Will People Analysts always be human?
Will People Analysts always be human?
We heard the words that every speaker emphasized in this conference: measures, KPIs, metrics, models, predictions, insights. And of course, People Analytics. These are important words. They are all related to our practices today. We have to measure, keep tracks of our KPIs, use advanced analytics to get business insights. We all do or intend to do, People Analytics.
But will our practices last, facing the rapid change in technology? How will our jobs as People Analysts will change in the future? Will People Analytics remain a job for humans? And if it will, what will we – humans do, when machines can do analytics much better than us?
I decided to be where questions are evoked
I’d like to present you my future professional self as a People Analyst. I’ll take you to a short journey into my future experience, in a fiction, yet realistic, organizational situation. Through my experience, my challenges, concerns and hopes, I’ll answer the question I raised.
I believe that this glance into the future is essential for us. It enables to prepare to the unknown, or at least try. As Dan Gilbert mentioned in his book “Stumbling Happiness”, the human being is the only animal that thinks about the future and has the ability to imagine events. Thinking about the future is useful because it evokes action. What actions should we take today in order to practice People Analytics in the future?
Our brain is an “anticipation machine”, so let’s use this function. But before I throw myself into the future, let me tell you a little bit about myself, in case this is our first encounter. I’m a consultant in the field of People Analytics for many years now. I started this journey more than 15 years ago, long before the terms “Data Science” or “Workforce Analytics” have emerged. I actually introduced myself, for years, as an Applied Researcher and an expert in Organizational Research.
My background education is interdisciplinary. It includes studies in the Technion – Israeli Institution for technology, where I graduated in Economics and Management studies, and where I gained my MBA. My studies encompassed a variety of courses in Mathematics, Statistics and Computer Programming. Looking back, it prepared me well for my current occupation.
But I was always attracted to the human factor. Naturally, I took complementary HR courses – as many as I could. Yet, it wasn’t enough, so eventually I graduated Psychology, and Positive Psychology, at the Tel Aviv University. Research methodology in Psychology is a great asset for questionnaires and other research tools’ design.
I see my whole career on a spectrum between People and Business, and the domain of People Analytics mediates between these two poles. Every transaction between people and organizations can be revealed through data. However, as much as data is thrilling, we know it is not enough.
The key to success in leveraging data to insights is asking the right business questions. It must come first, long before analyzing data sets, using sophisticated machine learning models or creating an amazing visualization. As a consultant, I understand now that only by being a part of the strategic hub in HR group, I can access business questions, and can really make a difference, supporting them with the right projects. I decided to be where questions are evoked, not where answers are requested. Therefore, I’m focused now, on exclusive long-term partnerships, and offer my expertise to selected companies, one at a time.
So, in a nutshell, this is my journey in the data-driven HR, but alongside my activities in organizations, I spend time sourcing and sensing HR tech, and it makes me wonder: How innovation will eventually broaden human skills and shape the future of work? Which brings me back to my questions: Will People Analytics remain a job for humans? How this profession will change?
My future professional self as a People Analyst
Significant questions, indeed. In the next minutes, I want to take us out of our comfort zone, by asking about our relevance in the future. How should we change our mindset to stay relevant?
Like many of my fellows People Analysts, I’m an eternal student. I study all the time. My daily reading, writing, and sharing are not exceptional in the open source culture of the People Analytics domain. Three years ago, when I achieved a certification in R programming, and in Predictive Workforce Analytics, I was pretty sure that I’m on the right professional track. I was wrong! I’m convinced today that in my future career I will not have to write a single line of code, and I will not produce even a single predictive model. Let me tell you why.
As I mentioned, I’m focused on business questions. Looking around, mostly on the web, I discovered that most business questions related to people in organizations can already be handled by machines! Technological solutions already enable analysts to combine different data sources that a company has on its people, to tackle business challenges.
The emerging HR-tech scene, which includes dozens of thousands of companies and start-ups, already understand the importance of data in knowing how to manage and engage people effectively. Some platforms consolidate real-time data and give decision-makers valuable insights into their employees, at a touch of a simple button. It looks like soon enough People Analytics can be done without us, without the involvement of actual analysts. Is this really the case?
Absolutely not! We will be needed more than ever. But in a new reality where we no longer needed for statistical modeling and hacking skills, we would have to find something else to offer.
First practical implication: Procurement
People Analysts have a lot to offer. We can keep using technology to amplify, not overtake, our influential role in organizations. We can do so, mainly due to our ability to change. The first important change in this profession belongs to the domain of Procurement.
If analytics is to be bought instead of being produced, someone in the organization will have to deeply understand the business questions and find the best technological solutions that suit each one of them. Someone will have to lead the organization in this puzzling industry, that encompass may be more than 20,000 innovative solutions, and which covers the entire employee lifecycle, from hire to retire. Who could do this better than a People Analyst who already understands how Machine Learning works and how model accuracy is tested? Someone who already knows how to map and access data, and how to communicate it with different stakeholders in the organization?
People Analysts must start to look outside of their data sets, and be open now to HR tech innovation, in order to be ready to lead the process of embracing it. We will point the way and direct the organization, but in order to do so, we have to fill the pulse.
Second practical implication: Ethics
The second important change is a responsibility for data ethics. Ethics in People analytics is to know what is good or bad and practice our role with moral obligation. There is a lot that we can do with data. However, it might not be what we should do.
The compliance with the GDPR and other regulatory issues being discussed these days is only a starting point. It will surely force awareness of People Analysts to privacy issues. But I think it will also influence employees’ behavior, and People Analysts will have to respond:
When people start exercising their rights and request access to their data, People Analysts will be ready in advance to give them comprehensive information about their data usage. When employees start asking to correct or erase their data, employers will request more transparency and security from HR software providers. Organizations will ensure that they process only the personal data that is necessary for the specific purpose they wish to accomplish, and therefore, they’ll need long-term planning and more serious considerations.
This will probably move the field of People Analytics forward. The implication for employees and candidates is Transparency! But not only… Eventually, since the People Analyst role will include more components of procurement and expertise in HR tech, we will learn, in the sake of regulations and ethics, to ask vendors hard questions and be more critique about model accuracy and data privacy.
Therefore, we’ll contribute not only to a culture of a data-driven organization but also to a safe work environment regarding employee data. Employees and candidates, for their part, will judge employers, in addition to Employee Experience perceptions, by employer ethics in data management, and when they feel secure, they’ll be more receptive and enthusiastic to participate and cooperate with AI to influence their career path.
Demonstrating the future reality
So far, I covered the two main changes in People Analytics: Procurement and Ethics. But how exactly this will be done? I decided to find out how such occupational change will actually occur, and naturally, I turned to the Israeli HR-Tech ecosystem.
The Israeli HR-Tech encompass about 80 companies. In a small country with about 8.5 million people, this means a proportion of one HR-Tech company or start-up per 106 thousand citizens. Quite impressive, don’t you think? Don’t worry, I’m not going to present every one of these companies here. But I do like to describe the research I’ve done on this ecosystem and show you how you can use it to prepare for the future.
I mapped the Israeli HR-tech ecosystem according to five major business challenges of an imaginary organization: Effective Recruitment & Mobility, Optimal Employee Experience, Enhanced Learning & Development, Building Great Teams, and Top Business Performance. For each domain, I tried to nominate the three best solutions, based on my own professional judgment. I started what I would call a procurement screening process, with each of the selected companies, using a questionnaire I designed for that purpose.
My criterions were not completely businesswise. I did not explore start-ups as an investor or as an actual buyer. Start-ups could be in a different stage of their developing roadmap, and that was OK since I only explored them as a sort of proof to my hypothesis. So, what did I ask them?
A procurement process that includes Ethical probing
First, I tried to understand their solution and differentiation, in terms of advantages for three different stakeholders: the business, HR management, and the People – both employees and candidates. Then, I took a closer look at data and business questions. I asked what can be done with data, beyond the product’s main purpose. Founders were asked to describe different aspects of analytics, planned or implemented, such as specific business questions, a user interface for analytics, APIs or other connectivity considerations, regulation, and success story related to data usage. I believe that this probing process will be part of my future daily routine.
You are probably curious about how startups founders reacted to my initiative. Well, most of them were not surprised at all with this theme, since they already considered themselves as a substitute for People Analytics practices, even if their solutions were not yet sufficient. For others, it was a beginning of an interesting discussion, since my research brought them to start thinking in a new direction. I think that my little research was a contribution not only for the purpose of this discussion about the future of People Analytics but also to some parts in this ecosystem too.
So what actually happened in the procurement process? I received a great cooperation. I looked for solutions in those five different business challenges and planned to find the best one for each question and present it in my lecture. To my surprise, during my research, I realize that a single technology can be the answer, directly or indirectly, to all the five questions I posed. This technology was bouncing again and again in every aspect of business questions, so eventually, I decided to concentrate on a single company. In terms of procurement, this means finding one, instead of several solutions, which may be easier and perhaps less expensive for the organization. Therefore, it can certainly be the first priority.
What company was it? What was the technology? How a single technology can address five different business issues? Well, StepAhead was the company, and it is based on Organization Network Analysis. This is an emerging trend in the field of People Analytics. However, this company has an innovative approach in this field too. In my lecture I explored their solution and value proposition, keeping in mind that my focus was the procurement process, and not a comprehensive review about Organization Network Analysis. However, I demonstrated exactly how the company addresses all my questions and what differentiation I actually discovered throughout my procurement process, and while probing the founders. This is a competency that I believe every People Analyst should have. To complete the procurement process, I also had to deal with the issue of Ethics. No matter what machine you implement into your processes, it won’t handle Ethics. Ethical probing is one of the soft skills, which People Analysts must practice. So I asked hard questions about privacy, employee benefits and barriers, and about the “Big Brother” concept.
Technology is exploding in our faces
If you had asked me two years ago how our profession has been evolving, I would have said that it did not change much for a decade or so. But in the past two years, technology changes have been so rapid. Digital Transformation is changing industries and organizations from within. In a sense, technology is exploding in our faces. We can barely imagine how the future of work will look like, let alone our own profession. So how could we possibly know today what should we do in order to keep up with our role and stay relevant?
As I found in my research, gaining two new competencies is the answer. Procurement processes on one hand, and responsibility to the ethical use of employee data, on the other hand, can lead to a data-driven solution to at least five business challenges. These two competencies are the necessary professional upgrade for People Analytics. They will keep our profession relevant in the future. We can’t stop, or even slow, the rate of change. But we can prepare for it, by changing our mindset.
The human brain is not only an anticipation machine, as I mentioned earlier, it is also a sophisticated learning machine. Neuroscience shows us that an integral part of being human is being wired to learn. Our answer to technology is to learn more of these two competencies – Procurement & Ethics.
Humanity is here to stay
But doing so, we will not only keep the People Analytics human. As positive psychology taught us, people are most happy and healthy when they express their full spectrum of abilities. They experience flow when their challenges correspond to their capabilities. They feel meaningful when they connect to something significant and bigger than themselves. All this goodness can be provided in the organization with future applications, enabling people not only to excel, but to express the full spectrum of their competencies, and thrive.
Is technology your comfort zone? No, for most of us. But let’s embrace this opportunity. If you choose to change your perspective, by these two new competencies – procurement and ethics, you will position yourself at the heart of the organization. We can take control of the machines, by ensuring to pick the right ones, for the right purposes and processes, and thus contribute to a better future of work.
To conclude, humanity is here to stay. As much as technology is evolving, our human role will not lag behind.
About the author:
Littal Shemer Haim brings Data Science into HR activities, to guide organizations to base decision-making about people on data. Her vast experience in applied research, keen usage of statistical modeling, constant exposure to new technologies, and genuine interest in people’s lives, all led her to focus nowadays on HR Data Strategy, People Analytics, and Organizational Research.