Mark has performed a variety of analytical and project leadership roles, across corporate HR and L&D functions, primarily within the domain of management consultancy – starting work with PwC nearly 20 years ago, later moving to IBM. Subsequently, Mark completed a project at Marks and Spencer and has worked as an Associate Consultant for several organizations.
As an independent consultant, he helped to establish a new Analytical consultancy, produced a new People Analytics business qualification in partnership with a leading analytics consultancy, co-led the creation of a new Taxonomy and Benchmark for HR, and conducted research into the impact of technology and artificial intelligence on the Future of Work.
Mark is a founding member of the CIPD’s HR Analytics Advisory Group, has an MBA from Leeds University Business School and has contributed to numerous professional research bodies, including writing articles for several organizations and has been published in the Human Resource Management Journal.
What are the key aspects of employee performance that are critical to the success of HR Analytics?
I might interpret this question in several ways, but perhaps we should consider the performance of People Analysts themselves…
There are some obvious capabilities for a high-performing analytical function, which may not be a surprise to your readers; such as numeracy and an ability to work with technology. However, a project can still fail unless certain other aspects are present. For me, the elements which push an analytical function from good to great, revolve around 3 C’s:
1. Curiosity – a dogged determination to understand ‘why’… Of all the analysts and leaders I’ve worked with over the years, I’d say it’s this trait which links the higher performers, regardless of grade or seniority. It was my friend (and colleague at IBM), Jonathan Sidhu, that first made me reflect on this when he recounted a memorable story about dismantling a door-knob at the age of 3! I remember thinking “Wow – this sounds like how I relate why I do what I do when people ask me what a former (aspiring) archaeologist gets out of analyzing people data: I dig deeper and deeper, looking for those hidden themes and messages.”
2. Consistency – It’s become a cliché to talk about HR lacking credibility and a seat at the table. As the years have gone on, more and more leaders are recognizing the crucial role which People functions have to play in enabling a strategic agenda. Analytics is a key part of the driving force, here, providing credible evidence to help inform decisions, which were hitherto beyond the reach of reasonable insight. However, it’s important to bring an element of predictability: since Analytics is still relatively unknown quantity among many decision-makers, there needs to exist some expectation of high-quality outputs. Delivering a mixed experience is likely to present a hindrance towards most projects, as HR struggle to shake off the reputation of being unable to work with sensitive datasets from other parts of the organization.
3. Communication – There are many reasons why communication is a crucial part of any engagement, but primarily:
a. to consult strongly with stakeholders, to ensure that business issues are properly understood before work begins;
b. to ensure that the right resources are engaged at the right time;
c. that findings and recommendations are presented effectively, in a manner which is accepted, digested and endorsed; and finally
d. to collaborate on action-planning and change management processes.
How can HR Analytics enhance employee performance?
Analytical functions should work in partnership with Performance Management processes to add a level of systems thinking, to make sense of this complex area. In order to identify the drivers of performance, People Analysts can make sense of multiple channels of data to isolate those factors which drive high (and low) performance amongst the workforce or specific segments of interest.
Talent leaders might use such insights to drive towards a culture in which the workforce can thrive – this might include adjustment of Recruitment processes, such as attracting talent from new or under-utilized channels; or perhaps selecting candidates based upon rejuvenated criteria which more closely match the cultural aspiration. Learning and knowledge management processes might be optimized for a different user experience. Progression, Recognition, and Remuneration may each be considered differently, rewarding individuals for newly understood performance drivers.
What do CEOs/CHROs look for in employee performance analytics?
Responsiveness – and this may also be part of the barrier towards deep insight! I am very fortunate to have some very supportive senior stakeholders at GSK, but I have seen other examples where promising projects have been cut short before they could truly realize their full potential – all because of the pressure to produce insights too quickly and act on those insights before they can be properly verified and validated.
Managing the progress of an analytical project requires a mix of managing stakeholders’ expectations, whilst providing a regular drip-feed of insights. Very few leaders would tolerate a project that disrupts an organization then disappears for 2 years with the promise of a big reveal at the end of it! (Besides which, who would want the pressure of delivering on that promise?!) So, as I mentioned earlier, communication is so important to ensure that progress is known and understood.
Increasingly, this may require an appreciation of digital channels – for example, we might employ social business tools to make transparent some of the things we are learning about our people, providing a virtuous circle of interest and demand.
What is missing in terms of employee performance data that could make HR Analytics even more meaningful?
A cookie-cutter formula!
Even if there were some magic Performance Formula, Michael Porter would argue that organizational uniqueness would present a risk to successfully mimicking that in a different organization. To truly understand the levers which need to be pulled to obtain optimum performance, there needs to be a foundational approach to building up a framework.
One organization I have supported in the past, Rosslyn Data Technologies, understands this need, very well;pulling together Analytics professionals from several other multinational organizations to create a framework for analyzing Productivity (due to being unveiled at the CIPD’s HR Analytics conference, later this month). Whilst I haven’t contributed as much as I’d like to have done, I’d consider that the model ought to provide several comparable touch-points, which organizations might customize; but to underlay these inputs with statistical models that determine degrees of interdependence and enable a hybrid of best-practice / best-fit. It may not provide a truly accurate answer, but there’d be plenty of food for thought and further investigation! I can’t wait to see how it looks…
Can HR Analytics play a prescriptive role in helping employees fine-tune performance, real-time?
One idea might be to give the workforce access to their performance data via a platform which allows users to adjust certain performance-based variables to explore different outcomes based upon known circumstances. If I were to need to stay home for a delivery, how might that impact my performance? If I were to choose one project over another, might that influence my performance? If I wanted to understand the revenue I am bringing into an organization, could I perhaps compare this against organizational norms?
However, it’s important to understand some of the key elements of Analytical work (by which I don’t mean to refer only to ‘Analytics’, in isolation) and to draw some distinctions: between concepts like ‘Analytics’, ‘Reporting’ and ‘AI’. To my mind, Analytics provides the basis for a rigorous approach to research and investigation; whilst Reporting is usually concerned with providing an ongoing monitoring, or ad hoc description, of a business process or situation; and AI (Artificial Intelligence) is a generic term for some of the techniques applied to an analytical problem.
Considering these concepts in harmony:
- Analytics is the process of determining the correct elements to leverage and helps to define the solution;
- Real-time analysis may power the engine which makes the solution possible; and
- Reporting, through the self-service provision of data visualization and narrative, may provide the user experience
- Finally, AI (or more specifically, ML – machine learning) might provide the ability to continually learn from these patterns to prescribe certain optimal behaviors or events, to help an individual truly maximize their potential!
Imagine having the support of a tool, which recognized certain conditions you may not even recognize yourself, and sent you a message with suggestions as to suggested actions and next steps to help you progress a project, for example…