On the show today, I am talking to Ian Cook, VP of People Analytics Solutions at Visier. He’s a man with a real passion for the people side of business and the subtle arts of bringing the right people together for optimum results. Throughout our discussion Ian shares insights, and plenty of case studies, on how best to approach data and real-life humans in separate but complementary ways.

In this episode, we discuss:

• The dramatic rise in people analytics over the past few years

• What it means to be in a phase of mass adoption

• The shift in what business leaders expect from HR when it comes to people analytics

• How to get employees onboard with your data-driven ambitions

• How to help HR business partners become more data literate

• The concept of “turnover contagion”

Support for this podcast comes from Visier. You can learn more by visiting https://www.visier.com/ 


You can listen to this week’s episode below, or by using your podcast app of choice, just click the corresponding image to get access via the podcast website here.

Interview Transcript

David Green: Today, I am delighted to welcome Ian Cook, VP of People Analytics Solutions for Visier, to the Digital HR Leaders podcast.  Ian, it's great to have you on the show.  We've known each other for quite a few years now, but please firstly, can you provide listeners with a brief introduction to you and your work?

Ian Cook: Yeah, for sure.  So, I simply describe myself as somebody who's very passionate about the people side of business.  Through early stages in my career, recognising when you can formulate a group of people with a purpose, with commitment, with a connection to each other, you can really make amazing things happen.  I've always been fascinated by that question.

As a career, that took me through consulting for several years, based in the UK working with a bunch of blue-chip companies.  For the last 15 years, I've been putting the data behind that behavioural view.  I ran into what I describe as a CFO problem, where we had some really amazing programmes we wanted to do; we know that they would help the business.  We couldn't get them funded; we couldn't get an understanding in the business of what this work would do.  As the son of an engineer, my response to that was, "Let's go find the data", and so the last 15 years, I have been engaged in building, selling, educating, explaining data products that help people make better decisions about people.

David Green: For the last six, seven or eight years, we've been bumping into each other at conferences, and it's been great to see your journey and Visier's journey over that time, so welcome to the show, Ian.  There's been a dramatic rise in the interest in people analytics over the last two to three years, and I think especially since the start of the pandemic.  I'd love to get your overview of the people analytics landscape today.  What's your view on the current state of the field?

Ian Cook: A personal story: when I talked to an HR leader who will remain nameless, he was like, "I'm not sure why you're doing this people analytics thing, Ian, it seems like it's a bit of a fad".  Roll forward, it is no longer a fad.  Where we would see the state of the market, I prefer to talk about the state of the practice, we are at the mass adoption phase, literally lots of organisations that kicked the can down the road, focusing on getting their data in order first, have recognised that actually the use of the data is imperative.

So, the growth we're experiencing, the growth that others in our space are experiencing, the "how do I do this?" is really huge; so, I think there's just a huge groundswell of people actually starting the analytics journey, which is fantastic.

The other point I'd make, David, is that the distribution of leaders to majority has never been greater.  I was at a session yesterday with one of our clients, talking about putting learning data against sales data to determine its effect on business outcomes.  That's leading-edge work, that's beyond -- let's just say it's beyond HR, it's like HR and beyond.  But that's the people aspect of business practice being delivered through a people analytics team.

I would say the majority of practitioners getting into people analytics, "Yeah, I'd like to get there", but they probably see that as five years down the line.  And yet we've got -- and again, I know a lot of the folks that you talk to would be in that same state, that the level of sophistication and impact and transformation they're able to effect through their work is at the strategic HR level, strategic business level.  At the same time, we've still got folks who are like, "Yeah, I'd just like to have an accurate headcount".  So, I haven't seen the spread quite as broad as this.

David Green: Yeah, certainly, I mean we've talked about this before.  But for the benefit of listeners, we're both seeing more companies investing in people analytics teams, those people analytics teams getting bigger in terms of the people, the amount of people and the variety of skills that they've got in there; more spend now on people analytics technology, it's a category in itself; and more impact as well, so that shift in people analytics being about HR, something to help HR to be really people analytics about the business.  I know it's something that you've talked about a lot, Ian. 

Have you seen that shift; have you seen a shift in what business leaders expect from HR, and maybe that's as a result of people analytics?  And, what are you seeing with some of the clients that you're working with at Visier?

Ian Cook: Great question, David, I love it.  So, we've always talked about this notion of a push and a pull strategy when it comes to the adoption of people analytics.  The push strategy was HR population, educating HR business partner, taking that out to business leaders, "Hey, we think you should pay attention to your people data".  We've seen a lot of success with that push strategy on things like using predictive retention.

What the pandemic created was this enormous pull wave of our own usage.  So, Visier's orchestrated to understand who's looking at it.  I looked at it the other week, and we get about a million people hitting our system every week.  We saw a 40% spike in consumption in March 2020.  That consumption wasn't more HR people coming in, and again that's not new clients; that's new users.  Those new users were people managers, business unit leaders, divisional leaders.  They were people who were having to make decisions about people, and that's very consistent in terms of the change.

That's created this pull where actually to run my business, in some elements it's scarcity, in some elements it's a lack of skill, in some elements it's questions around cost; and all of those questions have become front and centre, highly present, and people understand that the data's there to answer them.  So, we talk about a people impact gap, where the business has woken up, let's just say, to the effect that people have on results.  The businesses are becoming aware there's this rich source of fuel in the transactional data sets that live within HR, and we see more of a pull from business like, "You should be able to answer this question for me, you should be able to help this".

So, whilst progress has been made through taking it to the business, engaging in the business, but what changed in the last two years is this demand curve from the business saying, "I can't run without understanding my people the right way".  Much of that, not just, "What can they do and what do I pay them?" but, "Where are they?  What else could they do?  How is their sentiment about work and their connection to us as a business?"  I'm going to try and avoid the word, engagement; I might just remove that word from my vocabulary for the next few years!  It's somewhat overused.  So, how are they connected to the business?

David Green: Yeah, and I think, as you said, initially when the pandemic broke out, a lot of it I guess was about business continuity, what offices, what plants, what distribution centres are we going to have to close down?  Great example from a company that we work with, I think you might work with them as well, they're a pharma distribution company and their people analytics team was able to pinpoint, within a matter of a few days, when their distribution centre on the east coast of the US was going to need to shut down, and they were able to put contingency plans in place to make sure that the pharmacies and the hospitals were serviced.  You can't get more important than that.

Then, as you said, it's about understanding employee sentiment.  And I think as we now hopefully come out of the pandemic, and move into the post-pandemic world, it's going to be a lot about understanding hybrid work, I guess, isn't it?  And, will employee sentiment change in the next 6, 12 months; and will employer sentiment around wanting people back in the office, and I'm painting a very broad brush there, will that change as well as they start to see the positive impacts of hybrid working?  Who knows, but…

Ian Cook: I love the comment, David, because I think what is creating this pull from the business is the number of examples that now you have, that we have, that are now available for executives to understand that people data can avoid something like shutting down an entire plant.  That is not a trivial outcome in any way, shape or form; it takes it so far beyond resignation.  So, I think those educational, informative pieces, they start to work around business and somebody goes, "Well, how come they can do that and we can't, and what's that about?"

So, that's what I mean, that's a great example of that pull strategy, these demonstrated results' capacity to actually make a difference is become understood, and that's when change really accelerates.

David Green: And I guess more expectation for the business, more realisation of what people analytics can do for the business; that's a shift in expectation levels on HR, and people analytics teams.  You've spoken about the people impact gap, with business leaders on one side of that chasm and HR on the other; can you explain why that gap exists and what companies can do, what people analytics leaders, what HR professionals can do to close that gap?

Ian Cook: Definitely.  So, I think the gap exists for two reasons.  One is that very few business leaders are really trained in the aspects of human performance that make a difference in their world.  So, you're often promoted as a manager, because you are capable of managing the task components; you may or may not have gifts in terms of activating people.  And yet, the amount of revenue we all generate from knowledge is really, really high. 

So, when you rely on knowledge and you rely on discretion and you rely on an individual to give of their best, it becomes less about, "Did you get A done?" and it becomes more about, "How do I help you be the best at this task?"  So, there's actually been a shift in what it means to lead people and manage people.  It's been subtle, it's been over time.  The massive "go home and work" experiment basically brought that into bright relief; because all these managers who managed by walking around in the past couldn't do it.

I think there's this whole notion of managerial capability became really key, and so the gap existed because people weren't thinking that way.  They were like, "I've got my stuff done, I've got my people, we're fine, we'll just carry on".  So, the realisation of the gap, the what's possible, the, "I feel like I'm fighting with one hand tied behind my back because I don't have the data", so that's what's creating the energy on one side of the gap.

The other side of the gap, and I've talked about this a lot, for the longest time, the focus of HR investment has been around efficiency, and I'm slightly frustrated that we're seeing it again, in that we replaced the HRIS, that wave's happened, that took form-filling to a cloud-based, digital transactional system; it got you efficiency gains.  Though again, the evidence for that return to the business is poor.  Now, we're in the next wave where, let's stick some technology on top of the technology we had, which was supposed to make us more efficient, that's going to make that more efficient.  There's a point where efficiency becomes a diminishing return; the investment for reward is just not there.

So, I think on the people side, often the investments have been initially, correctly, focused on efficiency, and I talked to a few consultants who were part of that wave and they're like, "Yeah, it was the right thing to do", but it's not the right thing to do anymore.  So, we created the conditions in HR of digitising all the events, all the transactions, all this massive amount of insight about people; we haven't made the investment to take that to the business.  Sometimes, we haven't seen it as our job, sometimes we don't know it's possible.

I think there's been growth and development in each of these functional aspects of the business that were done in silos, but now we're at a phase in business where we have to go back and re-join the silos.  The way I've seen it done, and you've probably seen the same, is if you can, you hire somebody who's got that business acumen and analytic orientation to walk across the chasm and say, "How can I help?  What business problem are you facing?  How do people make or break your goals this year?  If you had data that would inform this strategy, what would it look like, how would you use it, how can I get that to you?"

So, you engage with the stakeholders on the business side, not in a blanket like, "Here's the dashboard everybody needs".  That's a bit of an HR out-push; there's a place for that, but I think we start to really close this gap when, and again, I think you and I know exactly the same story about that distribution business, where you walk into the business and say, "What are you facing in these uncertain times?  If I can find some data to help you make a decision about that, would you pay attention to it; would you welcome it?"  That revolutionised the trajectory for that team.

It starts with an individual, it starts with an intent from the CHO, we have seen it start with a willingness from the business side.  There's always friendlies on the business side who increasingly get, "People make or break my results".  So, I think you start to close the chasm through stakeholder engagement, investment in the capability, and just really the long and the short of it is prioritising it.

David Green: Yeah, tying it to, "What are the questions we can answer with analytics?  What are some of the hypotheses that you want to test?"  As you said, it's having that business acumen to break things down, isn't it, to hypotheses and questions that you can answer with analytics and with data. 

I'm going to move on to the next one.  You mentioned earlier that we are in a mass adoption phase now, people analytics, which means there are a lot of companies that are still early in their people analytics journey.  We've probably got people listening to this that are either in people analytics teams that have been recently formed, or they're HR professionals working in organisations that are investing in people analytics.  Many of these have invested in HR technology, they may even have some good data, but they're not quite sure how to move to the next stage.  What advice would you give to those companies?

Ian Cook: My advice to those folks is to not underestimate the value of accurate headcount.  The organisations that we have seen that have grown success from their practice started by engaging finance and engaging other stakeholders in a simple conversation around, what is the source of truth for headcount; because, it wasn't coming from their HRIS, it wasn't coming from finance.  They needed to treat the data from their HRIS to clean it, and they needed to get an accurate conversation going at the executive level, so decisions about whether we hire or don't hire or move money from one group to another group, are actually based on a clear and true picture.

Again, I think headcount, I don't really see that being featured in people analytics presentations; you won't.  However, you should not underestimate the value of a clean, accurate headcount that finance and HR agree on.  A win for us is when we hear one of our clients say, "Yeah, finance have given us responsibility as the source of accurate headcount reporting".  Do not underestimate that as a win, because all of a sudden you are the credible source of data about people that the business will come to and trust to move it forward, because you've demonstrated that you can create a foundational metric like revenue. 

So, don't get pulled away by this notion that you have to do a sort of Google moonshot and that somehow you will be a hero.  I'm really not in the "follow the heroes" mindset around people analytics.  I love the work and love talking to people.  It's exciting, it's a kind of intellectual joy.  But if you're actually going to pragmatically move your practice forward, get the business to recognise that you are the source of current, accurate headcount and the associated, specific cost of people.  And once you've got that established, you've earned the right to go and ask the next question, which is, "Okay, now we've got this data, what do we layer on that will answer a more sophisticated question?"

The other thing, the really, really strong piece of advice I have is, say no!  HR has often grown up as a service-oriented piece of the business, "Business asks, we do".  Again, the successful people analytics teams, we know they are, "Actually, we have a purpose.  We have a direction and a mission.  We exist to serve the business in a very specific way.  If your request falls outside of that, we will politely decline", because for all the energy and people and technology that's going into this space, there's still not enough.  So, you only get strategic when you say no.  It earns you credibility.  Whilst it feels like it's wrong, it raises your profile because, "Oh, actually you value your time to the level where you'll defend it". 

Even on a personal level, it's a brilliant tactic.  You have to do it politely, you have to do it the right way but actually, "This runaround for a whole bunch of data that you think you want, yeah, not doing that.  What have you thought about in terms of how it helps the business?  How consistently would you need this?  Is this just designed to just re-enforce a decision you've already made, or is this actually going to change the shape of the answer, because I'm not in the business of retroactively proving someone made a good or bad decision, I'm in the business of changing the future trajectory?"  So, saying no, saying no politely, being really crystal clear about what you do and don't do.

Another traditional thing that we've done in HR, and I've been guilty of this myself, like performance management process as well, "We've got to roll out to everybody and everybody's got to be the same".  No, you do not have to roll people analytics out to everybody.  Find one place where you can make a difference.  Go deep, make a difference and then spread virally from there.  So, the change methodology to actually build adoption is counter to, "Well, everybody's got to hit the HRIS on the same day, so everybody has to hit the people analytics system on the same day", fundamentally wrong.  If only five people are using your people analytics system, but you're saving the business $5 million, that's probably okay.

David Green: It gives you a good base, that's for sure.  And I love that, so if we start with, build credibility with the business, earn trust from finance, you don't want finance trying to disagree with your figures.  That's a really good point there you made, it's so important.  And then prioritise.  We work with organisations on a kind of two-by-two, "Hey, we're consultants", impact complexity, what you want is high impact, low complexity ideally; but yes, some high impact, high complexity of course, the kind of big projects, probably around skills and stuff like that.

Then, as you said, I mean I hear it all the time with analytics, "Don't try and boil the ocean".  If you're focusing on a couple of areas of your business that are maybe experiencing high growth, or are strategically important versus maybe some of the legacy parts of your business, do that, make an impact and then spread from there as you get more investment; and you will get more investment if you create an impact.

Ian Cook: You also get more investment when you say no.  We just recently closed a UK client, we're excited about that, and one of the arch steps in the process was this individual saying, "I would love to do that.  I see the value in it, I see this as an immense opportunity for the business to do that.  With my current resources, I cannot do this consistently at a level of quality that you need.  I can show you what I am doing and what I can do, but whilst this is a really legitimate request, I am unable to meet it in a way that I'm comfortable with without further resource".  And that's a really positive like, "I'm here to help, but I'm not here to kill myself", and I think that's a brilliant and much needed approach and habit HR should practise more.

David Green: I agree.  So, one level up from companies who are early on in their journeys, other companies might be investing in dashboarding tools that might aggregate data, you probably know a lot about this, and be on a mission to democratise their data, but they might be struggling to get people on board with that mission, so whether that's people in HR, maybe that's people in the business.  What advice would you have for those companies?

David Green: I'll take those in order, David, if I may.  So, the first one is, our CPO, Paul Rubenstein does this really nicely.  So, you've got credibility, you've got trust and you're in the broader adoption.  Target a certain level, like a business unit leader or a department head, who's got a big enough population that they can't see what's going on, so they care.  And then just develop a cadence through the HR business partner of a quarterly update. 

So, fit it into the quarterly business review, and its significant joiners, significant leavers, significant changes, what's happening in terms of pay change, any risks around possible significant exits or sentiment change that may affect your capacity to get your business done; and you just set that up as a cadence, so then it becomes like, "Oh, okay, when I used to engage with HR, they were telling me who hadn't filled in their performance review.  Now they're coming and giving me, even if it's all green, they're giving me a balanced perspective on my people such that I can look at money and people and work out if I'm going to get there", and just make that a cadence and build that up as a habit.

Again, it's one of those things that's worth piloting with friendlies, so find the business leader who cares, run the cycle, run the content, run the process, get it good and then spread, because there's so many unknown unknowns in there, in terms of do people know how to interpret resignation properly, do people understand what this data means; do you have the confidence in the business of assembling this data and sharing it?  That's one piece.

The second piece is, we talk to lots and lots of people who are like, "Well, I'm just struggling to make all the assets I need, because I made 20 dashboards [or] I made 10 dashboards, and that was what the business leader wanted.  They now want their 20 reports to see the same, but I've got to run security, I've got to run filtering, I've got to run all of these things on top of the dashboard", and that's where the traditional dashboard model breaks.

So, what we've done inside our technology and we think this is the right way to go, is actually get personalisation into the technology.  Based on an event that happens, we will email this very, very tight, discreet set of information to a manager about that event, "Your representation levels have dropped below the benchmark set by the business.  Here's where it changed, here's what it was, here's who left, here's who joined, here's why this is the case", triggered only when that measure has shifted, into their inbox, that leads back to the application.

We think this, I call it the "last mile" problem, but we think this is the right way to actually understand the broad adoption of data.  It's not more dashboards, it's not more education, it's not more, "Well, let's turn you into an analyst and hope you explore and find what you need".  We've tried that, we were guilty of thinking that was the right approach.  We haven't found the traction with it that we think, so we're kind of flipping, where instead the data informs what is sent, and what is sent is then personalised, relevant, contextualised for that individual.

So, getting it into the hands of each manager isn't just doing more of the same.  For me, it's a quantum step in complexity.  We can trigger the event, because we've got benchmark rates inside our technology, so I know if your resignation is going up 10% higher than your benchmark, it's in my technology, I know that.  So, that is a meaningful result to a manager, "Don't just tell me it's going up, tell me it's going up more than the market", because that's scary.  So, you need the context, you need the event set for the customer from your own organisation, you need the context for the organisation in order to start triggering those things well.

We're right at the leading edge of that, Dave, I'll be totally up front.  We released the feature two releases ago, so it's still early days, but that's how we are conceiving -- and we just think we just got started, but that's how we are conceiving of this, getting it out to the thousands of managers that we have.  I hope people know Gary Russo.  If you don't know Gary Russo, find him on LinkedIn, follow him.  He distributes people data to 13,000 managers, 10% of his workforce.  So, he is a team of 10 and he is serving 13,000 people, so it gives you a sense of what can be done.  And he'd be the first to say, "Not everybody's in there every week and not everybody's getting what they need, but we know this is the direction it's heading and we know it needs to be better".

David Green: And I guess ultimately, what we want to do is dry action, and the more you personalise something for a manager, make it easy for them, and I guess maybe a next step would be, "These are the recommended actions".  And I guess that's not going to apply to everything, of course, but you could get to that recommended action, that nudge to get decisions taken; or, it drives a conversation with the HR business partner, I guess, it could be either or, couldn't it?

Ian Cook: I think it is.  And again, I always like to have the pragmatic conversation, because lots of people are excited about a nudge.  I prefer to talk about that, "It's a nudge, but it's a frame the decision space".  Having worked with people, there's a rule with people, "What is true of a population, is not true of a person; an individual's an agent and an agent has choice".  So, as soon as you prescribe to the manager, "Do X", and the manager says, "I've been told to do X", think about your own emotional reaction to that. 

Even if you are a piece of the population that's supposed to respond in a certain way, just out of badness, you're going to do something different!  So, this notion that technology can somehow or other inform a manager of exactly the right action to make a human do something is just fundamentally flawed at its source, because humans are agents of choice.  As soon as they are presented with a context or a situation, their own emotions will drive how they respond to that.

So, when we talk about nudges or guidance, we actually talk about informing the decision space, "Here are three strategies that are known to be effective in this context; here's three ideas for you to think about, look at and guide".  So, rather than make a decision for the manager, which again, my experience of that is most people are like, "Don't tell me what to do, you're just a dumb machine!"  I have that reaction to stuff that tries to narrow the decision space for me, so I'm not guessing.  My decision is made easier, my decision is supported by good information that has been researched, as opposed to me guessing from what I've read on some blog recently.

I mean, we're already kind of in that space, but I think that's as close to prescription as you get.

David Green: HR; we always take about, "We need to bring HR on.  HR needs to become more data-literate".  Now, what we clearly aren't saying is that HR all need to become data scientists, that's certainly not the case.  And obviously, tools like Visier actually mean that doesn't need to happen as well.  But we do believe they need to become more data-literate.  I think HR, as a profession, needs to become more data-literate, be able to think more analytically, talk about the stories around data.  Now, what's your perspective on how HR professionals can achieve this?

Ian Cook: Three things.

David Green: Three things?

Ian Cook: Three things.  Let's try three and see if I got it right.  The first is intent from the CHRO.  I think the CHRO sets the tone by which HR business partners provide their consulting.  And again, we could likely go through our clients, I suspect you would do your same, and go, where we have a CHRO that says, "Data's not your job, but it is part of your decision cycle", you need to be oriented to considering the data and people decisions, or you're not really aligned to my HR business partner approach. 

The second piece is kind of baseline information.  I mean, I'm still slightly bemused, and this is probably on me even, but at just the lack of certain measures and certain metrics.  We hear people use "attrition rate".  I really never like the word, attrition, it's not really that comfortable a word.  It possibly goes back to my early history lessons about World War I; but resignation rate I see coming through in the press.  Well, resignation rate, that's people leaving the workforce.  No, that's somebody voluntarily resigning from your business; they may or may not leave the workforce.

So, I just think there's a massive amount of education on how do you get clear about what measures mean; how do you understand what those measures are?  If somebody said profit, we would all know what profit means.  So, I think there's just a baseline of relatively straightforward education around, headcount is this, resignation is that, our exit models involve this, movement is this, promotion is that; providing that information.

Then, the secondary piece which we've seen work really well is office hours.  So, rather than try and sheep-dip every single HR business partner into being analytically-oriented, we should have had the experiences where you try and create mass knowledge in a population.  You end up having to go through it again and again and again.  So, what happens with an office-hours approach is you create a baseline of knowledge, you put an expectation of practice, then you support the people who are trying to get it done.  So, as it becomes relevant for them, they can access somebody to guide, inform, shape, build their skills, one-on-one coaching, drilling into, "So, what does this actually mean?"

There are so many nuances and permutations as you start to use people data.  Trying to say, "It means this and only this", is a bit of a losing battle.  Again, this is from personal experience.  So, "Ian, my resignation rate is going up; what does that mean?"  "Well, it's probably bad, but let's go and look at the market and see if it's going up less than the market.  Let's look at if it's due to low performance, or people who joined us but we weren't really confident they were going to perform in the first place.  It ends up with so many contingencies, that to actually understand the meaning, those are best resolved when people work through a problem, as opposed to transmission of information.

So, don't think about building analytics capability as a chalk and talk problem; it's a use and resolve, and dig and experience problem.  So again, we've seen great success building up those sets: CHRO mandate, baseline understanding of the measures and what's possible, trust in the data and then emphasise learning through use.

David Green: Yeah, confidence, build confidence and community, I guess, it's so important.  Something we talk a lot about at Insight222 is that people analytics is not about HR, people analytics is about the business.  Are you seeing more HR organisations now addressing -- we've talked about this a little bit already, now addressing business problems with people data, and how do you see how that process can be improved?

Ian Cook: We do, is the first answer.  Two ways in which it can be improved.  One is to continue to hire people into the people analytics domain, who are oriented towards business problems, business situations, so they come with a business-operations-first mindset and they have the credibility, consulting ability, to connect with those individuals.  I mean, it is quite simple: understand how the business makes money, understand what it takes for the business to be successful, which is easier said than done, but that's sort of a first base. 

The second piece we've seen certain organisations do is actually put in a people analyst overlay to the business unit leader, in the same way as they'd have a senior HR business partner attached to a business unit leader.  They don't try and make that HR business partner both a business partner for the people, and a deeply capable analytics individual.  That's such a broad spectrum of practice; there's just very few people who have the orientation, let alone the skill.  So, they double up and put a capable analyst alongside the business unit leader.

So, there's the FP&A person, there's the people analytics person, the business unit leader and a business partner.  So, that starts to become this powerhouse of insight that can really help those 200, 300, 500, 1,000-person business units richly use people and cost data to actually get the business done.

One thing that you need to do, David, to get to that level of implementation skill, is to automate the data piece.  We see it in our own data, there's a transformation of the number of data engineers to the number of analysts, where the data-wrangling group shrinks, but the analyst population massively increases.  So, there's this maturity curve where it both seems strange to people, because if you're in the midst of trying to wrangle your data and it's a mess and it's difficult, those people are your friend and it's really valuable; but once you've got that, you have to build it in such a way that it can be automated, so that you can focus on the interpretation and use, and not get stuck in the constant break-fix of data.

David Green: People love examples, and I know you know many examples of companies and clients that you work with.  What are the best examples you've witnessed of companies that have made a real impact with people analytics, and where you've seen people using people data to solve real business problems?

Ian Cook: I have a spine-chilling one, which I'll share!  It's public, it's on the Visier website; it relates to Providence, Gary Russo and Mark Smith over there.  So, Gary's been an expert practitioner for many years.  They are in the throes of a great resignation and nursing staff being absolutely essential to their quality of care.  I really admire Providence, because their primary measure is care quality; it's not financial stability, it is care quality, and they look at, how do we turn our money back into care quality.

Gary went to the finance group and he went to the nursing leadership, so direct contact with the business stakeholders, and he said, "I want to understand the dynamics of a nursing population".  So, his very first analysis was actually, "Which jobs inside my business are sensitive to change in pay?"  What he found would surprise a lot of people; in only 1% of their jobs does paying more have an impact on retention.  Most people think the default mindset in most businesses, "Oh, people are going to leave; pay them more".

We're kind of beyond that transactional world, but it was true in Providence's case in 1% of their roles.  It's still a lot of people, but it's 1% of their roles.  That for me was the first marker.  It's like, "Let's see if our assumptions are right before we actually go and mess with the stuff".  Then they worked out what they would need to pay in order to change the trajectory on resignation, and what that would mean in terms of cost to the business, but returns to the business of lost delivery, all the other pieces.

So, long story short, they've been running that for a while.  Their estimation is they've saved the business $6 million and they've reduced their resignation rate by 30% in that targeted population.  The key piece for me is, Gary had to go to the Head of Finance and say, "We're going to pay people more; it's going to save us money".  The key piece for me is they believed him, he could prove it, they've done it and it worked. 

This isn't HR for HR, this is people data, a deep understanding of the dynamic inside the business, with finance, nursing leadership, people analytics, really not just helping the business on the financial side, because Providence is going to turn that straight back into quality care; it's just a wonderful, really, really amazing win story.  I have a ton of respect for Gary, I hope that's really clear, but I think that's something we should all aspire to.

David Green: Tell us, Ian, what goes wrong when a company fails to make decisions based on their people data.

Ian Cook: Where do I start, David?  There's so many of these that are really well documented.  My favourite and very simple one is this thing called "turnover contagion".  I have been engaged, in a prior life as a consultant, in a number of circumstances where employees were let go.  Typically finance will look at the conversation and go, "We've got to cut budget in this unit by 5%, 10%, so let's let go the people who represent that full budget amount". 

But there's this thing called turnover contagion, when your friends are let go, or a reduction in force is put into the business.  It creates uncertainty, it creates shock, it creates all kinds of other human reactions which leads to more turnover.  So it is really well-documented that organisations often fail to save the money they anticipated, because the way they execute on a riff actually creates more cost that they didn't anticipate, that then destroys the entire benefit they were looking for in the first place.

It is such an oft repeated and simple example, actually looking at how people are going to react to this news, what else might happen; how would we adjust our plan to take that into consideration, because my view is not, "We shouldn't let go of the people", there are business realities.  There's no point running at a loss, because the whole business goes down, "But if we've got to reduce 10%, let's take turnover contagion into account.  Maybe we just need to start by letting go 5% and see what happens and adjust; let's increment the decision".

We do have other examples from clients where again, finance came with this exact mental model and the people analytics team said, "Whoa, give us a week, we think we can help".  They looked at the maths, they looked at the timeframe.  They said, "If we don't fire anybody, but we let a hiring freeze, natural attrition, some early retirement happen, we'll hit your number.  We will not have given anybody a pink slip.  People may or may not understand the massive difference that is, but if you then want to rehire or you want to be seen as a good player in your community, if you've been able to adjust cost without firing anybody, there is nobody out on Facebook yelling about how bad an employer you are.  That doesn't show up on a balance sheet, but it should be considered in the decision".

David Green: Yeah, totally agree.  Good example, Ian.  We're moving into the last couple of questions.  Obviously, you work for Visier, you've helped all kinds of companies implement the technology and help them on their people analytics journey, but I'd love to hear your take on what is the role of technology in being successful in people analytics?  For example, there are organisations out there who have built their own tool to provide some of the capabilities that Visier provides; what are your thoughts on build versus buy when it comes to people analytics?

Ian Cook: The data I have on that, David, is a couple-fold.  The technology is a catalyst and total cost of ownership-wise, you have to think about the end state you are going to get to when you start.  This is what lots of organisations didn't do, they were like, "Oh, doing people analytics.  Quick, grab Tableau, I can make a dashboard and off I go".  Three years later, we talk to these people, they are buried in data management hell.  The difference in an application that is purpose-built to handle people data is a level of automation on the pipeline of data, the standardisation of data, all of those various components that are super-powerful.

The second piece would be, and again, differentiating Visier, I know the resignation rate to the end of March 2022 out of a population of 10 million employee records.  Any customer of mine can go and look at that and can use that in their decision basis.  I don't know anybody who's built their own analytics tech stack that can aggregate across 10 million employee records and return it back in their system.  It's just a capability that's not there, because you're not sitting on the data like we are.

When you're answering your own business questions, no problem.  If you can grab that data and attach it to a Tableau dashboard, lightweight for a business unit leader, no problem.  As you start to need to position that in front of 500, 1,000 managers to say, "You should care about your trajectory of women's representation, because you are not beating the market", that lack of infrastructure is crushing.

So, we're in the view of build and buy.  What we believe about our technology, which is borne out by its use is because we've thought about the people data challenges, like hierarchy, like security, like the mashing together on a data model of acquisition data with learning data with geo-story points, our facility to use and reshape that is way faster than a data warehouse, and it persists and it persists everywhere that, that at your core is the only way you're going to be able to automate the distribution of data at the scale you need to actually achieve what is the end state of people analytics.

So, somewhere in the region of 60% of our prospect conversations right now are people who've built and come to the scalability world.  We've named it; it's so prevalent in our conversation set.  I'm supporting 25 dashboards.  To support the next 25, I need 5 more people.  There has to be a better way.  Not to get too political on it, David; build's been fantastic, we've proven a ton of stuff, we've demonstrated the value, it is not a wrong approach.  But to truly get to this scale, you're going to have to introduce a level of automation, for one thing, and you're going to have to introduce some market context as another, and that starts to become an order of magnitude more difficult than just building out your own practice.

David Green: It makes sense.  So, Ian, moving to the last question, and this is the one we're asking everyone on this series, what do you believe to be the two to three things that HR will really need to do to add business value as we hopefully, and I will still say hopefully, come out of the pandemic?

Ian Cook: I think HR needs to go back and focus on the effectiveness of individuals and teams as it relates to managerial decision-making.  So, I think we need to get out of our heads of, "How do I make the capture of the engagement survey better or more good-looking?  And, how do I help somebody use that data to enhance their team, decide which opportunity, or combination of people, are going to go and do that work?"

So, it's about what are we focusing on; how do we use data to inform those decisions; how do we bring all that data together?  Again, one of the things I know that's been challenging in the past, and we've seen it grow over ten years is, "Well, I've just got the headcount data [or] I've just got the HRIS data.  There's something that's interesting, but there's a lot more richness".  Classically now, a client will have six separate source systems integrated inside Visier, that the most rapid-growing space is sentiment data, "How do I feel and experience work?" not aggregated engagement, but individual raw-level survey data.

You can really start to close this loop on, "We made a policy change.  Some people liked it, some people hated it.  We were looking at our different segments of population, how we're responding to those different segments", because the notion that there will be a single policy that applies to every employee going forward, and that somehow that will work, I think we have to let go of that belief, because I don't think it's right for 2020.  We got away with it in the past, because everybody showed up to the office; but we are in a much more diverse working pattern world going forward.

So, yeah, I think the focus really is on enabling managers, be it business unit leaders, be it team leaders, to appropriately use their people data in driving, enabling, activating day-to-day performance of people, and then assembling all of the data you need to do that.

David Green: And I guess, as companies come back, some are already back, whatever back means, but as the conversation around hybrid evolves, people data is going to be absolutely critical to that, isn't it?  So, if Company A is deciding that we're going to predominantly be in-person, four days a week, whatever it is, people data's going to tell us what's the impact, positive or negative, on retention, on promotion, on succession-planning, on our ability to attract key talent versus an organisation that maybe is adopting a more flexible approach, what's the impact, positive or negative, on our ability to attract different talent pools in different locations, get more diversity into our workforce?  It's just so many questions that you can answer.

Ian Cook: There are lots of questions you can answer.  I'd also recommend that people focus on, what's the impact on the work?  A friend of mine who works for a large software company, that I shall not name, shared that they had 20% more code check-ins in their flexible work situation than prior.  So, that's basically saving one-fifth of their headcount budget.  Code check-in means that the code is ready to ship, so it's product, it's revenue-generating product.  So, 20% more code check-ins; let's not lose sight of that in all these decisions about should you or should you not be in the office.

I know that's the way the conversation's being framed, I feel like that's missing the point in terms of actually, let's use the data to focus on the work, let's give people permission to do the work they need where they need it to get the right things done.  We aren't merely talking hybrid or remote, we're talking flexibility.  That's the policy we're in, but we need to study the work.

So again, what does HR -- I think the people analytics teams need to start thinking about how they study the work, so that we can make these experiments, we can look at, "You know what, we sent developers home.  We got a 20% lift in productivity.  Why do we want to bring them back to an open-plan office so they can hide under their headphones and be disrupted every 15 minutes?  We know that's a bad performance situation".

So, long answer and not necessarily in the flow of how the press are playing it, but I'm always about trying to get to the core of what we're actually trying to do, and use data in a smart way to do that.

David Green: Yeah.  As you said, lots of focus on the "where" at the moment, but there needs to be more on, as you said, the work itself; so yeah, that's a really good point.  It's a great place to end it, Ian.  Thank you so much for being a guest on the Digital HR Leaders podcast.  Please can you let listeners know how they can stay in touch with you, follow you on social media.  I know you post a question every Thursday on LinkedIn, which I think people should get involved in, and also find out more about Visier.

Ian Cook: Yeah, so personally, me, the best place to follow me is LinkedIn.  I've not managed to find my way onto other social platforms, but I love LinkedIn.  I run a Thursday debate, which is invariably a people analytics or a people behavioural question, eliciting different points of view, so that we can all learn.  I think it gets pretty good play, so it's a fun place to learn if you're interested in people analytics.  I also tend to post on issues around the labour market and what's changing, so LinkedIn is the place to connect with me for sure.

Then, if you want to learn more about Visier, our website is a great place to start.  We have a blog; again, lots of good learning on practices.  There is a path to success contained within all of that insight that will help any practitioner avoid some pitfalls and accelerate their path, so that would be the two ways to go; visier.com.

David Green: Brilliant, Ian, thanks very much and I'm really looking forward at some point to seeing you in person again, hopefully at some point this year.

Ian Cook: Yeah, likewise, Dave.  It will be sometime this year.  Take care.