplines seeking their services.
The ability to track and use data is easier said than done. Not only must the right technology be in place to capture the data, but you may also encounter data silos, sceptical stakeholders, a lack of the right skill sets, and countless other hurdles.
However, improving the EX is not necessarily about large-scale sweeping changes. Pick one area of HR’s mandate (onboarding, for example), obtain employee and manager feedback, adopt a design thinking mindset, change the existing process, trial a fresh approach, obtain feedback, and keep going. As the EX is fluid, continuous improvement is critical.
By embracing a data-driven approach, managers will be more effective at supporting teams, leaders will make more informed decisions, and employees will feel more empowered and engaged. The end result is a better EX for all.
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