Today, our guests, we have two guests on. We have Max Blumberg and we also have James Holdstock who are going to be talking to us about HR and people analytics. This episode is called Work Minus Only Trusting People Analytics. Hi, guys. How are you today?
I’m very well thanks very much for having us on the show, Neil. Max here.
Hi, Neil. James here. I’m good. Thank you.
It’s a very interesting topic we’re going to jump into. But I want to start by letting both of you introduce yourselves and tell us a little bit about how you got into this topic. So, Max, why don’t you start us off?
Thanks, Neil. I’m Max Blumberg. I’m originally a tech entrepreneur. So, I started out with the components distribution company which eventually IPOed. And that was in South Africa and then I came to the U.K. I did a PhD in psychology and a large corporate company called Rentokil, who are pretty global, came to me and said, “Max, you’re a psychologist. You understand statistics. We’re having some issues with our sales force. Can you help us sort this out?” And I’d never heard of anything like that but I said, “Sure. I’m happy just to try and use normal academic methods.” I did a project with them and we made $70 million in the first year for our people analytics project and that was back in 2011. So, it was pioneering early days and after that I was hooked and I just carried on doing it. And I’m now a professor at Leeds University Business School, a research affiliate at Goldsmiths, University of London. And really enjoy working in the field.
Great. And James, what about you?
Hi. So, I’m James. I’m always interested to hear what kind of route people have taken through to people analytics because this seems lots of different ones but a few streams whether it be psychology or workforce planning or that kind of thing. I myself would say I’ve risen from the ranks so I didn’t go down a charted route or a statistical route. But I went into the ground in recruitment and then in HR administration and working all around the HR arena before getting into reporting mainly because I had a little bit of technical know how but then also had the whole landscape of knowledge about the HR area. And so, I also then worked a little bit in finance to do group reporting for the whole company. This was London transport which I spent a lot of my time and it was a great to get a whole overview of the company but I really did miss the mystery and the investigation that goes along with people analytics. And so, I got back into the HR reporting team which we then stepped up to a people analytics team as many people I’m sure are doing and trying to do with their own HR reporting teams. And then I looked outside for some other people analytics opportunities and have been taking on contracts and moving around some companies.
Great. We’re talking about an article you guys wrote in HRZone and looking at the idea of people analytics and why maybe sometimes we take it too far away or where to trust it. But I want to start off asking, for those in the audience who aren’t familiar with the idea of people analytics, what does the common man need to know to get a start with this? Max, why don’t you start us off with that?
So, Neil, we use data in finance. We’re quite used to making predictions. We look at what’s happening, what are the bank rates doing at the moment, how big is the economy, and we build models to predict what the outcomes are going to be. And I guess we do that in marketing, segment markets to produce a product and then you try and work out who are the likely buyers, how likely are they to buy it, etc. But we haven’t really done that until the last few years with people. So, when we look at people to say how likely is this person going to be a good performer in the job or how long are they likely to stay with us and we’d typically be making those decisions based on gut feel. Now, we aren’t saying that gut feel is a bad thing. I happen to think it’s a really good thing. But there’s no harm in supplementing your gut feel with some hard data to say, well, what are most people who have that personality, what are they like? Are they likely to be high performers in this kind of job? Etc. So, people analytics is really just using data to support decisions you make. Should I recruit this person? Or what training should we give them? How should we do them in succession planning? And so on.
James, when you tell your friends what you’re into or your relatives, how do you explain people analytics to them?
Well, I generally try and keep them awake. But I, too, love talking about it. I get quite passionate about it. I generally explain that it’s using data and technology for the benefit of the employees and the business. That’s the short version really and I completely agree obviously with all the things that Max said as well. That people are starting to really drill into customer insight, for instance, being a standard team now and all they’re doing is trying to predict people’s behavior using the data from those people and our employees are people as well. One thing that I think to add on to that is quite important in terms of the common person really needing to know about the people analytics is that it’s in their benefit and trying to give them an idea of what we’re doing and what comes out of it because I firmly believe that a big issue in the success in people analytics is trust. We want them to know we’re not doing weird, creepy stuff and that it genuinely is in their interests so that they actually allow us to use their data.
Let’s jump into the article that we’re talking about. You start off with a really interesting idea that the way we look at employee data and people analytics is actually pretty similar to how we look at livestock and inmate systems in prison systems. So, how did all of this come together? What’s the issue with all this?
Well, I guess it started, Neil, when I saw Tracy Smith wrote from North Carolina, as it happens, wrote in on Linkedin once saying what is the point of doing these attrition studies that’s predicting whether employees are going to leave when you’re not going to do anything about it? But the word that she used that really kind of freaked me out, she said what’s the point of analyzing flight risks? Now, I’m a bit naive, and even though I’ve been in this business for such a long time, I’ve never heard the term flight risk and James said to me, “Max, it’s a really common term.” And I thought, “Wow, isn’t that a word that we use with prisoners who might be escaping and inmates?” And they said, “Yeah. But we don’t think of it like that.” And I said, “But language is so important for determining how we behave and if you use a term like flight risk, all we’re thinking of our employees as inmates.” And then I started looking at technology being used for animals and I thought, “Wow.” They’re starting to track productivity of animals and productivity of human beings in people analytics. And the algorithms and the techniques that they use are really similar. And that’s when I came to the conclusion that unless we are prepared to put human beings on the same… treat them the same as animals, and I’m very pro animals, by the way, or think of our employees as being inmates, it just felt like we’re doing something wrong if that is our attitude. So, there’s nothing wrong with people analytics but I think there’s something wrong if we see our employees like animals or inmates.
So, in a way, do you feel like it’s a dehumanizing thing to apply these analytics in this way? Do you feel that way, James?
I think one of the reasons I was quite excited that Max got into this conversation and then called me to talk about it was that I don’t like taking things for granted. And so, I like challenging them, playing devil’s advocate. So, the question is is it dehumanizing and is there a problem with that? And so, I think we were able to, between us, debate quite a few of these things and then go away, do some more research. I think my personal view, which probably comes out through the article, is that it is a problem and that we need to be looking with the people analytics to be quite rigorous and adhere to a bit of an ethical code.
The reason I called James, because James says I called him to discuss it, one of the key reasons for me calling James, other than he’s an exceptionally bright people analytics professional, is that he’s also quite close to being a millennial which is the opposite of me. I’m a baby boomer. And I wanted to see what James’ attitude was and what drives that is that I was in a conference once and a guy from Jawbone was on the stage and he said they were giving employees these watches and measuring how many hours they slept and I said, “What has that got to do with an employer?” And he said, “Well, if you’re an airline, you want to know that your pilots are getting enough sleep.” I said, “Yeah. Okay. But most of the people in the audience are not pilots. Surely they’re going to want to have some private life that the company doesn’t own their whole existence.” And we did a quick hands up in the audience, how many people are happy to have all their data measured, and I was shocked when most of the audience said they were absolutely cool with having their company measure everything about them. And they were all millennials. And I don’t know. You said, “Well, Max, don’t feel bad. My grandfather would have felt the same as you.” But anyway. And that also shocked me. So, I wanted to find out from James, was this conference audience representative? Do young people really not care about their data just being used and being dehumanized, to use your term, Neil. That really got me going.
James, do you feel like it’s more of people are okay with it, they feel like there’s going to be some benefit to it or do we just assume that they’re going to have it anyway so why fight it?
It’s hard to say really because I guess, of course, the ideal scenario is to take a couple of groups and give them different scenarios and then see what the outcomes are and compare them against each other. But I guess we don’t necessarily have the opportunity so it’s hard to say even if you can see that the results of talking to people and using their data is actually a positive one it’s hard to say where it’s come from or why the difference potentially in different groups of people.
We’re talking about this. It all comes down to productivity. How can we make employees more efficient, more productive in these things. Why do you guys feel that this just focusing on people analytics is not necessarily the right path without conjunction with lots of other things added to it?
I think that people analytics is political, whether you like it or not. The idea of we live in a capitalist, on this side of the world, and we live in a capitalist society, in a capitalist economy, and so a lot of it is about making the shareholders wealthy or not, but nothing against that whatsoever. But I don’t like one group getting rich at the expense of another. So, I feel that shareholders and employees should get rich together. But that’s not what I’m seeing happening. I’m seeing these systems going to squeeze the last pound of flesh, as Shakespeare said, out of employees without them getting much more reward for that extra pound of flesh, whereas the investors get all the benefit, the additional profit from all of the productivity. And that’s where I think people analytics needs to be very careful in its political stance and its objectives that it consciously, as James likes to say, that it consciously looks at employee benefits as well as investor benefits.
Yeah. To think about the idea of being able to everyone to benefit from the idea of people analytics, what’s the next step in that, James? How do employees benefit from these numbers and this data just as much as investors and top management?
That’s quite big question. I think I’d give the classic people analytics answer of it depends on the scenario really. I do certainly have a belief and this is where I guess I stray from my belief that I should only make statements that are backed up by reams of data and fact. I genuinely have a belief that both of those parties can… that employees and shareholders or business owners can both win. Maybe it’s naive. I don’t know but I feel it that if the employees are happier, more content, feel safer, they can be more creative, innovative, and will work harder and be more valuable, which means that everyone in theory should win as long as the business owners are I guess working with the employees because there could be a scenario where the business owners create this wonderful environment, the employees work really hard, but the business owners don’t share that benefit with the employees. So, I guess if I wanted to put a word on that, I’d have to call it that there should be more transparency, which a lot of people don’t like.
So, what does that mean? We’re talking to somebody who’s a department head or a large team leader and they’re new on the job or they just started using some people analytics software and they get this big reports and it has all sorts of data about everyone, how do they use that data in an ethical way that treats people as humans and also increases productivity?
From my side, I think it’s about gaining more employee trust by involving them and engaging them in your projects, to say, “Folks, this is what we want to do. We want to improve your productivity for the betterment of society so there’s a CSR agenda. We want to improve it for the investors so that they get a good dividend that the share price rises. But we also want to improve it for you by handing back reward.” And it doesn’t have to be money all the time. It can be flexible working, working in a nice place, working under good conditions, having opportunities for you to have some free days, like Google do where you offer employees the opportunity to do innovative work. It’s rewarding the employees proportionately to what the investors are being done. So, the advice I would give to department heads is don’t rely on people analytics to tell you how to behave towards your employees. Develop a relationship with your employees and let that be the thing that improves the productivity and stops them from leaving the company. James has quite a good story about this idea of tracking employees actually makes them want to leave the company when you start doing attrition analytics. James, I think you had something like that?
Yeah. It’s a text that that we came up with together I guess that is in the article which is about it’s all about trust really, and if you are tracking these people, but you’re not being transparent with them and you’re not being open with them, then how are they going to feel about that? And as soon as someone doesn’t feel as though they can trust you, I would say probably they’re going to close up and maybe even start looking for other opportunities where they might feel safer and more trusted. So, it could well lead to people actually leaving, ironically, from just tracking the information.
So, should you make these reports open where everyone can see them? Should you make sure to tell employees that this is being tracked, this is what we are tracking, if you want to see your scores you can fill out this form? What’s the best practice there?
The best example I can think of to answer that question about transparency with everything and there’s a guy at Rentokil who’s one of the finest managers I know. He happens to be the MD for Europe, but instead of relying on technology to find out what’s going on in his teams, he has each of the country heads give him a rag indicator for all of their key employees, so red and green as to whether that employee is going to leave. And if an employee leaves and the country manager didn’t know about it, that country manager has to answer why they didn’t know. So, what he’s doing is saying let’s rather replace technology with relationships. So, I’m not saying get rid of technology but I’m saying why don’t we invest more in nice managers, managers that are able to have great relationships rather than having technology do the dirty work and do it very badly for us. And there’s a lot of evidence of this going on. We see a lot of companies now are trying to get rid of levels of managers using automation and to try and replace these managers with soulless, emotion-free machines and I don’t think that’s going to be great for the employees in terms of they’re not going to want to work hard. They’re obviously going to want to leave an environment like that. So, I think department heads, to answer the question, need to be investing more in relationships with employees supplemented by technology but the manager is still making the decision, not the technology.
And what about you, James? Do you feel like if a manager is going to use technology, should all that data be open so that everyone has access to it?
That’s a tricky question. I don’t necessarily think that all data should be open. I think there should be transparency about what data is being looked at, what’s available, and then also why it’s being looked at because explaining to people why you’re doing something can often help in dispel fear, especially if they have no idea why you’re using it in the first place. I would move rather than looking at the actual possibility of likelihood that someone will leave, even if that’s quite well informed by talking to them, I think one needs to move further back in the process to actually use the information that physically does exist about their past and about the movements they’ve had maybe within the organization or in their work history and then the information that is available to the line manager anyway and the line manager can really use this in conversation with the employees to help them and to help develop them and help find out what they want to do because if they want to leave in a couple of years, then if you help them leave in a couple of years, then they’re probably going to be a lot more productive during that two years but they would have left anyway.
You also have the idea, James, of cascaded goals. I didn’t really answer your question very well on transparency, Neil, but if the goals of the organization are cascaded down so you have the company objective and it’s cascaded to everybody in the team and then everybody can see everybody else’s KPIs and who’s reaching them or not, I think that kind of transparency is absolutely essential. Sure, low performers are not going to feel good, but on the other hand, it will motivate people far more. I know a company that had a really simple system is that in the contacts list, you had your name and your extension number, etc., and you also had your KPIs and how they linked to your manager and to the people below you and you could see how well you were doing on them. And that works fantastically. I can’t say who the company is but they’re a fortune 500 and it works really well.
Interesting. Well, let’s close out with this question. We say, okay, maybe we don’t want to push too hard and lean too hard into the technology side of people analytics, but what’s a good question or a good insider, a good data point that technology has taught us that we can then take back into those very human relationships, things line managers and department heads can ask their employees? What are some of those questions that we can learn from technology to ask in that person to person relationship?
Well, from my side, I think one of the key questions that I think technology has highlighted but he is not used very much in the relationship is for managers to understand what is the unique value that each member of the team can bring and I don’t know whether many managers know that. You can use analytics to find that out but it would be much simpler for a manager to sit down. In fact, I’ve recommended even to companies like Facebook that at recruitment time, one of the questions you ask employees is what value do you intend to add to this organization and to measure employees against that if the manager agrees with them. So, yeah, I think that’s one area where just it makes employees feel valuable when a manager says what is the value you’re going to bring in and helps to nurture that employee once they know what the chosen value of that employee is.
And what about you, James? What’s a thing you’ve learned from technology we should apply to our relationships?
I think something that we can take which I’ll say it because I don’t think it’s necessarily in common usage and it links to the one of the things that Max has said already is that most of us have performance reviews and we often capture information and nowadays there’s so much of that information, the objectives and performance against objectives that’s actually captured in technology in some kind of system. But going back to what Max said about people knowing what the objectives of the organization are and how their objectives are actually fitting into those objectives I think is incredibly powerful because you’ve got a way of employees straight away feeling very valued for the work that they do, understanding how the work that they do contributes so that actually they’ll probably end up being innovative in coming up with potentially a better way of doing the thing that they do. And it also means that they recognize their own value and so when performance objectives are being set, they can actually be coming up with them rather than them necessarily always being fed down from above. So, I think that’s possibly a large dataset that using a bit more of slick technology is quite underused at the moment.
Well, guys, it’s been a really interesting topic. I’ve loved learning about this idea. We’ll put a link to the article in the show notes so people can see that. How else should people connect with you, stay in touch with what you’re doing?
They can find me on Linkedin quite easily. I’m Max Blumberg and delighted if anybody wants to have a check, get in touch, get some advice about career or people analytics, etc.
Absolutely. Me too. Linkedin‘s probably the best way of reaching me. I don’t think there are many James Holdstocks generally, let alone on Linkedin, but I’ll be the people analytics one and I love growing my network and talking to people.
Well, thanks a lot, guys. It’s been a great topic and we appreciate you coming on the show.
A great pleasure. Thanks very much indeed, Neil.
Thanks very much, Neil.