Interview with Littal Shemer Haim, People Analytics Consultant

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Interview with Littal Shemer Haim, People Analytics Consultant

At UNLEASH Amsterdam I was lucky to run into Littal Shemer Haim, an independent people analytics consultant based in Israel. Littal has 25 years of experience doing analytics, starting long before the field was even called people analytics.

You can read the full transcript below the video. Alternatively, you can also turn on subtitles!

Erik: Littal, thanks so much for being here. I’m really excited to interview you.

Littal: Thank you, Erik. I’m glad to be here, too.

Erik: We tried this a few times, but we’re getting there! I specifically want to ask you about the future of HR, and some of the trends that you’ve been seeing over the past years. Because you have been in people analytics for over 25 years, which I think is really impressive. What I want to ask about-

Littal: It wasn’t called people analytics, you know?

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Erik: It, probably, wasn’t called people- it wasn’t even called HR analytics back then!
Over the last 25, or so, years, what are the biggest trends or changes that you’ve been seeing in the marketplace?

Littal: Yes. I think that the first big thing is that HR people started to look outside of their domain, started to explore more business questions and gain more impact with the analytics on business. And the second thing is impact more on our other stakeholders, which are the employees. So using analytics to make work better for people, which is the second trend I see.

Erik: We just saw Josh Bersin on the main stage talking about the employee experience, and the importance of involving the employees in the analytics process. How have you seen that develop?

Littal: So, basically, we are starting to use data, with AI, and other applications, to give personalized insights for people. We’re not only using analytics to give executive answers and insights but, also, the very personal individual in the workforce – which is a huge change.

Erik: Yeah. That’s fascinating. And I think that’s where analytics is going. I have a Samsung phone, and it counts my steps every single day. And that’s an analytics insight that’s useful for me, but it might also be, in a productivity setting, be a productivity measure, or depending on your job, of course, that’s useful information.

Littal: I think that the employees already are used to using their smartphone everywhere, for every activity, so now they expect the same experience at work.

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Erik: Yeah. They expect the same from their HR technology. What I really want to dive into is, I know you have a strong vision on the future of analytics, and a lot of people are saying AI analytics is the next thing. What’s happening after analytics? Will people analytics always will be there, always be the separate department, or where will we go in the future do you think?

Littal: Well, we are involved in our building dashboards, and doing predictive analytics, and all the shiny methodologies that we like to use. But the thing is that, all of this will change, eventually, because AI is getting into the HR domain and will actually replace these kinds of analytics. And I think that, we, the people, analytics leaders in the organization, have a new and very important role. Because since we know something about the mechanism behind those shiny apps, we will be the ones to choose the right applications for the organizations. And with the mindset of being ethical organizations, we need to have ethics guide us while doing procurement of AI applications.

Erik: So, recently, Amazon has been in the news because they had a faulty hiring algorithm, where it favored males over females for certain roles. What can companies do to prevent this from happening in the future?

Littal: Well, first of all, we must understand that garbage in, garbage out. If we teach our robots to learn from all data that enables all the discrimination, all biases, we should not be surprised-

Erik: Be surprised when robots are also starting to discriminate?

Littal: So we should ask our vendors hard questions about the kind of data they use to teach their machines to give insights on. And I think that we should think of new data, new kinds of data that can be used, like data about aspirations and behaviors that are related to career development. And, on the other side, opportunities that some kinds of new apps offer to employees to match their aspirations. So this is new data, without the old biases that we know from work.

Erik: So what you’re saying is that before we input the data and train our algorithms to be a certain way, we need to check the data for biases, see if we are an equal employer, for example, see if that also is represented in the data. And if that’s not represented in the data, we should be very careful training our algorithms on that biased data, in that sense.

Littal: I think that we should do that. And we can’t actually do that, so, I don’t see any HR leader actually do that. But we should ask our vendors, those suppliers of new AI applications for HR, those hard questions, to really make sure that the data they use is not biased.

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Erik: Yeah. Even if it’s our own data that they might use, and that might actually be biased.

Littal: So, basically, we have two new roles as people analytics leaders: one, is the procurement role; we want to find the best solutions out there, that are best for our business questions, for our organization, for our culture. And the other important role is the ethics issue. We are responsible for the ethics of all these robots. They are not ethical, they are just machines.

Erik: Yeah. They just do what we train them to do, or tell them to do. And we need to train them in the right things and show them the right example. And that’s a hard task. Littal, thank you very, very much!

Littal: Thank you so much.

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