A few weeks ago, I was fortunate to be speaking in front of a room of high-level corporate executives and decision-makers, curious to find out more about the world of HR Analytics. Being a “People Analyst”, I saw an opportunity to gain some interesting data. Before introducing myself, and through a simple show of hands, I asked three questions, and the audience played along.
Question 1: “How long have you been with your current organisation?”
- 5 years or more? = c.50%
- 18 months – 5 years? = c.25%
- < 18 months? = c.25%
Question 2: “How many of you took the role, already with an idea of when you would be leaving?”
- = c.10% (very few hands!)
Question 3: “And, for that matter, whether you might subsequently look to return?”
- = 0%
I asked the audience to remind me of this exercise at the end.
Wouldn’t it be useful if an organisation were able to forecast this?
Even better, if they were able to predict it to a high degree of certainty?
And, of course, once we have the headlines, to be able to segment those analytics to pinpoint certain causal factors behind those expectations of attrition – such as identifying:
- an ineffective manager or toxic colleague;
- perhaps highlighting an outdated compensation strategy; or
- a lack of progression opportunity (or, perhaps, just a perception, thereof)?
During this article, I want to explore some examples of analytical activities being captured at various stages of the Employee Lifecycle – to show how leaders, managers and stewards of organisations can start to leverage commercial advantage through HR.
“People are our biggest asset”
I first started to hear this phrase more than 10 years ago, when I worked at IBM; I dare say IBM wasn’t the first, but I’ve since heard it recycled by many organisations.
Privately, though, many leaders will be worried that this represents a significant risk to their organisation: how do they know if their people are truly an asset, and not a liability?
After all, the nature of work is changing – rapidly – and so too, therefore, will the nature of the workers, themselves; shaped by both technology and economics.
From those stretched, dual-income families finding ‘life hacks’ through mobile apps, to the “The Future of Work” and the “Gig Economy”, organisations are needing to understand their people now, more than ever.
Broadly speaking, all of this can be summarised by “economic changes in working patterns giving more flexibility to organisations and individuals concerning working relationships, commitments and productivity, driven by technological advancement and entrepreneurial spirit.”
For an organisation’s workforce, these two factors are linked by Autonomy: people are starting to take control of their lives and using technology to do it.
HR analytics can help to understand and predict these shifts; affording the insights needed to engage with the workforce more effectively, just in time.
Accepting that most organisations are not (yet) filled with staff wanting to work for themselves, we should consider the relationship between the organisation and the individual.
Such changes will not occur, definitively, overnight, but most people will gradually start to crave more autonomy and control – spurred by experiences both within the workplace, as well as socially.
Consider, then, how this might affect the long-term commitments of the employer-employee contract. It’s this concept of what happens to the individual during the span of the employer-employee contract which is referred to as the employee lifecycle.
Broadly, there are 5 phases to the employee lifecycle:
The Employee Lifecycle Teardrop (M. T. Lawrence, 2015)
- Recruitment (from attraction of the right candidates, through to onboarding processes)
- Development (of core skills; via training and knowledge assimilation)
- Utility (of advanced skills and further competency development, to enhance productivity)
- Progression (engagement, organisational contribution and realisation of experience)
- Exit (disengagement, or leaving current role for another reason, such as promotion)
“Culture eats strategy for breakfast”
Bernard Marr, the performance expert and commentator, suggests that “Google arguably knows more about us than our loved ones, knowledge it uses to provide a highly personalised service”.
Imagine what it can do for its own people. To this end, Laszlo Bock, former Snr VP of People Operations at Google, offers up a wealth of information and analysis in his book, Work Rules!, identifying the importance of building the right culture for the organisation to attract the right talent.
But how do you measure culture?
Numbers of people wearing T-shirts to the office? Analysis of corporate mission statements? Numbers of people logging into an “All-hands” conference call?
Caring leads to engagement, engagement leads to productivity, according to Bock, who stated that 86% of Google’s salesforce agreed, strongly, that they could “see a clear link between Google’s objectives and my job.” (91% for the rest of the organisation, 2013).
How many of you know this for your organisation?
Transparency and clarity of purpose
Bock’s commitment to the use of data is mouth-wateringly refreshing for HR:
“If you believe people are good, you must be unafraid to share information with them”.
I have been talking about the need to act in ‘data partnerships’ with all areas of the business for many years.
Sharing data needs to be the default position, so that restricting information requires effort.
This often shocks my clients, who are used to protecting person-level data with every fibre of their being; but so long as the appropriate controls are in place, organisations can enable collaboration, which boosts productivity.
And, crucially, collaboration can be measured – through knowledge-sharing activities, from which an organisation can look for correlations with performance…
“A century of science points the way to an answer”
Sentiments and platitudes are important in driving an evidence-based culture; but what really counts are results.
Bock describes how Google were able to optimise, identify and mitigate biases from their recruitment process, for example.
In experiments involving observers from the general public, Google were able to establish that the first 10 seconds of an interview can be predictive of the outcome: establishing a healthy rapport, it seems, is important where structure is lacking.
Seeking to mitigate this ‘halo effect’, therefore, firms may choose to employ:
- Work sample tests = a 29% predictor of success
- Tests of general cognitive ability (e.g GPA) = 26% predictor
- Structured (standardised, competency-based) interviews = 26% predictor
However, when combining these more rigorous assessment approaches, Google were able to reduce their famously difficult and chaotic recruitment process from between 90-180 days, to approximately 47 days and an average of four interviews.
This increased their level of confidence to 86% as a predictor of good performance. Aside from the implied benefits of a more engaged, aligned workforce, this also meant that interviewing managers spent less time away from their ‘day jobs’, trying to plug gaps.
Ensuring data was at the heart of the process, Google were able to analyse performance of their interviewers (understanding, as they did, that most weren’t seasoned, well-trained, well-practiced interviewers) and were able to show a clear correlation between experience and performance.
This is the start of the employee journey; imagine if we apply the same rigour to the rest of it…
All of this is fascinating for those interested in recruitment; but if we return to the employee lifecycle, for a moment, we can see that all this insight really only goes to serve the very start of the employer-employee relationship.
If we have analytics at this level, it stands to reason that we ought to be able to generate similar insights for the remainder of the journey. One of the reasons Bock focuses on recruitment, however, is that it’s a relatively data-rich environment: not only do we have specific systems, but it’s often the source of service-level agreements between different organisations.
Outside of the recruitment process, the CIPD, in conjunction with experts such as Max Blumberg, Sam Hill, Eugene Burke and Andrew Marritt, has sought to raise awareness of people analytics amongst its wide membership. On CIPD training courses, personality profiling techniques benefit from analytical rigour to increase performance, for example.
Importantly, though, the CIPD emphasises the need to therefore adjust recruitment processes to attract and select candidates with more “winning characteristics”.
Importantly, segmentation of results, to optimise funding and investment decisions is another feature. You need to ensure that training initiatives are prioritised only for those that will experience the biggest benefit;or that resources are appropriately aligned.
Recruitment is a formative process: one which sets the context for the rest of the employee lifecycle.
If we hire the right person, or the wrong person, there will be long-term implications for the organisation and for the individual – whether the employee will truly engage with the mission of the employer, whether they will be satisfied with work, motivated to be productive and to develop in line with organisational objectives…
During my time at IBM I worked closely with the Workforce Analytics team, involved in a number of projects which showed how IBM sought to link these processes together, for deeper insights and to offer the individual greater opportunity.
It’s important to stress that it’s this healthy employer-employee relationship which is at the heart of good business; and that people analytics is not a tool for organisations to exploit the individual.
Social analytics sought to provide insights into the collaborative nature of IBMers and gain real-time feedback from its people.
Furthermore, analysing five years of historical data, including known flight risk factors, they sought to identify which of their staff had the highest propensity to leave; and then target those high-value employees with interventions to attempt to retain their expertise. (Of course, I then left, so there’s obviously room for improvement…!).
However, what this did was to provide a level of insight to inform decision-making and time to reduce negative knee-jerk reactions.
Just as data is beginning to underpin so much of what is understood about an organisational workforce, so learning and development is crucial to growing, empowering and progressing those people performing the company’s work – allowing individuals greater autonomy of decision-making and driving productivity and engagement.
Value-adding activities were optimised, freeing up resources for other activities more closely aligned to organisational objectives.
Within the space of nine months, this group was working with data from learning systems, HR systems, operations systems, finance systems, delivery systems and others to generate unprecedented levels of knowledge about the ways in which its people learned most effectively and presented dynamic recommendations.
HR cannot work in isolation.
In order to gain influence at the Executive level, breadth and depth of data is critical.
.In a meeting two days ago, I heard an anecdote of a Chief Counsel who took a sideways step into an HRD position and immediately felt her voice was no longer heard at the Board level – she put this down to a lack of credible or relevant data.
So, what are you going to do, now…?
Having discussed the employee lifecycle, and returning to the questions posed at the beginning, you may be wondering what I did with access to such unique insights…
After all, these were important individuals in their firms – if I were to have emailed them all a survey, the day before, how many responses would I have got?
Well, I haven’t prepared any kind of analysis: I have no suggestions or recommendations, and I can’t help you make any decisions, either. Having gone to all the trouble to ask the questions, gather the data, in a setting that is conducive to a high volume of responses, it seems a shame not to do anything with it, wouldn’t you say?
In an earlier address at the same event, Hugh Cox (Co-founder and “Chief Data Whisperer” at Rosslyn Data Technologies) stole my thunder: he estimated that only 0.5% of all data is analysed.
The same is true of your people analytics activities: all of this will only be of any value if you use the information to achieve something valuable.
When managed properly, your people represent a massive asset – so make sure you’re not wasting your time: align with strategic objectives, plan ahead for anticipated outcomes and link processes and data together for best impact.
References:
Bock, L., ‘Work Rules!’ (2015)
Cox, H., verbal address (2017)
Deloitte, ‘Disruption ahead, Deloitte’s point of view on IBM Watson’ (2015)
Marr, B., ‘Beyond The Big Data Buzz: How Data Is Disrupting Every Industry In The World’ (2017)
