Littal Shemer Haim

People Analytics, HR Data Strategy, Organizational Research – Consultant, Mentor, Speaker, Influencer

New Roles of HR Leader in The 4th Industrial Revolution

You can’t evaluate AI solutions without understanding the basics of practical machine learning and predictive analytics. You don’t have to be a data scientist for that. It’s like driving a car – you don’t need to be a mechanical engineer to buy or drive your car.
Photography by Littal Shemer Haim ©
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HR departments practice People Analytics to help business leaders to improve performance and growth through insights from people’s data. But what’s beyond People Analytics? How HR leaders should be prepared for the fourth industrial revolution?

 

AI changes everything. We have new responsibilities.

We’ve discussed a lot the two trends that contributed to the emerging of People Analytics a few years ago: data democratization – managers demand people data to run the business, and data consumerization – employees demand to use data for growth, wellbeing and positive experience at work, just as they do in other aspects of their lives.

But today, AI can make everybody better in many fields. Personally, I try to use AI to make myself more productive, e.g., I use speech to text and text to speech to cover content more quickly. Moreover, I collect data about myself in many aspects of my life.

However, I think I’m still one among the few who read privacy policies, and I take them into account when I choose apps. Data can make us heroes, but it might also destroy us if misused or abused. We leave data traces everywhere: when we drive our cars, watch TV, buy products, consume web content, or interact with people on social media. And of course, at work – we leave data traces with every breath we take – when we move across offices, write e-mails, manage calendars, learn, conduct our work, or even when we don’t show up to work.

Who owns these traces of data? The regulation defines it, in many parts of the world now, but it lags, in comparison to technology. It is our responsibility, not only as managers or consultants, but also as people, parents, and citizens, to understand the rapid changes and make informed decisions, not only by insights derived from data but mainly informed decisions about the usage of data-based apps, which basically are every app.

New learning path. New employer rating.

Privacy and ethics are not new in the organizational research field. For instance, we had discussions about the smallest group we can analyze in surveys more than two decades ago. However, we have so many new data sources of the workforce now, from sensors and smartphones and desktop apps. As I mentioned, people are not aware of the digital footprints they leave. This data might be turned against their interests.

I think it’s time for people to learn how to protect themselves, and this learning path should be also a new responsibility of organizations. We discuss Ethics in People Analytics and HR-tech, but we must keep in mind that this is a crucial topic in educating our employees too. To do so, learning leaders must already gain a thorough understanding of this domain. Unfortunately, this is not the case in many organizations.

Furthermore, there’s a lot of talking in the HR sector, about employee experience. I believe that soon enough employees will start exercising their rights in data privacy, and we’ll see employer rating based on data transparency, and data usage that is aligned with employee interests – growth and wellbeing, which is literally, what we mean when we talk about using employee data for good.

New skills. HR people are not there yet.

As AI sweep HR-tech and being introduced to many HR practices in every stage of the employee lifecycle, someone in the organization will have to pick the right solutions for the right needs. I forecast demand for two new skills in the HR role: Procurement and Ethics. However, if HR people keep procrastinating their up-skilling in analytics, the consequences might be that Procurement and Ethics roles will be filled by someone else in the organization.

You can’t evaluate AI solutions without understanding the basics of practical machine learning and predictive analytics. You don’t have to be a data scientist for that. It’s like driving a car – you don’t need to be a mechanical engineer to buy or drive your car, but you do need to know how to hold the wheel and to obey traffic rules, so you don’t kill anybody. Therefore, I call HR professionals to start their journey into the data world. And start it today.

Littal Shemer Haim

Littal Shemer Haim

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.

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