People Analytics is not merely a function or a role within the HR department. It is a mindset that each HR professional should have and leverage to impact both the business and the people. This analytical mindset, which becomes more common within HR teams, essentially changes the entire sector. I was honored to participate today in HRweek, where I met three respected colleagues in a panel conversation about how People Analytics transform the HR function.
The panel facilitator, Maja Ninkovic, Global Head of People Operations, Mitto, raised four main topics: The most significant successes and the remaining challenge of People Analytics; Leveraging analytics to orient business leaders in the pandemic and beyond; The barriers in deploying People Analytics capabilities; And what most exciting in the future of HR. I was happy to share and listen to diverse perspectives in the panel, which surely represents the evolving conversation in our field. Here are the main ideas that I contributed to the discussion, followed by some key takeaways from my colleagues’ presentation: Erik Van Vulpen, Founder of AIHR Academy, who talked about main skills for the future of HR, and María Jesús Belizón Cebada, Assistant Professor of HRM, UCD Michael Smurfit Graduate Business School who talked about the maturity model of People Analytics and tips to create added value.
The most significant successes and the remaining challenge
“People Analytics as a discipline has come a long way from 10 years ago. To what extent has it been successful in changing the way HR operates? What are the biggest successes, and what are some remaining challenges?”
People Analytics is a long journey. I think that all kinds of significant success and challenges in People Analytics are bound. Let me give you some examples. First, think about the deployments of the People Analytics tool. Most organizations succeed when starting to use an HR dashboard. They easily create and use the common new language based on standard metrics, and when needed, HR professionals upskill themselves as BI tool users. However, a significant impact occurs when you integrate data from different sources, both from HR systems and the business, and when you use advanced analytics with a lens into future outcomes. Although analytics skills have become more common among HR departments, Machine Learning is still challenging for most HR professionals. This knowledge gap is a serious issue when considering the available tools in the market.
Secondly, work is continuously changing. People Analytics platforms enable to analyze and visualize new concepts, e.g., the network structure of organizations. However, in many places, like in my country, it is still difficult to handle people in different occupational methods. Gig workers, contractors, and freelancers are part of teams and contribute to the business. However, in many cases, they are listed in procurement departments, separately from the workforce. And so, their measures of productivity or experience are excluded.
Third, there are organizational challenges, or if you like, social challenges, in which the use of People Analytics practices contribute to awareness, but the change or resolution is still far. Take, for instance, Diversity and Inclusion. For a few years now, this topic was one of the main themes in People Analytics, and yet the gaps exist. Even when implementing AI solutions, and the awareness of bias is growing, we can’t say that bias is eliminated.
Leverage analytics in the pandemic and beyond
“The global pandemic has fundamentally transformed the way people work. What are some of the ways HR professionals can leverage analytics to help their business leaders orient themselves in the new landscape?”
Let me answer this question without reviewing the entire tech solution categories that assist in the collaboration and employee experience. When I consider the HR data strategy solely, I don’t think the pandemic changed it. Just as before, we have business questions at the top, actionable insights at the bottom, and in the middle, we have a funnel consist of data from people processes, sources, storages, analysis, and outputs. The processes remained, as remote work is not a new concept. Even hot topics in pandemic times, like burnout, life balance, mental health, etc., are not new to the field of organizational research. And yet, the doze of topics we analyze changed. Mainly, think of these four questions that we asked before, but now they get much more attention: How do employees feel, What do employees need, How productive are we, And how connected are we.
Let’s take productivity, and explore further. It was always challenging to associate HR activities and productivity of business units, and mostly related knowledge workers. But in Covid19 times, when measuring remote workers’ productivity became crucial, people analysts could leverage the attention and integrate such data into HR data for valuable insights. It enabled executives to use talent data to capture ROI from people processes and well-being solutions.
However, organizations were still interest in measuring the facet of time. The implementation of tracking apps increased during the pandemic. HR leaders should have focused the discussion on some of the consequences of these new tools. Beyond privacy and the blurred boundaries between work and non-work, surveillance technologies that monitor work from home might be the wrong solution because it signals distrust and reduces intrinsic motivation to perform well. As research reveals, the potential reactions to surveillance solutions may undermine the goal of increased productivity.
The barriers in deploying People Analytics capabilities
“What is the single biggest barrier when it comes to developing and deploying People Analytics capabilities within the organization or HR function? Any advice that you can share on how to best address it?”
I hear accusations that HR professionals are not analytical enough. I even read articles that blame HR for the slow growth of People Analytics practices in organizations. I do perceive HR as responsible for their upskilling in this area, but their current state is more complicated.
Academic programs of HR still neglect People Analytics as a mandatory domain. I think that all programs should cover practical machine learning, and specifically, the differences between inferential statistics and machine learning. When they graduate, HR practitioners are placed in roles in which analytical expectations are not high, and so seeds of skills and interest might decline over time. The entire HR sector relies on consultants and contractors, but unfortunately, many of them are also not updated, and their interest in changing the state of affairs is unclear. Tech vendors sometimes prefer to bypass HR, which also makes HR lag. In many cases, HR is under-budgeted. It is most prominent when it comes to professional development. Relying on marketing content sponsored by technology vendors is insufficient for upskilling and reskilling.
Obviously, private learning programs do a great job in helping HR professionals closing their skill gap in analytics. However, I truly believe that HR people can overcome their analytics barriers when they exercise with real data, their own organizational data. But it doesn’t mean that HR people should become data scientists. They should become great clients of data scientists.
What’s most exciting in the future of HR
“Beyond just People Analytics, HRweek today is dedicated to Innovative HR and forward-thinking HR professionals. What is most exciting when it comes to the future of HR? What are some new skills, perspectives, or tools that will ‘future-proof’ HR professionals and HR function?”
I remember one of the first job interviews I had in my twenties. The interviewer asked me what makes a great manager. I described someone who can handle both the organization’s interest and the people’s interest. The people analytics domain conversation evolved in the last couple of years, moving from focusing on one stakeholder to another. It started focusing on HR processes, proceeded to business questions and c-suite level, and then shifted toward employees, teams, and finally team leaders. I follow HR-tech and people analytics and find it fascinating that a single button press enables us to handle so many stakeholders in a way I could not even imagine thirty years ago when I started my career. But to do it right, I mean, to choose the right tech tools that fit all stakeholders in the organization, HR leaders need two new skills: Procurement and AI Ethics. I believe these skills are crucial for future proof of a career in HR.
More key takeaways from my colleagues in the panel
People Analytics is a part of a broad spectrum of HR upskilling. As Erik Van Vulpen nicely articulated, there are three main skills for the future of HR: First, Business Acumen, which includes positioning HR policies and activities in a way that will serve the organization and deliver sources of competitive advantage. It is also including skills such as interpreting the context of work, understanding customer expectations, and co-creating the HR strategy. Secondly, data-driven skills, namely, turn data into information, metrics and KPIs, and the language of the business. The third is being digital savvy, who understands and leverages technology.
In a deeper glance into People Analytics practices, María Jesús Belizón Cebada offered a broad maturity model, which includes six measures: adoption, sponsorship, technology, capabilities, data points, and HR metrics. In many organizations, it takes 2-3 years to reach a maturity level across all these measures. In order to create added value with HR analytics, she offered some tips: start small, nurture the six dimensions of maturity, use data relevant to the organization’s competitive advantage, build inner organizational sponsorships and get the business on board.