Episode 163: Boosting Managerial Efficiency: The CHRO's Outside-In Approach to Productivity (Interview with Paul Rubenstein)
In this episode of the Digital HR Leaders Podcast, host David Green engages in an enlightening conversation with Paul Rubenstein, the distinguished CHRO of Visier.
Throughout his illustrious career, Paul has been on a relentless quest to empower other HR leaders and professionals with the knowledge and tools they need to extract maximum value from their data; and in this episode, David and Paul dive deep into the transformative potential of HR data and analytics, shedding light on the key takeaways from Paul's extensive experience at Visier.
During this episode, you can anticipate exploring:
An in-depth exploration of the strategic importance of HR data and how it can reshape organisational decision-making, based on Paul's experience and expertise;
The symbiotic relationship between data-driven HR practices and fostering diversity, equity, inclusion, and belonging (DEIB) within organisations.
A visionary outlook on the future of people analytics and how organisations can proactively prepare for what lies ahead.
Concrete strategies and actionable insights for cultivating an organisation's data-driven and digitally literate HR culture.
Support from this podcast comes from Visier. You can learn more by visiting: Visier
If you would like to discover Visier’s groundbreaking research ‘Unlocking Manager Effectiveness: The Next Driver of Value clicking this link.
[0:00:00] David Green: If you are tuning into this episode or are a frequent follower of the podcast, chances are that you're on your journey towards creating a data-driven HR function, or you're already a data enthusiast looking to take your people analytics to new heights. Regardless of where you are on this path, today's conversation is one that is going to transform the way you think about HR data, as today I am joined by Paul Rubenstein, CHRO of Visier, the sponsor of this series of the Digital HR Leaders podcast.
Paul's passion for data-driven HR and his visionary insights have made him a prominent figure in the HR community, inspiring professionals worldwide to embrace data as a powerful tool for shaping the future of their organisations. From the synergies between HR and CFOs in data utilisation to overcoming the challenges faced by people analytics, today Paul and I will discuss how organisations can unlock the true potential of HR data to drive strategic decision-making and create a data-driven culture. We'll explore the critical role of data in transforming HR from a reactive support function to a proactive strategic partner within organisations. We'll dive into the practical aspects of implementing data-driven strategies within HR, and we'll venture into the realm of how cutting-edge technologies, such as generative AI, can empower HR leaders to extract deeper insights and drive unprecedented value for their organisations.
So without further ado, let's start the conversation with a brief introduction to Paul, his background and his unique role at Visier.
Today, I'm delighted to welcome Paul Rubinstein, CHRO at Visier, to the Digital HR Leaders podcast. It's an absolute pleasure to have you on the show. Can you share a little bit about your background and what your role at Visier entails?
[0:02:07] Paul Rubenstein: Sure. Well, I'm Paul, I'm the Head of HR at Visier, and I'm a first-time Head of HR, so I spent most of my career in consulting at two of the big human capital firms. And I'd say about half of my work was, remember the old HR transformation consultants that used to write those business cases and put in PeopleSoft and Workday and shared services and all that? I did that for about half my work. And then later, I was able to really do some interesting work on talent strategy, and I ran an assessment business and a leadership business. So, it's been a really, really interesting career, and being Head of HR at Visier is sort of a passion project and a whole new world for me.
[0:02:54] David Green: And you've been with Visier for a few years now, haven't you, Paul?
[0:02:57] Paul Rubenstein: Yeah, six years and change, I think, and what an adventure. It's one thing to evaluate technology and put in technology and help HR functions operate; it's another thing to (a) run the function, and (b) work within the technology that helps change the way we think about HR and human capital. It's just a completely different perspective.
[0:03:22] David Green: And I know, Paul, as part of your role at Visier, you spend a lot of time obviously meeting with customers, meeting with some of your peer CHROs in other organisations. I also know you've delivered a series of talks in the last couple of years on how to use HR data like a CFO. So, I suppose the obvious question is, why the CFO? I think I know part of the answer, but I'll let you explain. The second part of that is, what are CFOs doing with their data that HR could learn from?
[0:03:52] Paul Rubenstein: Yeah, it's interesting. All those years advising, it's one thing to advise; it's another thing to sit in the chair of the role you've been advising to. I guess I've always sort of been fascinated by talent strategy and the HR function, I really have been a student of it. It's interesting, do you ever scratch your head sometimes at the decisions people make around people where you're like, "Wow, I don't know if that was really aligned with the business", or, "I don't know if you really had a complete view of how you should have made that decision"? And to this day, I'm surprised at how many people decisions are made off of instinct or inertia or tradition, and then all those other things we talk about, bias, or I mean there are so many things that can influence a people decision alongside with data and facts, etc.
And, man, I remember advising heads of HR, we'd talk about diversity. And I think one of the hardest things about being a Head of HR is going in front of the board one day, and I'll use diversity because it's an easy example. I could use turnover, I could use almost anything, cost, and you always build a chart up and to the right, that you're going to improve; all charts must go up and to the right. You're going to improve engagement, you're going to improve diverse representation, you're going to improve retention. Anyway, I think watching heads of HR invest money and articulate strategies, yet come back a year later and they were like, "Hey, let's change our workforce composition", only to realise the actual decisions that show up in that chart are the collective sum of lots of decisions distributed across an organisation.
So, as much as you may have in the C-suite all the best intentions around things like diversity and engagement and turnover, it's lots of little decisions that are scattered. So, I used to watch -- again, those decisions around people, it almost felt like there was optionality or other things that would influence them. So, who's good at that? What job is good at unpacking business strategy into a set of documents, numbers from two statements, distributing it across the organisation, and then holding up a mirror to all the decisions 12 times a year or more or less, but always with an absolute, "I'm going to make a decision, and it is either going to be aligned to or departing from where we all want to go".
The CFO does this amazing job of taking business strategy, unpacking it into financial data, distributing it across the organisation, and creating this alignment mechanism and this mirror to help everyone hold up that moment, that they are about to make a decision, and really help people show how it shows up as the collective sum in an organisational outcome. How's that for a short answer?
[0:06:52] David Green: It's a good answer that it built up for, I think, which is important. And what are the things that the CFO actually does that the CHRO and other senior HR leaders could learn from? I think you distilled it down to four things, I think, didn't you?
[0:07:05] Paul Rubenstein: Yeah, and so, David, this will be my attempt at short-form answers, which I'm so desperately working on as part of my personal development! But I think there's four things that the CFO does that the CHRO can learn from: cadence, curation, context, and conversation. So, let me break those down for you. Again, it's cadence, curation, context, and conversation. So, what I mean by cadence; a rhythm. In HR, we often wait for people to ask us for data. The CFO publishes that data 12 times a year whether you want it or not, they're going to have a point of view around, and it creates a heartbeat. It creates a checkpoint for everybody to know that, "I made a set of decisions, they're showing up in this number, the next set of decisions and how it shows up in that number is up to me, right?"
I mean think about it, how many months or quarters can a leader go, departing from what the expected result is? They're either going to be a hero or a goat at the end of the month, end of the quarter. HR can do that same thing by, instead of waiting for data, for people to ask for data, pushing it out there. And by the way, it's okay; sometimes it's slow data, sometimes it's boring data. But the funny thing is, when you go out as a HR person, when you see something in your data, maybe it's a turnover spike, but the person you're trying to convince that it's a problem has never seen that data before, they're like, "I don't know, is this good or bad?" They don't know if it's signal or noise. So, that's why it's really important, just like you know that check engine light is there in your dashboard in your car, it's only meaningful when it goes on because you know it's always there and you know it's normal to be off. I realise I just dated myself. Are there even check engine lights built into cars nowadays?
[0:08:54] David Green: You're asking the wrong person about cars, I must admit!
[0:08:59] Paul Rubenstein: Same here. So, cadence is about a rhythm. And curation, I think, is the same thing. When the CFO puts together financial data and distributes it across the organisation, each FP&A person, they're not giving the same data to everybody, they're curating it because each business unit may have to focus on a different thing. Maybe it's productivity, maybe it's pricing, maybe it's market share, maybe it's, you know, whatever it might be, the data is curated to focus on a certain thing. So, when you throw out a turnover chart, in some parts of your organisation, turnover may be great; in some, it's actually desirable; in other parts, it doesn't matter, right? It's not core to the business. In other places, it may be incredibly critical that you have continuity of staff, right? Sameness does not always yield greatness when it comes to talent strategy. It's a portfolio, so it's really important to curate that content to get people to focus on what's most important to that segment's talent strategy. That's a really important concept.
I think the third thing is context. Context is king. I often see people analytics functions respond to a request with a chart or a graph or something. Man, I've got to tell you, you send that to one person, they send it to five other people. And the conversation that you may have had about what that graph or chart means, that gets lost, it's like a telephone game. The CFO, when they write the management discussion and analysis, it isn't just a chart or graph or a number, it's words, it's a narrative that gives it context, "Here's what's happening. Let me demonstrate it to you in numbers and here's what you should do about it, here are the ways to deal with it". And that becomes a lasting method of scaling context and scaling the talent strategy beyond the direct person you've talked to, because paper and graphs and charts and emails, they move.
Then the final thing is conversation, right? So: cadence, curation, context, conversation. The CFO talks about numbers like, "Let's start with the numbers", right, and there's something grounding about that. I mean, if you've ever seen like a head of HR staff meeting, it typically goes something like this. All the business partners from all the all the business units, they go first, "Oh, what's happening in your group? What's happening in your group?" Then, somebody from learning and development tells everyone what book to read this month. And comp says, "Hey, you're spending too much on these people", and HR ops, "We had the following complaints, etc". And then you get to analytics and they're like, "Oh, we're seeing these trends". No, start with the numbers. If everybody has a set of numbers about their different units that's sort of consistent, it helps balance a conversation to say, not what is most urgent, not what's most recent, not to what's top of mind, but as a rhythm, how are we progressing to a collective or individual set of goals?
The second thing it does is it normalises the use of data for the entire HR function. When the head of HR demonstrates those behaviours of being data-literate, of stressing numbers, of having them in his or her head at all times, that sets the floor, right? That sets the floor for the data-literacy and use in the function.
[0:12:33] David Green: Yeah, it's interesting you said that, Paul, because by the time this episode goes out, we will have published some research at Insight222, and we've looked into data literacy in HR, and what are the key things that drive it. And actually, number one is the HR, the CHRO and the HR leadership team modelling that data-driven approach themselves, because then other HR professionals will buy into it. Now, obviously there's other factors that you need, and I know we're going to talk about data-literacy a bit later in our discussion, but it's interesting that you've pinpointed that one as well.
[0:13:07] Paul Rubenstein: I wholeheartedly agree. We think about the jobs we want and we also think about influence, and we're often sent to the people we sound like. So, if you are a business leader as an HR leader and you are trying to talk to the Head of Sales, I don't know that the language of leadership and engagement or social science always works. Balancing that with the language of data and numbers, and profit and loss, and growth and margin and quota attainment, that's where it starts to come together. I think very often, part of the challenge is HR has its own secret language and you need a secret decoder ring in order to understand it unless you grew up in the guild. People outside of HR don't use our language every day. And it's important to bridge that gap, not blame those people.
[0:14:01] David Green: It's almost like data can be the common language that links different parts of the business together. And as you said, if you start the conversation around that, then you lead to hopefully solving certain challenges, maybe reinforcing something that's working well, because let's be honest, it's about understanding what works and why it works. So, yeah, really interesting.
When we talked a couple of weeks ago, again, you're talking to CHROs all the time, and you're seeing that people analytics is being a little bit squeezed at the moment. So, I'd love you to expand a little bit on that; and also, what do you think the main causes of people analytics being stuck a little bit maybe in some organisations at the moment, you know, what are they missing, perhaps?
[0:15:27] Paul Rubenstein: I mean, let's talk about this, David, because I think you're seeing it, too. I think we're all seeing it. I speak to a lot of people in the people analytics community and I'm a little bit worried. I see this plateau being reached. I think people analytics has come a long way. Jeez, how long we've been at this now, like deep in it; seven years, eight years, nine years, ten years?
[0:15:49] David Green: Yeah, at least.
[0:15:50] Paul Rubenstein: All right. And that makes us old in people analytics! I mean, I remember when there wasn't even a job called Head of People Analytics, remember that? This is relatively new. And so, great work has been done to understand how business impacts people. And I think it is incredibly powerful and meaningful in today's world. The way we look at engagement, the way we look at diversity, the way we look at burnout, the way we look at how business has taken a toll on people, right, and what we understand about sentiment, what we understand about how people exit, right, or what drives retention. Great, great strides have been made, but I see it's sort of hitting a wall.
We've worked a lot on how business impacts people in the pursuit of profit, growth, etc, the toll it's taken. And look, social justice movement, pandemic, all these things, mental health, we've had to understand this. But now we've reached this wall of productivity gap, right? There's a huge productivity gap and a labour shortage. And capital's expensive. Hiring people is more expensive than it ever has been, investing in everything is more expensive. People are searching for these more predictable returns, right? And human capability is the last indivisible element of corporate performance to truly be conquered. We've conquered finance, we've conquered supply chain. And all the work in understanding how business impacts people and human psychology and all great work done in industrial psychology has led us to this moment to better unlock individual and organisational potential. But it requires us to think about the data and the delivery of HR services differently.
People analytics is often constrained by HR's own silos and thinking and siloed data, right? You get the HRIS data, you get that learning data is governed by learning people, you get the comp data governed by comp data. And a lot of times, the people analytics group has had to wrestle all that data in combination. But the real insights around how people can impact business, the real paths and the use of the language around a margin, growth, etc, EPS, that lays in the combination of data outside HR with people data putting people at the centre of analytics in business. When you start to take HR data with finance data, which I think a lot of people do do, you can really get to some interesting stuff. You can understand the relative contribution of pay versus retention; that's something simple.
When you start to layer in the data around production, Salesforce, JIRA, whatever has healthcare outcome scores, there are all these different things that are of more interest to the business than HR, you then start to understand the relative impact of HR programmes and investments on people, on not just big number outcomes like margin, but like sales and quota attainment, or customer retention, right? You can draw the line backwards from, "How did I train someone? How did they spend their time?" all the way to, "Did it have a business impact, or did we even hire correctly?" It gets even more interesting when we stop thinking about the systems of HR and start thinking of the systems of work, and we bring in network data, so that we can hold a mirror up to how deep are our connections at a customer or within an organisation; how did we spend our time; who do we connect with?
I feel like I'm going on and on, but I think you get my point. Getting beyond HR data is a means to an end. The end is a business outcome, and you can't understand how people impact business if you don't have as much business data in that discussion as you have people data.
[0:20:13] David Green: No, it really makes sense. I mean, at a high level, it's what are the people factors that impact most on sales, revenue, profit, customer loyalty, all those types of things that we could come up with; then thinking about, "Okay, so what are the business outcomes we're actually trying to move here; what data do we need?" So, that's people data clearly, but that's also different data coming from the business, whether it's from finance, whether it's from operations or somewhere else, or maybe data sources that we haven't traditionally tapped into. That's the network data that you mentioned there.
[0:20:49] Paul Rubenstein: I want to just dig in on this for a second, right, because this requires us to love a problem that is outside of HR. And it's funny, at the DNA of HR, a lot of people invest for efficiency. A lot of people start people analytics functions and fund them because they're looking for an efficient way to do reporting, not necessarily what is the business outcome. And the psychology of this is huge to understand, right? Because investing and spending in one P&L, where the benefit is actually happening in another, that's hard for a lot of organisations to wrap their head around, because they often think about with their own P&L, it's headcount, power, whatever that dynamic is. But now you're falling in love with a problem that is outside of HR that is truly a business problem.
I want to tear through it one example and just get real specific with the systems. Think about that sales example. Think about Gong data, right, being able to listen to a call, understand who talked more or less, understand what keywords were used. Think about the training that happened in order to prepare somebody for that. Think about who they invited to that meeting, that sales meeting, and how that shows up in a network score was how deeply did they penetrate, did a salesperson penetrate an organisation, how broad was their constituency, how syndicated is that purchase going to be? And then work that all the way back to, I don't know, their pipeline.
So, if you think about that, the traditional way that HR approached it was at the end of the quarter, end of their year, let's look at someone's quota and let's give them a performance rating also, and all that retrospective look. Now you're switching it and you're getting in the headspace of a manager to help them not reconcile somebody's past performance, but see where they're headed in their performance and to see the behaviours and how they match it up against the best performing people, and give them insights in where to drive the car, not where the car wound up. That's a different sort of HR thinking.
[0:23:13] David Green: Yeah, and that leads quite nicely to the question I was going to ask, Paul. It's almost like what you're saying is, instead of metaphorically looking down, as maybe HR has done in the past, looking at the function and thinking, "What work are we going to do, etc, what analytics are we going to use to look at our work?" they need to be looking up and outside of the business, more of an outside-in approach. So, we've talked about that kind of bit, but what else do CHROs, and it is the CHRO really that needs to direct this work, yes, with their HR leadership team, hopefully with a head of people analytics on the HR leadership team, what do they need to be doing to get their people analytics back on track?
[0:23:52] Paul Rubenstein: I think there's a couple of things, right? First of all, there's behaviour and philosophy. Josh Bersin calls it, "Falling in love with the problem, not falling in love with the solution". I think HR has benefited greatly from all of the transformation that's gone on, right? The systems are in damn good shape, the data is good enough. Stop cleaning your data; the more you get it out there, the cleaner it will stay. Stop trying to find a zero noise or complaint HR function; it's good enough. This is the moment you've invested for, is to flip the switch and impact business problems. So, I think the Head of HR has to have that context.
The second one is this notion of outside-in thinking. Understand business outcomes and work backwards. That requires new thinking and new leadership from heads of HR on talent strategy. You know, it's funny, before I joined Visier, one of my favourite pieces of consulting work I did involved looking at talent strategies across a couple of really large companies. And, David, they all said, if I crossed off the names, you could barely tell the strategies apart. It was improve engagement, reduce turnover, they were these sort of big sweeping generalisations. They were not talent strategies that were granular and specific enough by critical role and or business unit and geography to hang all those distributed decisions off of. I will tell you, it's hard to write good talent strategy, but we really have to make good progress in that, because good talent strategy is that North Star for everyone's decisions.
People analytics is the ability for the CHRO to take talent strategy and collapse their distance to impact on all of those talent decisions and business outcomes, by turning that strategy into numbers and distributing it. I know I'm right back where we started this discussion, but the CHRO cannot look at people analytics like it's a technology thing. It's a strategy thing, it is the most core function in HR, it should be number one. If your Head of People Analytics isn't reporting directly to you, change that, if your Head of People Analytics isn't in the conversation with the CFO and you, change that. I mean, there are organisations, there are some people who are really out there, they're doing some really smart things with people analytics. They're looking at it like an FP&A function. The business partners are looking more like FP&A people, or mini CHROs of their own divisions, and numbers is what helps drive the rhythm and connection to the talent strategy, and also brings both clarity and accountability to all of those people decisions.
[0:27:00] David Green: That's really interesting what you're saying, Paul, because a lot of what you said really resonates with the research that we've done here at Insight222, and I know the research that you've done at Visier as well where, yes, if the people analytics leader is on the HR leadership team, it says something to the rest of HR that people analytics is important enough to be on the HR leadership team. It means that the CHRO is hopefully then modelling that behaviour and the HR leadership team are modelling that behaviour. It means that the people analytics leader is probably getting more time with the CFO and their team and the CEO even as well. And it's really interesting, we see that those companies that are doing what we've been talking about, tying people analytics work to business outcomes on a continuous basis, are those organisations where it's elevated.
[0:27:49] Paul Rubenstein: And I think we get to a point where people analytics isn't a function, it's pervasive, right? It is just the way HR does business, the same way it brings in the principles of industrial psychology and basic human behaviour and comp theory, all those different social sciences with data science. And it isn't a special thing. Look, Visier was created so that you didn't have to have teams of analysts that you went to to understand data. The whole point is, everybody should be able to use analytics, not some special team in some guarded closet somewhere. This is really important.
It also speaks to the challenges that HR has, overcoming some traditions that have been stratified by the pursuit of efficiency. HR has very much, you know, their data and systems and their approach to data and systems mirrors their org chart, which is a set of specialties built for scale. And my God, great things have been done in creating specialty functions in HR. It is amazing what has happened in the last 15 to 20 years to create these deep domains with proven methods and repeatable scalable methods. But the problems that HR needs to solve in human productivity are not a learning problem, an employee relations problem, a comp problem. They are not a singular problem, they are connected problems. And we see all the major consultancies, Burson, Deloitte, McKinsey, etc, talking about a next evolution in what the HR delivery model looks like.
I've heard everything from systemic HR to connected HR to exponential HR, there's lots of terms. Even Dave Ulrich, who helped us understand how, with the three-legged stool, to create these scales and efficiencies and globalise HR, talks about the same thing. It's a connected problem-forward HR that transcends the boundaries and org charts and specialties. I don't know what the answer is, but I do know it requires new thinking, new leadership and a set of data that transcends these internal borders of HR.
[0:30:19] David Green: Yeah, it's almost like data is the thing that links all those traditional silos together and, as you say, connects everything so you understand it at the level you need to understand it at.
Paul, I want to talk about a couple of things. Number one, we're going to talk a little bit about some of the legislation and the regulation that's coming in and why that's important for people analytics and HR professionals; then we're going to very much look at generative AI and also some of the things that you're doing at Visier around that as well. So, everything that we've talked about so far really highlights the need to the HR professionals -- we've talked a lot about upskilling and reskilling. HR professionals themselves also need to be upskilled and reskilled, and that goes right up to the HR leadership teams as well.
There's new regulations coming in. Obviously, the Securities and Exchange Commission, there's much more disclosure of human capital reporting now required for companies listed on that exchange. We're seeing, obviously, in Europe with the EU Corporate Sustainability Reporting Directive, which is a bit of a mouthful, so we'll just call it CSRD from now on, that also requires organisations to publicly report and disclose certain workforce data. We can see where this is moving, but it's not only HR functions and professionals that need to be upskilled, there's a growing importance for people managers as well, the people that actually use this data and hopefully use it to make decisions in the flow of work. I'd love to hear your thoughts on this and what you're seeing as someone that's been a consultant, that's now running HR within Visier, but also speaking to customers and your peers in those organisations every day.
[0:32:49] Paul Rubenstein: Let's take this in two directions. Can we talk about those frontline people leaders first? Frontline people leaders, man, that's where the rubber meets the road. At the end of the day, you may hate or love your company, you stay or go, all the data shows you stay or go, primarily because of your relationship with your frontline leader. You can have all the amazing engagement programmes, benefits, culture, etc; if you're a frontline leader and you have an amazing bond, it can outperform the corporate culture. If you have a crappy bond or you have a crappy leader, that person is going to leave. That last mile is critically important.
But what's funny is, I think that that group is incredibly underserved by HR. We talk about leadership investments and leadership dollars. Man, frontline people leadership raise the floor. We talk about employee self-service and manager self-service around transacting. Manager self-service has very much become one of those things that was pushing HR's administrative work on somebody else. They resent that stuff by the way, okay? Giving those frontline people leaders access to insights, patterns, predictions, propensity to exit data, giving them you know data, really trusting them like adults to understand how again their data -- they work every day with time data, production data, etc, and they have to beg for people data. Make it easy for those people to fly the plane. Make it easy for them, like Waze makes it easy for you to know where to stop for coffee, pick up dry cleaning on an optimal route to get to where you have to go. Do that same thing for people leaders, right? That's people leader data.
But when you talk about sustainability and when you talk about the audience of, I'm going to call it investors, let's look at an example because I think skills are amazing. I think skills, as a unit of data for connecting all the things we do across HR and outside of HR, is hugely important, because skills translate to work. And being able to have, what are the skills we have; how many of those skills are available in the market; how do those skills relate to the different priorities? Those are like looking at the underlying securities of a bond. Good investors don't just take the bond rating agencies' word for A, A+, B, B-, they analyse those underlying securities to understand how to see deeply into what the performance may be. I think boards, investors, etc, are going to look to skills data to understand the sustainability of the workforce and the ability to execute. And I think there's a lot of gold in that.
[0:35:52] David Green: I think you're right. And interestingly, skills data in particular is arguably the thing that links a lot of these traditional silos in HR together. If you're hiring for skills, you need to understand skills data to personalise learning, to think about career pathing, to maybe identify mentors within the organisation, but then you also need it from a workforce planning perspective, "Okay, this is the strategy we're trying to achieve, these are the skills we've got, this is the gap, how are we going to close that gap? Are we going to close that by buying in talent or maybe buying in companies? Are we going to build our own? Where are we going to build our own? Where are we going to buy our own? What about location strategy linked to skills in terms of availability of skills, or partners?" There's so many things that you can use that skills data for.
[0:36:40] Paul Rubenstein: So, you and I agree this is important, right? But I see a mistake getting made on this, right? People are doing these skills projects, or they're only looking at, "Oh, let's see what skills our candidates have", or they're doing these, "Oh, self-report your skills". This is the first place, Visier included, where AI is really making a difference. I remember doing these projects when you were a consultant where you'd do competency models or you'd read job descriptions, you'd hand-tag things, oh my God, right? Skills are changing. Skills, in what is both explicit and inferred and the language of it, it moves faster than you knew. And doing a skills project, as soon as you've done in the classic language of HR, it's out of date.
So Visier, for example, taking those jobs, looking at that data, inferring the skills, using AI to understand it, is so much faster, so much better to build that base level sort of a layer of what do you have, what do you need. It's amazing the advances. That's just one example of where AI is changing the ability to understand sets of data and keep it fresh. I think that's the second part.
[0:37:55] David Green: Yeah, you're right, because otherwise if you ask people what skills they've got, you'd probably be lucky to get a 50% adoption rate. How do you validate that? And as you said, it's out of date straightaway. And then, how do you connect it to stuff to close the gap and everything else? So, yeah, really interesting. And that leads on quite nicely, Paul, to the next question. Obviously, it wouldn't be a podcast in 2023 if we didn't mention the words, "generative AI", but it really does offer the potential, I think, to help bring some of these insights that we've got in this data to people leaders and HR professionals faster. But what do you think this means for the future of people analytics? Do you think it will help people analytics scale, get back on track in those organisations where it isn't; or do you think it will even replace it?
[0:38:44] Paul Rubenstein: You and I lived through the outsourcing craze. Did I just call it a craze? We lived through the first ERPs being implemented, right, "Oh, woe is me, everyone's going to lose their job". What it wound up doing is helping everybody's job uplevel. Our work continued to be more meaningful, and that's what will happen with AI. We will go through a temporary distortion where we can unpack jobs, take off parts of them, give it to AI and fill it up with more meaningful work. Yeah, there will be winners and losers, there are in every technology shift and revolution, right? But in the end, there's always been more winners than losers and we've benefited as a society and the productivity of our economy overall, so I look forward to that.
But okay, I'm going to just give you my favourite thing about AI. It's just asking a simple question, "Tell me what the trend is for turnover in this group". Okay, I don't care what you're using today as your toolset, Visier, Power BI, no matter what, that can be some work and iterative. People just want to ask questions and get the data very quickly, and that's what our first huge announcement in AI has been. We call it Vee, and it's very exciting, and so you'll hear more about it. Maybe you and I can look at it together in either Vegas, or you're not going to Vegas, or Paris, or somewhere fun, right?
[0:40:14] David Green: How does Vee work? And maybe give some examples of how Visier customers are going to be able to use it.
[0:40:20] Paul Rubenstein: So the beauty of Visier isn't -- what's hard about large language models? The data sets and the data about the data, understanding how the data relates to each other. That's where the people who build proprietary deep data sets that are normalised across multiple clients and can really reach deep, are going to get fast, insightful responses from generative AI. And so, that's the key right there. So, I think the first thing it disrupts is the delivery model; how we consume, especially outside of people analytics, our data. I think the second thing it does is it helps us reach deeper into patterns and up-level the high-value work we do in people analytics. And beyond that, man, sky's the limit. I'm just excited to see where it goes.
I was with our Head of Technology, and again, I'm not a I'm not a programmer, but we were looking at something and he was showing me what it would take to do some of what we can do with AI in writing long SQL statements, right? It was it was maddening to see how fast and accurate it gives responses that used to just take hours of layers and logic problems and nesting of arguments. It's just phenomenal.
[0:41:45] David Green: And I suppose if you're a people manager, you've got so many pressures on, if you ask a question, you actually want the answer almost immediately, don't you? Now, it's always going to be possible, of course, but with the generative AI that if your data is there and you ask the question the right way, then potentially you're going to get an answer that comes back. That might then prompt another question, of course, but that's the kind of speed of business, isn't it?
[0:42:13] Paul Rubenstein: Exactly, right? So think about the old speed of business partners and the current speed of people analytics. You have a question, I give you a set of answers. Appreciative inquiry is the art of getting to the root of a problem. A guy, Mark Sullivan at Lego, he taught me a long time ago, the point of people analytics is not to answer questions, it's to get people to ask better questions. Humans want to ask the next question, so AI is trained to learn. So, you ask one question, you didn't understand the answer, or you need to go deeper, it just gets better and better as you refine it. And that's how humans ask questions, and that's the speed, "Rather than going back and forth, run me another chart and graph, let's experiment", that's where we're going and it's going to be awesome.
[0:42:59] David Green: If you catch up with me in Paris, you can show me a Vee as well there, Paul. So, I think this then leads quite nicely to the final question, and this is a question we're asking everyone on this series. And I think the background that you've got as a consultant and now as a CHRO in a technology company, actually with people technology, people analytics technology, I'm getting really interested in the answer to this. How can HR leaders build a data-driven and digitally-literate culture in HR?
[0:43:31] Paul Rubenstein: Curiosity; model the behaviours you want to see in others, be fearless. I am not a technologist. You can probably hear that from my answers around AI.
[0:43:41] David Green: And nor am I!
[0:43:43] Paul Rubenstein: You have to be curious. And not just curious about data. You have to be curious about the moment when people see new information. Do they actually change their decision? Understanding that moment and how you harness it is what's going to create a great leader, regardless of whether they're in HR or not. And understanding that moment is noisy. We live in a noisy, noisy world, David. You know this, right? We're constantly pinged, tons of email, lots of data. Any leader who can harness that data with a narrative, connected to a North Star, bring it down to the moment of, am I going to make a choice? Make sure that data and insight is there at that moment of choice or at least present of mind, especially when it comes to people decisions.
In the next economy, the winners will understand their people, and they will understand their people, how they operate, how to motivate them, and how to use data to see better into those decisions. The losers will rely on instinct, inertia, and tradition, and they will hide their HR data behind the four walls of HR, and they will not connect it to anything else. Man, let's create more winners because it isn't just good for the company, it's good for individuals. The truth we see through data unlocks both individual and organisational potential. And remember, companies only grow when people grow. The sum of corporate growth is the sum of individual growth, and I think we have to get back to those basics.
[0:45:30] David Green: No, I think you're right. And I think actually, if we really realise the full potential of this, actually if we think about the organisation, yes, it will help the organisation grow, help people grow, but actually, back to what you were saying right at the start about diversity, equity, and inclusion data around burnout, wellbeing, all those sorts of things, we're actually improving society. We potentially can improve society as well.
[0:45:53] Paul Rubenstein: Absolutely. More meaningful work, more meaningful decisions, more truth about people. It will be fairer, it will be more just. Let's get to that world fast, man, because they need it.
[0:46:03] David Green: Thank you so much for being a guest on the Digital HR Leaders podcast. I always enjoy our conversations, they're always very thought-provoking. Can you let listeners know how they can find you on social media, if you do social media, and find out more about your work at Visier and maybe find out more about Vee as well?
[0:46:19] Paul Rubenstein: Just go to www.visier.com, and you can learn more. You can find me on LinkedIn, Paul Rubenstein 100. I am about to do a speaking tour for the rest of the year about outside-in thinking and how the CHRO unlocks the potential of talent in the new world. We'll cover talent strategy, we'll cover all those things. Yeah, David, just to bring it on, we have a big tent and a big community for anybody who's not part of people analytics. David and I are blessed to be part of a really interesting, growing and welcoming community. So if you're in people analytics, listen to these podcasts, what is it? Swipe up and subscribe. And then if you're not, learn more.
[0:47:04] David Green: Paul, thank you very much and looking forward to seeing you in Paris.