Episode 39: How People Analytics Has Progressed in the Last 10 Years (Interview with Jeremy Shapiro)

The guest on this week’s podcast is Jeremy Shapiro, the Executive Director for Workforce Analytics at Merck. Jeremy is rightly considered as one of the most highly regarded and influential leaders in our field, and co-authored one of the first articles I ever read on People Analytics, the seminal Competing on Talent Analytics, with Tom Davenport and Jeannie Harris, which was published by the Harvard Business Review in October 2010.

With the 10th anniversary of the article approaching, Jeremy and I thought it would be neat to reflect on the last 10 years, assess the considerable progress the field has made and ponder what lay ahead.

This episode is recorded in two parts, part 1 was recorded before the COVID-19 pandemic spread across the world, and part 2 was recorded more recently in the midst of the crisis. You can listen below or by visiting the podcast website here.

In our conversation Jeremy and I discuss:

• How the workforce analytics team is organised at Merck and talk through examples of their work

• The New York strategic HR analytics meet up group that Jeremy co-founded and how this has helped foster a thriving people analytics community in the Big Apple

• Whether AI and automation is a threat or an opportunity for HR

• The work the team is doing around employee listening, both using active and passive data sources

• How the COVID-19 crisis is acting as an accelerant to digital transformation and the work of people analytics teams

• What the role of people analytics will be in the next normal

Support for this podcast is brought to you by Insight222. To learn more, visit https://www.insight222.com.

Interview Transcript 

David Green: Today, I am absolutely delighted to welcome Jeremy Shapiro, Executive Director of Workforce Analytics at Merck to The Digital HR Leaders Podcast. Thank you for shooting this in your office as well.

Welcome to the show, Jeremy. Please can you provide listeners with a quick introduction to you and your background and also your role at Merck and Co.

Jeremy Shapiro: So thanks for having me. I am now eight months tenured at Merck and Co, so for those of us in Europe it is known as MSD. So this is a 70,000 person company that is dedicated to the pharmaceutical industry. So its goal is to save and improve the lives of people and we also have an animals business as well.

I get to lead a very talented people analytics team here that has been established over the past decade or so in different iterations. So that is kind of my third chapter, right before this I was at Morgan Stanley for about eight years and started their analytics practice as well, inside of HR.

That is where I got into both the sustainability world and the external human capital disclosure world, or whatever size world that is. Then previous to that, I started my career at the Omnicom group, the multinational, multi-agency, agency group. Where I was running a P and L for them, I was building business that was HR related where I got to build some of the early machine learning algorithms that are there, text parsers, being able to understand what is going on, both from an applicant tracking standpoint with a company called Hodes IQ. Spent a little time at a company called Agency.com, that has celebrated their 25th anniversary.

So, I am feeling like, you know you have been around a little while, sometimes you learn something.

David Green: Well, you have certainly been in the workforce analytics space for a while and actually you were one of the first people that I came across when I got into this space. That was primarily through this seminal article that you co-authored with Tom Davenport and Jeannie Harris, Competing on Talent Analytics, in HBR back in 2010. We are now in 2020, this seems like a good opportunity to look back a little bit and actually look at some of your reflections over the last 10 years and the progress that we have made in the space.

Jeremy Shapiro: Yes, so if I think back to 10 years ago, it seemed like a good idea at the time to write about... analytics had just become mainstream in business parlance. Competing on Analytics, which Tom Davenport and Jeannie had written, was the number one selling book just a few a few years beforehand and so it felt like a good time to talk about the human capital angle. Looking at it 10 years later, I do wonder a couple of things. One is, we talked about a bunch of companies in the piece, how did they do if the assertion was that people analytics can create competitive advantage?

Okay, so now, Jeremy you sucker, you actually got to live through those 10 years. So what actually happened? I have not opened this article in a while, so I opened it up, I looked at the companies that are mentioned and I have to say if I were to compare the performance of the S&P 500 to the companies mentioned, we might just match the S&P 500 and that is only because of one over performer that was on the list.

So several companies do not exist anymore either. The lens for me is one, is people analytics something that creates competitive advantage for a company and I think where my head is at on that is it might be necessary, but it certainly is not sufficient to create competitive advantage for a company, that is not a great revelation.

Then the question is, 10 years ago we asked a bunch of questions. We ask questions about, how would you approach data in an analytics capacity inside of HR? What kind of people questions would you ask? Those kind of held up, if we want to try to predict attrition, not my favourite analysis but it was in there, those are questions that you hear today as well. I think what does not really hold up so well if you were to rewrite it today, the entire body of knowledge of machine learning, of process automation, and that is not a surprise you have been talking about this for 9 years, but the acceleration inside of HR that has created, that is the missing story. That is the story of where analytics is, I think, becoming more and more of a necessity is because not one of us can keep up with the pace of change. So that acceleration is to me, something that was really, really unexpected and I think for many of us, but that is the one where my head has been going more and more lately.

David Green:  Yes and a couple of things that kind of struck me was you actually mentioned a couple of those organisations either are not here anymore or they have certainly not outwardly sustained their capability in people analytics. I wonder if that is partly because there is this challenge around up-skilling HR and you can have a great people analytics leader, a great team, but if you do not create that sustainable capability by enabling the rest of HR. If that person is pulled away to another company, as a result of being in a great article maybe, and takes a couple of their team with them, then it can all fall down.

I do not know the inner workings of some of those organisations, but I sense that could be one of the reasons why that might have happened.

Jeremy Shapiro: Well, I think you are right and I can imagine that anything that is new is temporary, until it becomes more permanent. Even thoughts of employee self service, just because employee self service was available in an older HRIS does not mean that people automatically turned it on and that it became the fabric of the work itself. I think today things that are settled work become settled work. So employee self service or analytics have become a mainstay inside of many organisations, certainly not all too. But the longer we go down this road, the more it just becomes part of the fabric. I suspect that the personality led era is largely over and it is now, what is the business reason for investing in this way?

David Green: You mentioned as well the introduction of machine learning since 2010 and we are seeing that a lot more in HR now. Has that helped move the function from maybe the periphery of HR, doing some core projects, to actually the centre and almost mainstream in HR now because of the whole development of products that actually support career pathways. That actually support workforce planning and all these other important things. As you said, things are moving so fast now, we need to bring data to that conversation.

Jeremy Shapiro: I think on our best days, that is what happens. To the promise of AI, the promise of machine learning and the reality of the day to day when you are in the code and you are trying to solve a problem.

The difference between getting a result and actually being accurate and appropriately characterising what is going on is pretty big still. As we are talking with wonderfully talented partners on the outside or someone that has a great startup idea, we constantly challenge where is the state of the art in whatever their technology is, whatever the machine learning is and is it ready for prime time? Even when we are building applications here, whether it is truly an application or just a script or even a methodology, we think about it in terms of an experiment. After a series of experiments become stable, we consider that to be a product.

So those products have features to them, but it is only when they are ready for prime time that they can really be used in a large scale way.

David Green: So let's say Harvard Business Review get in touch with you again, they would love you, Tom and Jeannie to write a follow up article to this, looking forward to the 2020s. What are some of the additional things that you have not already mentioned that you would bring into that piece?

Jeremy Shapiro: So I think that I would probably want to write about the singular moments when leaders, whether they happen to be HR leaders or happen to be business leaders, have a critical decision to make.

What was the data analysis insight or analytic behind it that helped them get to that point. I would love to interview 20 or 30 senior leaders like that and really get to the core of, this is a time when it was helpful. I would interview a bunch more people and say, here is a time when it was not helpful at all and you really missed the mark.

Largely if you are not process automating something and you are not creating a scalable solution, there is a fair amount of people analytics work that is still influence based. I am trying to understand an insight, I am trying to understand a result, because I want to influence an important decision. How does it really work and what is the right level of effort that you need to apply in order to create the effect that you are looking for.

David Green: Good, I hope they do get in touch with you to do that. So moving on a bit, I know I was always intrigued when I have seen you speaking before about the importance of storytelling, I know recently you have been talking a lot more around the role of empathy and analytics. Why is this and what is the relationship between the two?

Jeremy Shapiro: Empathy is an interesting angle for an analytics professional. So I started to explore this just just a little bit, particularly as I was training up new staff and trying to help tune teams to understanding business problems and understanding the results that they are finding, tying the results set to the business problem and in driving insight.

What I realised as I was doing this over and over again, is that the thing that was not connecting was an empathetic response. What I mean by that is, we as human capital analytics practitioners, can we put ourselves in someone else's shoes, so that is cognitive empathy and try to understand what position are they in?

What problem are they dealing with? Maybe even sometimes, what meeting they just came from as well. So it is frequently the case that one of us may go into an executive's office and that will be absolutely the biggest meeting that we have today, it is not the biggest meeting they had.

They had a very different day than what we are having. Just really understanding where you are in your role, how you are trying to help someone else, takes a degree of empathy.

Now there is a different lens of empathy as well that is an emotional connection.

I find this really helpful no matter where we are talking about in the analytics framework and working with analytics teams. If I happen to be a data scientist, I actively want our data scientists to be really thinking about the data, which is about people, that they are working with. So every single one of their data points has a mum has a dad, has a family, has motivations, has a career goal in place. If we are not paying respect to our employees, we are not doing justice to the organisation, to the employee base and honestly most of the time you do not get the analytics right either. So to use that framework to try to express how we can storytell better and one of the easiest ways to express this is in that final layer when you are trying to build a deck for a bespoke piece of work to someone senior. You have heard this I am sure, in your interviews, the importance of adding context to whatever analysis is being presented.

Well, it is much easier to think about context if you use an empathetic point of view. If I am really focused in on that end user, I might read something and say, the R squared value is 0.62 and we find that to be credible, can I buy a vowel? The person that you are expressing this to might not be statistically literate, might not have the context to know why you, who naturally thought that was a no brainer, might actually be something that you would want to explain.

So how do you help to connect the dots between the point you are trying to make and the person you are trying to make it to? So far it has been quite helpful as a technique.

David Green: It makes perfect sense and I love the way it combines the angle with the ethics part as well, thinking about the end user. But for the story telling part, it effectively means that if you really think about it, you are going to position the findings or insights very differently to different stakeholders because ultimately you want an emotional connection from them. If you think about what is going to drive that, then that will make you tell that story maybe in a different way.

The facts are the same but you would just present it to them in a different way.

Jeremy Shapiro: You know, you bring up an interesting point. So we are training a series of cohorts right now. It is being led out of a, we have an innovation lab that is not an HR innovation lab, that is training a set of speaker trainers across Merck, to help scientists and other subject matter experts to present their findings either internally or at events. One of the key groundings that we are using are Ted talks as well, which have a methodology that prescriptively talk about building emotional connections, attaching data to the emotional connection to drive an outcome in itself. I think you are totally right that there is a method to that particular madness that creates an impact.

David Green: So turning to your role at Merck, how is the workforce analytics team organised and how does the team interact with the key stakeholders in the business and HR?

Jeremy Shapiro: We have got a wonderful team and it is roughly split into two types of functions. So one is as an internal consultant function. So these are generally pretty senior folks, they are either industrial psychologists, they are economists who are very good at tying up problems to research, working to conduct the research and then working to influence the decision making process. We also have our product teams as well, so we do have some dual hatting, where a senior person may own a product and also cover an area.

The key areas that we think about right now are one, insights at scale. Our technical stack is Workday, it is not even a year old yet, so a new deployment of Workday, Workhuman is our recognition engine we have Visier lying on top of that. So the team that works on insights at scale really focuses in on, how do you get the basics out? Increasingly we are working on the idea of getting the right data at the right time, using a tool like Visier to ensure that HR business partners and others can segment the data easily and simply and understand the story moments before walking in to a meeting. So that is the first tranche. We are standing up an employee listening strategy as well, so making that transition that many have from surveys to a more fulsome approach. We are standing up right now a formalised data science unit, Bennet has now joined the team so he is leading that up for us and we are very happy to see a very fast progress there as well. Then we continuously are looking at workforce planning and organisational structure and design and so forth and what is the role of analytics in those areas?

David Green: And it is quite interesting, you mentioned that there has been a team here for over 10 years, and it is interesting that all of those specialities are coming under the people analytics hat. I think that is a sign of a reasonably mature function.

Jeremy Shapiro: Well, I think yes and it is because we reinvent all the time. I think many of us do inside of companies, the special challenge for us is asking ourselves, would we do it that way today? Which is a common cultural question that you would want to ask anyway too, but it is also important for us to make sure that our assumptions are constantly challenged and understanding where we are at and where we want to be.

David Green: So again, looking at the work at Merck that you are doing, is there an example of a project that you can share with listeners?

Jeremy Shapiro: Yes, so as of late, I think as many companies are going through transformations as we talked about, acceleration, one of the ways in which we are accelerating learning and accelerating the speed of decision making is something that we have nicknamed internally, ways of working. It is a good catchphrase for us to work through. What is interesting is that the ways of working that we have defined working with our employees about, was fully derived from our voice survey itself. In using the voice survey, we were able to create more precise messaging and really target areas that both resonated for our employees and also drove the types of actions that we are hoping for as well. So it really is a testament to a wonderfully strong survey team on our side and some great thinking but then also the motivation of the executive team to say, this is where we would like to go so let's make sure that we are expressing this in a way that resonates. We are still mid-story for it, but it is a great linkage of an analytics project, organisational priority and then formed into impact within a pretty short period of time.

David Green: And of course that is so important because you see so many of these projects happen and then no action happens and that is frustrating, I guess, for the people contributing.

Jeremy Shapiro: It is interesting you say that, because we talk about that a lot. So I do take a longer view of project work and so there are some things that we do that are relatively quick service, so if there is a natural disaster that may be impacting our employees, we get quick data to our senior leaders right away. Here is a map of what is going on and here is the path of a hurricane, those things are pretty quick. There are some other topics like this that take such a long burn rate that, I tend to stay optimistic, that if we do not yield a result in the time in which we expected there is one of two issues there. One is my expectations were too high on when it was going to occur or I was not influential enough to try to get it done when it needs to get done. If you use a sufficiently long time horizon however, it really does help, particularly with motivation and keeping the projects going.

David Green: Great. Well, it would be interesting again, next time we speak to see how that evolves moving forward.

You have given a lot to the community, you set up the New York strategic HR analytics meet-up group a few years ago now, and I had the pleasure of coming along to a couple of the meetings. Stela Lupushor one of your co- organisers, we had her as a guest on a previous episode of the show and she told us all about it. But what I was wondering from your perspective as an analytics professional or analytics leader now, what makes the group so special, firstly, but also how important is collaboration to the analytics community?

Jeremy Shapiro: Yes, thank you for saying that. I will say that the story of how it started was a lunch where someone new to the analytics community said, could you set me up with contacts for another 10 or 15 people to have similar lunches? And I think the conversation went something like, I am not sure I can do that, but I could fill out this form on meetup.com, it was that type of thing. And Stela coming in, everything revolves, not surprisingly around Insight222, Jonathan Ferrar actually introduced me to Stela as well. She is an amazing partner and thinker and in so many different ways. What is so interesting to me about how it has grown over the past few years, is that analytics in HR in companies can be a lone task. Even with all of the technology and ways in which we can connect and using LinkedIn to broadcast the conferences that you can not get to. All that being said, there is something about sitting down with friends and peers over a couple of hours, maybe sharing an adult beverage and talking about what is going on with their organisation that has been resonating.

I have heard there are like 10 or 12 meet-ups that are using the model around the world as well, so Stela and I will sometimes get emails from relatively smaller organisations or from countries that we would not have expected where they just held their first meet-up as well.

The conversation that we have at these meet-ups definitely is proof that, if you are in this particular area, if you are in analytics, you want to talk and you want to network. The value to me and I think to a lot of folks is that acceleration problem, that if you know that the pace of learning is no longer linear, you better have a bunch of friends. You need people that you can work with in order to stay on top of what is happening next. Because the next conference that comes up, there is a whole new stage of thought that you have to absorb incredibly quickly. It is not just us, It is not just in HR, in the medical community you see the same thing going on where the pace of change is now non linear that is causing all organisations to think of ways to learn faster and more with greater agility as well.

David Green: Well that brings us to the last question, which is one we are asking everyone on the show. AI and automation, do you see them as an opportunity or a threat to HR?

Jeremy Shapiro: Absolutely an opportunity, what a surprise that I would say that. But it is the thing that I think is the most exciting about HR is talk about thinking through talent strategy in itself. So if we are thinking about leveraging a workforce and the old adage of am I building, am I buying or am I borrowing?

Well now I can add to it and I can add, am I using a bot? Now I can add to it. Is this going to be a gig as well? Just that element alone of talent strategy is energising to me and I think it is really catching fire in so many different ways. The opportunities that people have today to accelerate their learning inside of HR and to help counsel our teams on the impact of machine learning to improve their own lives, I think is incredibly important.

David Green:  Perfect. Great answer.

Well, that is part one of the podcast, which I hope you enjoyed. Part two focuses on the COVID-19 crisis. Jeremy and I discuss how people analytics is helping Merck and Co respond to the crisis.

We talk about the work the team is doing around employee listening, both using active and passive data sources. We also look at how the crisis is acting as an accelerant to digital transformation and the work of people analytics teams. We also ponder what the role of people analytics will be in the next normal. Enjoy part two.

Well, Jeremy, it is great to see you and a lot has happened since we sat down just over three months ago, I think it was the start of February, to record a podcast episode. We both felt that we wanted to talk about the crisis together. What has changed over the past few months for you and your team and how has analytics supported the company at Merck?

Jeremy Shapiro: Thank you David. It is nice to see you and I hope you are staying healthy and for everyone that is listening as well, I am sending best wishes from here in New Jersey. So it might be helpful, it has been only three months so just to anchor us in time, depending on when you listen to this, we are recording this about mid May. I am looking at the Johns Hopkins dashboard, roughly 4.2 million people around the world have at least been actively diagnosed with COVID-19, almost 300,000 have unfortunately passed away from this illness. What is so interesting is even day by day, week by week the response has changed, thinking has changed and this kind of accelerated thinking certainly has gone through. Look for us at Merck, in the HR analytics team, I could not be prouder of them. I think they have done a remarkable job, transitioning quickly from an in person culture to a virtual culture. We were about 50% before and now we are a hundred percent. What is so interesting is for those of the team, and I think this is true for a lot of us that were physically close, we are now physically distant but I think in many ways we are closer. Because we see each other so much now on video and are able to check in with each other on a daily basis as well.

So I think that is the first tranche, is the differentiation between physical distance and the connection that we have, the connectedness that we all have together. I have certainly seen you more in the past few weeks.

The second is probably focus, how we have focused time and how HR has focused time in such an important way to help protect our employees' wellbeing, to ensure the supply chain for the organisation has certainly been different. And this word that we have heard so much of, acceleration, I know we are not alone in this too. In times like this, decision making can be accelerated, assumptions can be challenged and it changes the way that we can work in ways to the benefit.

David Green: Yes I know we have spoken outside of these podcasts as well, and I know one of the things that there is that real emphasis on wellbeing, and it is kind of that shift from engagement, there is a whole rally around the flag concept, in times of crisis but I think wellbeing is really where we are trying to understand and we are going to talk a little bit about that later.

How are you and your team spending your time right now? Obviously not together, but what are some of the things that you are being involved in?

Jeremy Shapiro: So particularly in response to the crisis, I think a lot of people analytics teams around the world have tried to provide data and ground decision-making in the best intelligence available. Certainly the Johns Hopkins database, whomever is hosting that database wins the A plus award for availability as well.

But one of the nice things about the times we live in is we can incorporate public data into corporate data in such a rapid scale. One of the things that we were able to produce rather quickly was an executive level dashboard that merged the public data with sets of internal data as well to help manage what is the state of every single one of our facilities, where are our employees and incorporates badging data, incorporates HIPAA compliant information so that we can understand patterns of employee quarantine so it really helped drive productive conversations with teams as well. I can just imagine in times when we did not have information, even if the information is not always in real time, being able to drive decisioning based on patterns is incredibly helpful, to have that level of intelligence, to have that level of business intelligence and to have that level of transparency so that we can have conversations with employees, we can have conversations across all of our 71,000 members.

David Green: I think it has been good to see that data really is coming to the fore with this, not just inside companies but we have seen a lot of government decisions in different countries, we do not necessarily need to get in to individual countries otherwise we could be here all day.

But we have seen that most countries around the world are basing their decisions as we move through this crisis on data and science and that seems to be the same in organisations, particularly those that have invested in the people analytics teams and those people analytics teams have developed that stakeholder equity already within their respective organisations.

Jeremy Shapiro: Yes, yes. You know what is interesting to this situation, is it is not one instance, so depending on where we are in the world it manifests differently, we are in different stages everywhere. From an organisational standpoint, it also asks us within HR to drive decision rights into appropriate spots around the world.

It is only in the country that you really understand the dynamics of what is going on, the specific regulations inside of the country too. So the logistical challenge of driving decision making through data in multiple channels and then getting that into the best hands that can make the right decision for employees based on what our priorities are. I have been spending so much of my time thinking about how we spend our time and I have tried to rank our priorities as where you have discretionary time as an analytics team, working on topics that benefit our employees to keep them safe, healthy, that is number one. If you have a choice, that is where you spend it.

The next tranche is in critical operations and supply chain. Let us help ensure that if we can detect something that we can pass the messaging along and make sure that they are okay and then we move into regular operations.

David Green: I think it is good to see that focus really and we talk a lot about people data being used for good and ultimately I think that is something that will help the field continue to progress. Yes we want to help executives make better decisions, but we also want to provide value to employees, it is their data that they are providing after all.

That leads on quite nicely. In the opening question you talked about wellbeing. Now what are the sorts of work that your team is doing around employee listening of what is your newly remote workforce and are you using active and passive data sources too to do that?

Jeremy Shapiro: I could not be prouder of our team. So, Juran Hulin, who runs that team for us, is a very, very sophisticated thinker in these areas. So what we have done is incorporated both a weekly question-based pushes of data, that actually serve two purposes for us. One is it helps us get some intel and information, but in times like this sometimes asking a question can also send a message too. So by asking a single focus question. How are you fairing and what has benefited you the most? It also does project something that I truly feel, which is we want to know that you are benefiting and that you are okay in doing that too.

So where we can both incorporate listening with messaging, we find that to be quite helpful.

We do look as well in a very appropriate way at our internal social channels and where we can pick up patterns, we do and then we try to help unlock any roadblocks.

So we have found an instance where there was a technology issue in one part of the world, it seems like it was not detected as well, so we were able to get that messaging to help to unlock value. Or even just to talk to senior leadership and help them really understand the extent to which the crisis is being talked about and in particular in a company that is a focal point for medicines, particularly vaccines as well, you would expect that would be highly engaged in this topic and we are highly engaged in this topic. Particularly content that seems to get a lot of reactions on include our own employees that have taken themselves offline from their day jobs and volunteered either in a hospital or in a clinical setting of some sort. One of the underreported facts inside of pharmaceutical companies is we have a lot of medical doctors and we have a lot of nurses at work inside of the organisation and so when this happens, there has been multiple stories and instances of folks just saying, Hey, look, I need volunteer time. I am heading to the hospital.

David Green: It is interesting as doing the passive analysis or the passive listening, helps you to identify issues that you might not otherwise pick up from active surveys and also highlights things that you might want to ask deeper questions on through the next survey or something. So the two really do flow together.

Jeremy Shapiro: They do and I think everyone is learning how to listen more deeply to thousands of voices as well and doing that in a way that is appropriate and that is comfortable and that is with the intent of help. That is the critical path for me to make sure that we are moving the company forward.

David Green: Okay. Well you talked about it earlier, but we have been hearing a lot about COVID-19 as an accelerant to digital transformation and the future of work, almost like an accelerant or a catalyst really. What do you think has changed for organisations and specifically the work of people analytics teams?

Jeremy Shapiro:  I have noticed that this era has been a time of challenging assumptions and then essentially having necessity drive some types of innovation.

So on the challenging assumptions notion, HR organisations around the world and it is so wonderful that as a discipline I have noticed more collaboration across HR organisations in public forums to just get the messaging out of what are you doing? How are you thinking about that?

Ideas for big box retail we can use inside of a corporate setting and back and forth so quickly. So this idea of challenging assumptions becomes absolutely critical. Where before there was maybe a hiring manager who would have said there is no way this individual, a new hire, could do that job unless they were in a specific location.

So now let us evaluate that and really understand was it true? Did I need to be physically there to do that role? And I think for many types of roles, we are seeing that of course that assumption can be challenged and that what we can open up in terms of our labour pool and talent pools to find the best talent around the world that can do a specific role or lead in a specific way, why wouldn't that be part of what we incorporate.

It is so interesting in the downtime when we are not working and certainly watching enough Hulu and Amazon Prime to see the commercials too, and the number of commercials for Slack and Microsoft teams is just astronomical. Because it certainly is the moment in which collaborative software seems to be the case and I do hope that the ideas in collaboration for those that were not already on some type of collaborative tool canuse that as they go forward.

It focuses me on a question and that question is, even though this is a difficult time, are there aspects that we wish to keep afterwards? I think it is important for all of us to articulate what that might be now because as we all hope the era subsides and that we can return to more of a daily routine, we will normalise to that too.

So by asking ourselves the question, what do we get to keep now we can help to lock in a few benefits out of not a great situation that we would like to see in the future.

David Green: It would obviously be people analytics teams that will be measuring the effectiveness or otherwise of these.There has been reasonable steady growth in use of passive network analytics over the last few years and I know some companies are doing more of that than others, but with the growth in Teams and the growth in Slack, the growth in the use of Zoom as well as all the emails we get every day, we can understand a lot around communication patterns and burnout, isolation, collaboration, all those sorts of things.

So I think that give me some interesting work we will be doing in the future. That will support our work at workforce planning and workforce location planning as well in the future.

Jeremy Shapiro: Absolutely and not to endorse any specific platform on this, but I have been thinking much more lately about, who is that analytics for?

So if you are using Slack, if you are using Teams or any of those tools it is wonderful that some of those personal statistics and that personal data is made available to me as a direct contributor or as a leader so that I can see the results of some of my actions. The number of collaborations I have does not tell me about the quality of collaboration, certainly. I would take one great idea and that was my only collaboration of the day versus 20 that were not so great. The degree to which we can unlock the data for employees so that they can experience it for themselves, not for judgement and not for evaluative purposes, but for themselves.

What a great benefit. Some will take that up, some may not, and that is great too. But if you can take it up and absorb that and use it for yourself, I think this is just a wonderful new opportunity.

David Green: It is certainly going to be interesting and that leads quite nicely onto my next question. When we sat down at the start of February, it does seem a long time ago and it really was not, we spoke about the role of empathy in analytics. What has COVID-19 taught you about analytics and empathy together?

Jeremy Shapiro: So what is so interesting on empathy in this era is, I have been thinking a lot about great leadership and the times in which our leaders are really connecting with our employees and the times in which externally so, on LinkedIn you will see leaders posting messages that are kind of for employees, but are posted on LinkedIn too. It made me look at the qualities that we use in industrial psychology and assess, what does great leadership look like in the time of COVID? I think what my hypothesis is right now, that I hope we will test shortly, is it looks a lot like great leadership did beforehand too. Great leadership is vulnerable, great leadership is transparent, its frequency and dependability are high working in that way. So just because we happen to be projecting that leadership through, for many folks if you are working physically then you are working physically, for others you may be projecting that leadership through a small square on a computer screen as well.

But that medium, of the small square on the computer screen, it does not change how we should think about the analytics work. It should not affect us as leaders on how we try to inspire others.

Those kinds of components, I think, have a large impact on leadership assessment. How we are thinking about inspiring, directing and goal setting and all of the different wonderful ways in which world-class leadership manifests. That is just as important today, more important in some ways than it has been beforehand. This is the stuff that we all know, we have spoken about it on so many occasions.

That is just part and parcel of great leaders working today. It does not cost us one word dollar to project empathy and then look at what the effect of that is as well, this is certainly a time where it is valued.

David Green: And I think what we need to do be doing more of in analytics as a whole, as a field really is actually showing the value of empathy to employees, but also to the business. I guess it is easy to look at the political leaders around the world and we are not going to talk about any individuals, but I think what is clear is you are right, the same leadership qualities that have always been important are maybe more important in a crisis. But I think what it is doing is it is exposing some of those people that maybe do not have some of those skills and I think empathy is one of them. I think it can not be a coincidence, granted it is a small data set unfortunately, but a lot of the female leaders around the world are a perceived to have done a really good job during this crisis whereas the ones who are, let just say who appear to be the less empathetic political leaders, seem to be doing not such a good job. Maybe that will help us in businesses as well, when we come to choosing our leaders and seeing the ones that really add value both to the business but also to the workforce as well.

I think this is a topic that we will be talking a lot more about in the coming years.

From speaking to many of your peers, as we both are as part of the work we do at Insight222, but also others outside of that it is clear that people analytics teams like yours at Mercks have been in the spotlight in response to the crisis. Do you think people analytics will continue this trend as we emerge into the next normal?

Jeremy Shapiro: I think that our goals inside of a Human Resources function of data driven decision making, it has not changed. For those of us that are lucky enough to work with leaders on data driven decision making, that is not going to change either.

The crisis is certainly dramatic and many, many organisations in so many different ways stepped up to the challenge of the crisis itself. For any function, our goal is to be decision useful fit for the time in which we are living. So the lesson that I hope we learn from all of this is not, isn't people analytics so valuable, shouldn't you use more of it? I hope the lesson that we learn is that strategic decision making will continue to have an enormous talent component to it and that enormous talent component can have value added through natural data, natural insights that can be provided along the way.

I was just listening to something where they were observing, actually I am going to cite you, in your last podcast when are you talking about Davos. If the increase in the number of CHROs attending Davos is on the increase, then that is a signal of, at least on the international stage, something that has always been known inside of corporations of the strategic importance and value of human capital. That will just accrue over time as well. So this might be an instigating event, it certainly does not have to be, but the things that we have under our control as HR leaders is can we enable this trend? Can we enable better decision making through maybe that one insight, that one data of an insight that is just going to accelerate us further?

That is the promise and hope that I am routing for.

David Green: Well, hopefully we will find out sooner rather than later. I think this crisis is set to continue for the foreseeable future, but, we will be seeing each other like this for a while yet I think Jeremy.

Thank you so much for joining the show again.

How can listeners keep in touch with you and follow you on social media?

Jeremy Shapiro: So please, LinkedIn is probably my most expedient. We do have a Slack channel that we use for that New York analytics meet-up which is there. But I listen to both so please, anytime, particularly in times like this, we are all supporting each other. So we are here for each other.

David Green: Well, thank you for continuing to do what you do, Jeremy. I know you have been pretty visible during this crisis, joining some of the other public forums as well and I think people value your input.

You have been in this space for a long time and you are one of the most respected leaders in it, deservedly so. Also thank you for the nice shout out for the podcast. Just for those of you listening, if you want to find the one that Jeremy was referring to, it is from Ravin Jesuthasan and it is around the work that he did with The World Economic Forum on some of the future skills required in HR.

Jeremy, it was a pleasure as always. Thank you very much.

Jeremy Shapiro: Thank you for having me.