What does the current landscape of HR and people analytics look like today? In this episode of the Digital HR Leaders Podcast, host David Green is joined by Dirk Jonker, CEO of Crunchr, to discuss the latest developments for the industry.  

From organisational network analysis to the current focus on skills and generative AI, topics covered in the discussion include: 

• Insights into how people analytics is enabling HR to play a more active role in business transformation and strategic alignment. 

• The importance of partnering with finance to enhance cost management and demonstrate the commercial value of HR initiatives. 

• The critical role of building data literacy within HR teams to leverage analytics effectively and drive informed decision-making. 

• The essential role of middle managers in driving organisational change and how data can empower them to lead more effectively. 

• An urgent discussion on why HR needs to start gathering and reporting on ESG metrics to meet new regulations and drive sustainable business practices. 

• The future of people analytics and how HR can become a central part of any executive committee. 

Join David and Dirk as they delve into these key topics and provide valuable insights for HR professionals looking to stay ahead in the rapidly evolving world of people analytics.  

Support for this podcast comes from Crunchr, a platform that integrates an HR data lake with state-of-the-art people analytics. Whether you're an advanced user or just starting out, Crunchr's generative AI co-pilot helps you unlock insights with ease. 

You can learn more by visiting  www.crunchr.com

[0:00:00] David Green: At the start of every year, industry leaders in HR and People Analytics eagerly peer into the future, analysing trends, emerging technologies, and workplace shifts to offer us valuable insights and predictions.  One standout leader in this field is Dirk Jonker, CEO of Crunchr.  Known for his ability to make complex topics relatable, often by connecting them to famous song lyrics and other cultural references, Dirk also authored an insightful article forecasting the key forces set to transform HR in 2024.   

Today, approximately halfway through the year, Dirk joins me to discuss the current state of HR and People Analytics, and review where these predictions stand.  We'll explore the evolving landscape, not least the buzz around skills and generative AI.  We'll also examine how People Analytics is empowering HR to drive business transformation, the critical partnership between HR and finance, and the growing need for data literacy within HR teams.  Additionally, we'll highlight the pivotal role of middle managers in driving change and the urgent necessity for HR to gather and report on ESG metrics.  These are crucial topics that resonate with every HR and People Analytics professional.  So, without further ado, let's dive in and hear from Dirk Jonker.   

Dirk, welcome back to the Digital HR Leaders podcast.  It's been over four years, incredibly, since you last appeared on the show, and a lot has happened since then.  So, maybe as well as providing an introduction to you and your background and also to Crunchr, please let our listeners know how Crunchr has grown in the last four years too. 

[0:02:06] Dirk Jonker: Yeah, hey David, thanks to have me back, I'm really looking forward to this conversation.  So, maybe for those of you who don't know Crunchr, we're basically a very intuitive platform for workforce reporting, analytics planning.  We're super-passionate about the space because we are on a mission to empower HR to drive business conversations with confidence and clarity.  And you're asking about what has changed so for the last couple of years.  To be honest, I don't even know where to start.  From a company point of view, the team has tripled.  We're still headquartered in Amsterdam, but we now have offices in London, in Boston.  I've moved to Boston.  Many of the teammates from the first years are still with us.  I'm super-proud of the culture that we built, the product that we built, and together with our customers it's a really powerful partnership too.  Many customers are renewing for three years.   

If I look at the market, how that has changed, I think it's still discovering itself a bit.  You probably remember that three or four years back, it was all about organisational network analysis.  Today, people talk about skills, we're moving very quickly into Gen AI, and these are all very relevant, trending topics.  But what matters for companies most depends really on their business context and their maturity, so where they are in their journey.  So, probably also due to the work that you do, HR leaders are taking a pause and reflect on where they want to go and build a plan from there. 

[0:03:35] David Green: We're halfway through the year, or more or less halfway through the year.  So, I'd love to know from your perspective how these trends are mapping out so far in your work with global organisations and what you're seeing.  So, let's start with business transformation.  Are you seeing any movement with HR playing a more active role, and even leading business transformation in some organisations? 

[0:03:55] Dirk Jonker: I think business transformations are very long-term strategic programmes, so I'm not sure how much change we can already see in just five months.  But we do see again a shift in these transformations in the conversations that we have.  So, the conversations are less focused on technology and more on strategic business alignment.  This is a really big thing.  It's, I believe, often driven by board discussions on future of work.  These boards are really interested to understand what the impacts will be of the accelerated process automation on the blue collar workers, but also the impact of the ChatGPTs and alike on the white collar jobs.  So then the immediate next question, which moves into HR, is what is the impact on the workforce, how to fund this transition?  Business transformations are incredibly expensive, so how can we save cost here to reinvest in growth there?  And then also, as a third, how do we track the critical numbers and our goals to measure that this transformation is on track?   

So, those conversations are happening and those to me are leading indicators that HR is getting more deeply involved in business transformations. 

[0:05:06] David Green: Yeah, and all of those three steps that you talked about, they all require data, data to inform the transformation, but also data to inform how you're tracking against it.  And maybe talk a little bit about how the rise of people analytics, or continued rise of people analytics, is helping HR have that more active role in business transformation. 

[0:05:28] Dirk Jonker: Exactly.  People analytics is a beautiful methodology to really show where the risks and the opportunities are related to your goals, so you really know where to focus.  It helps to create a 360 view of the problem, to have better business conversations.  But then again, the most important part is that you not only talk about it and agree, but also set your critical metrics and track against these goals.  And those conversations are happening more and more, where the technical details around, how do we integrate with Workday?  What are the API connections?  I mean, of course, all of that stuff is really important.  It's very needed to play, but it's very distant from the board discussions that are happening, and HR is feeling that pressure and starts to make fantastic contributions. 

[0:06:20] David Green: Yeah, and in terms of tracking progress against business transformation, I mean we don't have to go into all of them, but what are some of the metrics that companies would typically be looking at from a people perspective? 

[0:06:32] Dirk Jonker: This really depends on the type of transformation.  So, let's maybe take cost as a very good example, because the funding of any transformation is incredibly important.  Typically, you would look at your spans, your layers, your managerial density, your SG&A ratios, so basically, how much HR do I have relative to the size of my organisation; how much finance do I have relative to the cost and to the revenue that I have?  Those are very easy metrics to track.  Then it comes to setting your goals, and then you need some kind of mechanism basically to report on it monthly.  So, I think those are some of the things that you can very easily track, but I think we will get into that later on. 

[0:07:12] David Green: There's a lot of focus on middle managers at the moment.  We've seen research from McKinsey and others talking about the role of middle managers and how that's changed and involved over the years, particularly things like hybrid work, technology, more distributed teams, etc.  How can we empower middle managers to be the catalyst through this transformation? 

[0:07:36] Dirk Jonker: It's really important that you bring this up because people analytics and all kinds of strategy will help us to create a path towards transformation, but we also need to execute, and this is where the middle managers come in.  These middle managers are incredibly important in supporting the programmes to drive the change and lead by example really.  It's not about just communicating, "This is what we're going to do", but it's about creating a belief.  I don't know if you saw the series, Ted Lasso, but it's all about that.  That is really needed to drive change.  So, let me give you a really simple example in my own company. 

Part of the work of our product engineering team is writing tests.  So, you write code to produce features and then you need to test if it works.  It's very important, but also not the most exciting work, but it's an excellent candidate for automation.  And driving change is not saying, "From now on, we're going to use AI to write the tests", but it's really to explain how this would free up time so we can work on more interesting stuff, like the AI assistant that brings us much closer to our vision, and therefore the value to our customers.  How we now think of middle management is changing a bit.  I mean, in the old days, we are all thinking about delayering, which basically means scanning out the layers of management.  McKinsey also was big on that five years back, but they realised that driving change happens through this layer.  And this new approach is, I believe, a better one, but it also requires HR to think it through.  So for example, can we enrich our Workday data, to use a metaphor, with Qualtrics data or Glint or Peakon, or whatever, to basically build this transformation monitor?  And can we use generic driver analysis to explain not just the standard use case and turnover, but can we explain using driver analysis, the acceleration and the adoption of our transformation programme on, for example, what makes a manager a good manager? 

[0:09:37] David Green: The next one I'd like to cover, and I guess it's kind of linked to that, it's definitely linked to driving business outcomes with people analytics, and interested to hear your thoughts on this because we've talked about this before as well, about partnering of finance to improve cost margins.  We know how important it is to demonstrate the commercial value of HR initiatives to gain board buy-in.  Our research at Insight222 interestingly found that only 24% of the 271 companies that participated in our People Analytics Trends research in 2023 had built relationships with finance.  I'd love to hear your take on this, and maybe some of the research or the examples you've gone on about, where people analytics partners effectively with finance. 

[0:11:21] Dirk Jonker: Let's do some root cause analysis first.  I really believe that finance and HR, they sit on completely different islands, and on every island they speak a different language.  So, on the island of finance, they talk about unit economics, critical numbers, OPEX management, margins, revenue growth, productivity, efficiency programmes.  And on the island of HR, we talk about people, organisation, leadership, engagement, culture, skills.  And both islands do really important work.  And at first, it feels a bit like a parallel universe.  But what we see very successful companies do is to build linkages and to start to speak each other's language.  So for example, why don't we start agreeing by redefining the headcount and FTE definition?  Why don't we, in HR, start to add cost centres and profit centres to our analysis?  Why don't we help to quantify HR practices, for example, absenteeism, first-year turnover, having too many layers, and translate that into unique economics, into margins, etc?  So, that is important.   

One feature, let me give you an example, that really helped our clients big time was to show the headcount work on cost.  So, everyone knows the waterfall charts and we all do this with headcount, some companies do this with FTE, but you can actually do this on anything.  So again, we generalise this and now we can do this on fully loaded labour costs.  And why is this important?  Imagine that you are working for a company where in certain call centres, there are budgets to reduce the fully loaded labour costs.  Finance is basically getting their bookings on the ledgers for payroll, but they just see the end-of-month balance.  So, let's say finance observes an increase in cost centre 423, goes to HR and says like, "Listen, dudes, we agreed that we were going to reduce fully loaded labour costs, but it increased".  HR says, "What do you mean you increased cost in centre 423; we didn't hire anyone?"  And now with the headcount work on cost, you immediately see that they're both right.  They did not hire extra people, but they moved people internally into a call centre.  And also, some other people increased their hours, which increases cost.  So, we need to build these bridges.   

Another thing that I would say is that we often talk about finance as they figured everything out.  I think they are advanced, but they definitely didn't figure everything out yet.  What they did really well is they started to speak business language.  So, years back, they talked about cost centres and ledgers, and now they talk about margin and revenue and this helped them to grow from an accounting role into what we now call finance, and from the most boring job in the world to the number two position in every single company.  This is the path that I wish HR is going to. 

[0:14:27] David Green: Yeah, we've got to get away from our HR language and nuances and, as you said, convert it to the language of the business.  And actually, if we want to build the relationship with finance as a profession, then that's what we need to do.  Now, that lends it quite nicely to the next topic, quite an adjacent topic, around building data literacy in HR.  Again, if we look at the research that we've done at Insight222, we still see a gap between the expectation of the CHRO and the reality on the ground.  So, last year in the People Analytics Trends research, 88% of CHROs and those participating 271 companies say they regard People Analytics as an essential part of the HR strategy, but only 55% of those companies say they've got a data-driven culture in HR.   

Now, the good news, that went up from 42% in 2021 and 49% in 2023, so we are getting there as a profession, albeit slowly.  As a CEO of a successful People Analytics Technology firm, I'd love to hear your thoughts on this topic, and how do we build that muscle, that data-literate muscle in HR? 

[0:15:38] Dirk Jonker: Yeah.  We have been very interested in this topic since 2018 and for already six years, we've been partnering with Professor Boon and her team at the University of Amsterdam to really understand the drivers and the blockers of people analytics adoption.  And we were really inspired, David, by other professions how they started to adopt data in their day-to-day work.  Think about Formula One, think about physicians, think about other sports, soccer for example, or football, I have to say now.  So, what we found is that there is a very clear flow for building a data culture in HR.  It starts with inspiration and simplicity.  And this leads to a feeling like, "Wow, this could be super-powerful, and I feel I can do this".  This leads to a feeling.   

So, then we need to talk about how to transform this feeling into an intention, and this comes along with capability building, seeing the personal potential of like, "Hey, if I master something like people analytics, it advances my personal career".  And also a subjective norm is really important.  It's a CHRO that says, "We are going to make incredibly important and complex decisions.  Bring data to the table to make sure that we make the right ones".  And only afterwards, after you've set the groundwork, then the external stimuli lead small pilots.  And then with governance, you scale from experiments to adoption.  So, there's a very clear flow.  And we actually use people analytics to understand the adoption of people analytics.  And what we found, with a lot of data and experiments that we ran on data, is that just having inspiration very, very loosely connects to organisational-wide adoption of building culture.  So, just talking about it is not going to cut it; correlation of 0.2. 

Just a super simple solution by itself also correlates incredibly low.  But the combination of inspiration and a simple solution increases the powers by 2.4X.  These are the multipliers.  And maybe some learnings for the listeners that I can share, that you can use tomorrow.  The first is that a successful adoption, again, is not determined by how advanced your solution is, but how easy it is perceived by the majority of HR and business users.  It is not about catering to the exceptions of the highly skilled people analytics teams that like to sometimes manage the exceptions, but get over it and think about how a solution empowers HR business partners right in the conversation with the business.  That's the first thing.   

The second thing, and we talked about this before, David, is that I wish more people analytics teams would think like a startup.  Why?  Because this is really still a developing field, where basically you develop product for a moving target.  So, imagine that you and I, David, are going to step out of people analytics and we're going to build a hotel.  We're going to open a super-cool hotel in the centre of London.  Of course, the hotel has a pool, and the temperature of the water is important.  But do we really need equipment from day one that measures it down to the fourth decimal place on how the temperature is?  And do we need to spend tons of time on policies on how to adjust the temperature for seasonal adjustments?  Maybe down the line, but for now, the guests just want a pleasant swim.   

Similarly, in people analytics, it's super tempting to get bogged down in perfecting every single detail.  But if you have a very technical, or too much enterprise-led approach, you will end up in a super-complex, expensive environment that no one really uses, you need a big team to manage, and at the end of the day your people are confused and you're not realising your goals. 

[0:19:42] David Green: Well, and I think one of the things that we see, again, maybe you talked about sometimes the people analytics teams themselves maybe want to do very sophisticated, more advanced analytics.  You talked about ONA at the start, and I still remember people would come and say, "I want to do ONA", and it's like, "What for?  What's the business problem you're trying to solve?"  We've got to connect what we're doing to actually real business problems that we can solve, because then we'll get buy-in of not just the business, but from our HR colleagues as well.  And that probably leads to the next topic, which is the thing that's on everyone's lips at the moment, artificial intelligence, generative AI.  How can HR professionals ensure that they are implementing ethical AI; and what should they look out for when purchasing AI tools, because it's a very confusing marketplace, I think, for buyers? 

[0:20:31] Dirk Jonker: It is.  I have a couple of thoughts on this.  So, first, I use personally ChatGPT in everything I do.  We have a private account, so nothing is shared, and we have all kinds of policies internally, what you can use and what you cannot use.  I incredibly believe in the power, and I can really see how this will impact your work, my work, the work of my colleagues and customers.  But we have to realise that generative AI, and especially solutions around this, are still very much in their infancy.  The technology is brand new, and it needs at least another 12 to 18 months more to become production-ready.   

One of the things, for example, and I talked about this at People Analytics World, is that the more instructions you put in place, the more personalisation, the longer it waits.  Many companies are now adopting a multi-agent model where basically all small AI agents, let's call it that, are communicating with each other to get a very transparent flow.  Well, this is all fantastic, but you as a user do not want to wait 35 seconds for your answer.  So, the technology is moving fast, but it needs another 12 to 18 months.  And what we also need to realise is that all these systems are going to be an extension of our brand, so we really do not want to rush this.  There was a very famous philosopher, his name is Eminem, and he said, "You've got one shot, one opportunity"!  And if generative AI is really an extension of your brand, it must follow your values and your ethics.   

One of the things that we really are building is a constitution, and this is a really cool topic or subject.  You can basically write down your values, write down what you find important, how you want AI to behave.  You can include some fantastic starting points from the United Nations, for example, of non-discriminatory, and we can now load this into our model.  So, we can give it also a face and behaviour.  On the other hand, I find it really interesting to think about the impact that generative AI also has on the work of HR.  So, for a long time, I was not entirely convinced, to be quite honest, that we should provide all kinds of data training to HR professionals.  Of course, an introduction course is fine, but many people in HR, they loved English and history at school and did not choose maths and science.  And I can see a world where generative AI is helping HR to ask the right questions to guide them through a consulting cycle, and that is exactly the approach that we're taking at Crunchr. 

So, what do we need from HR in the future then?  It's not about the transactional blah, blah, blah.  I mean, people can now use self-service to fill out forms, or whatever.  Is it analytics?  I don't know.  Product technology will do a lot, from servicing problems to providing the full picture of what's happening.  What we need to double down on, I believe, is how to translate these outcomes and drive actual change, so basically the HR as the people and culture consultant to the business.  This is really what I see ahead for a lot of people in people analytics, just like doctors or Formula One racers do not know how machine learning works, but they have embedded the output in their daily flow of work. 

[0:24:04] David Green: Yeah, I mean we talked quite a lot about productisation and democratisation in our episode four years ago, and maybe one of the things that we're seeing at Insight222 is that generative AI could democratise analytics even further, because as you said, it means that we've got to strike a balance obviously of people not necessarily having to be experts in data and analytics themselves to be able to use these tools, because that layer kind of does it.  But we've also got to be careful, I guess, from the ethical point of view, that people don't make the wrong interpretation when they haven't got the training to go and make decisions on it.  So, I guess that's the grey area and as you said, 12 to 18 months really to be production-ready perhaps, maybe it's training in ethics that people need, and what to look out for, what to maybe ask your people analytics team before you go and make a big decision.  I don't know, maybe it's a slight nuance to what we've been thinking about before. 

[0:25:09] Dirk Jonker: I mean, the decision-making, yes, for that you want to consult.  But do we have ethical guidelines for how to use Google?  Not really, right?  Is there a human in the middle?  Very popular term nowadays.  Listen, this is so perpendicular to the whole idea of productising technology.  There's no man in the middle for Google.  What you want is that if you ask Google a very offensive question, that Google says like, "Listen, David, I'm not going to get involved in this, it's not ethical", but this is where the constitution helps.  So, I think we need another year before the technology is fast enough, generalised enough.  The approach that we're taking is that we're going to launch it out of beta in two months.   

The first version of the AI assistant will go across all the data we have in Crunchr, so from financial to business to HR data, you can ask any question that you have.  But as you move to more automated decision-making, we have to be super, super-careful.  It's a violation of GDPR; it's a violation of the EO AI Act.  There, you want the man in the middle, but for the first part, let's make it as simple as possible and also use voice basically to have conversations. 

[0:26:34] David Green: Let's move to something again quite nicely tangential.  You mentioned EU legislation around AI.  In the article that I referred to at the start, and we talked about this as well, you talk about driving impactful and compliant Environmental, Social and Governance, or ESG as we all know it, tactics.  How does the new EU Corporate Sustainability Reporting Directive impact HR from your perspective? 

[0:27:53] Dirk Jonker: This is the only topic that really deeply worries me.  We are not making progress fast enough on ESG reporting.  The due date is coming up very quick and I really want to be clear with everyone on the call.  Almost all European companies with over 500 employees or more have to produce their first CSRD reports in seven months, which basically means you have to report on all the data that you had already been connecting since January this year.  This happening in seven months.  In eight months, you're going to work with your corporate auditors to validate your conclusions.  So, do you think a corporate auditor is going to certify basically a whole balance sheet in Excel or in Power BI?  Come on, forget it.  If you're saying that your accountant is going to build your ESG report, you need to find a second independent auditor who's going to audit your accounting.  So, it's going to be double cost.   

In nine months from now, you are going to be working with your executive board to craft a narrative and practice that Q&A for the capital markets day or their annual shareholder meetings.  And right now, you may for example think that adequate wage, some amount of work, we deem it immaterial.  Well, I cannot wait for your CEO to come to you and say, "Listen, at our capital market stage, we got so many questions on why we thought it was immaterial.  Are we trying to hide something?  Do we not think it's important?"  So, we have to realise this.  On the other hand, HR leaders that are listening to this podcast, realise that ESG reporting can be a tremendous catalyst for your workforce reporting and people analytics strategy and your foundation.  I mean, new legislation always gives tailwind, creates budgets that you never thought were possible before, budgets probably out of finance and not out of IT, and we're really sharing as much information as possible to help HR.   

We did a great session together, David, in January for your network.  We did a podcast with Ian Pinkett of Arcadis in April.  We developed a ready-to-go CSRD reporting template that you can just download, and you will hear a lot more from us.  But this is the only topic that gives me a bit of heartburn because it's not going fast enough, and in nine months' time, you'll wish you had started before. 

[0:30:26] David Green: And just to kind of crystallise, I think, am I right in saying that with the CSRD, each company, as you said, with more than 500 employees in Europe, and that includes American and British companies who happen to have 500 employees in the EU as well, doesn't it, as far as I'm aware -- 

[0:30:45] Dirk Jonker: This has changed a bit since the last time we spoke, but generally speaking, if you are a European-headquartered company with over 500 people, then you can bet that you're in scope.   

[0:30:59] David Green: And again, it's quite a lot of metrics, it's over 30 metrics, I think, that companies are going to have to publicly disclose; isn't that right?   

[0:31:08] Dirk Jonker: Yeah, and with that, there is 162 pages of guiding principles that you have to go through and that the auditors will go through.  So, we cannot get away anymore with like, "Oh, yeah, our headcount was more or less this", or, "Oh, yeah, we changed that definition in April and therefore the headcount is just slightly off, but they're actually correct".  Well, welcome to the world of auditors and finance.  Maybe in the first year they give you some slack, but every year after they're going to make annotations to your report and this is where you're going to get a very angry CFO. 

[0:31:48] David Green: Let's talk about the skills-based organisation.  So, again, when I go to conferences, I don't know if it's the same for you, I'd say the two topics that's on everyone's lips is AI and skills.  I feel that many struggle to get to grips.  Why do you think this is; and how can these companies overcome that? 

[0:32:07] Dirk Jonker: Yeah, let's start with a positive observation, and that is that we also see a lot of companies talking about skills.  And this again is a result of poor discussions around the future of work.  So, it is a signal that HR is getting deeper involved in business transformations, in the future of business, etc, so it's a really good thing.  And this of course leads to the question, what skills do we need; what skills do we have; etc?  And there are really, really cool companies.  We just launched a partnership with Techpool, for example, where we can now connect their data, their fantastic taxonomy to all the data that we collect in Crunchr, so that we can start answering questions in a heartbeat like, "What are the critical skills that we need?  Are we paying for the right skills?  The people that we just get on board, do they have the right skills?  Are we losing the people with the critical skills?  How does critical skills correlate to sales revenue?  I mean, it automatically snaps, so this is fantastic.   

But I'm with you that inferring skills from people and from positions is still a bit difficult.  I mean, these companies are making fantastic progress, but they need one critical ingredient, and that is a clean job taxonomy framework that basically organises all the jobs into families, into bigger families.  And to make this even better, you need very up-to-date job descriptions, so the LLMs can do their work. 

[0:33:38] David Green: Yeah. 

[0:33:39] Dirk Jonker: So, companies, they see the value of the pilots that they do, and they're now triggered to say like, "Listen, if we really want to scale this, then we have to improve our data quality extremely fast".  And this is, and I also spoke about this at People Analytics World, there are incredibly interesting open-source technologies that can help you to sanitise basically job titles, "I'm a sales manager, manager sales, MGR, SLS".  There are extremely elegant mathematics that you can just use, download off the shelf, that can help you to get to 70%.  This is what we like to do.  So, yes, it's becoming important, it's the future, I truly believe it, but it also shows that this foundation is incredibly important before we can get to these bells and whistles. 

[0:34:35] David Green: So, Dirk, if we were to sum up our conversation so far before we get to the question of the series, where do you see the future of people analytics? 

[0:34:47] Dirk Jonker: I hope that in, let's say, the next two or three years, HR is also part of any executive committee, just like the CFO, that the CHRO is then called the Chief People, Performance, and Culture, whatever.  I mean, "General Resources", give me a break!  The third thing is that we've realised that people analytics is a fantastic tool, but not an end goal.  Same with AI.  Now we talk all about gen AI, but it will become second nature.  And that we really focus on where we can move the needle within the first 12 months in frontline workers and middle management to drive transformation.  That is what I wish.   

[0:35:37] David Green: Okay.  Well, that's a good wish.  I think I share that with you, so that's certainly something we can talk about next time.  How can HR leaders use analytics to uncover and address inclusivity gaps? 

[0:35:50] Dirk Jonker: If you close your eyes and you picture yourself a line basically, on the left, we talk business; and as we move to the right, we talk HR.  And let's plot the employee life cycle on this line.  So, on the left, we have our business strategy.  We translate the business strategy into people, organisation, and culture requirements; then we get to recruiting.  We need to onboard them, we need to develop them, we need to pay them, we need to measure engagement, etc.  I believe that HR leaders can use analytics across the entire life cycle to really understand by call centre, by function, by leader, where the hot zone is where we need to do something, "In this country, we have this leader that tends to promote people differently, or where people do not get the right opportunities, or when in the engagement surveys, people talk about this topic".   

So, it's almost like what we do in Six Sigma is process variation.  We see the end result, very high variation at the end, but we need to go back to the root cause to see where the variation accelerates and starts in the beginning.  And that is for me, the full view of uncovering and addressing inclusivity gaps, using connected HR insights. 

[0:37:18] David Green: Thank you so much for joining me again on the Digital HR Leaders podcast.  And thanks obviously to Crunchr for sponsoring this series of the Digital HR Leaders podcast too.  So, Dirk, before we part ways, could you let listeners know how they can follow you on social media and find out more about the great work you and the team are doing at Crunchr? 

[0:37:38] Dirk Jonker: Yeah, I mean of course, LinkedIn, website.  We do a lot of inspiration and clarity workshops in many cities around the world.  It's free, it's super-cool, you can connect with people.  I think last year, we grew most in the US from word to mouth, so talk to other companies what they do, that's really important.  And we just don't want to become the biggest people analytics company, but we want to be simply the best.  And I think that's also quite nice song for my next article! 

[0:38:09] David Green: Well, you've managed to get a Tina Turner reference, an Eminem reference, and a Ted Lasso! 

[0:38:13] Dirk Jonker: Exactly! 

[0:38:14] David Green: We've got a lot of cultural references in here as well, Dirk, which is fantastic!  Thanks so much for being a guest on the show, and also for everything you do for the People Analytics community, you know, Crunchr's not just a great --  

[0:38:24] Dirk Jonker: I was about to congratulate and to thank you, David, because to whomever I speak with, they know your newsletter, they know your passion for the community and I mean your team is bringing everyone together, so thanks a lot, we need more of you. 

[0:38:41] David Green: Well, that's very kind, Dirk, and likewise to you.  There's a few of us in this space trying to push it forward, and you're definitely one of those people.  So, thank you very much.