To build sustainable success in people analytics, you need a few key ingredients. Let's look at three. First, align the work of the people analytics team to the business strategy and priorities. Second in parallel, be intentional about building analytical capability across the wider HR function and third, get the sponsorship from the Chief Human Resources Officer, the Global HR Leadership Team and Senior Leaders in the business.

My guest on this episode of the podcast has mixed all of these ingredients and more since founding the people analytics team at Merck, in 2016. Alexis Saussinan is the Group Head of People Data and Technology, and the function he has built has become a bedrock of Merck's people strategy and consistently delivers value to the business and the global workforce at Merck.

Alexis and I reflect on the journey of people analytics over the last five years at Merck and look forward to the future as Alexis' role has expanded to bring people data, analytics and technology together.

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.

In our discussion, Alexis and I discuss:

• How to align the work of the people analytics team with the business and the people strategy

• Examples of people analytics in action, including how Merck takes a skills-based approach to workforce planning

• The size, structure and skills of the people analytics team and how it has evolved over the last five years at Merck

• How a combination of CHRO sponsorship, ambassador networks, rotational programs and effective communication combined to help grow a data-driven culture

• Why bringing people data, analytics and technology together enables the next wave of HR transformation

This episode is a must listen for anyone interested or involved in creating business value and employee experience from people analytics, in parallel with increasing HR capability in data and digital.

So that is Business Leaders, Chief HR Officers, Chief Learning Officers and anyone in a people analytics, learning, HR leadership or HR business partner role.

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

Interview Transcript

David Green: Today I am delighted to welcome Alexis Saussinan, Group Head of People Data and Technology at Merck, to The Digital HR Leaders podcast. Alexis, it is wonderful to have you on the show. We speak quite often, I know who you are, but can you provide listeners with a brief introduction to your background and role at Merck?

Alexis Saussinan: Sure David and thanks very much for having me. So I am Alexis. I work at Merck Group and today I head the People Data and Technology Unit. I am based in Asia and I have been based in Asia for the last 10 years. I manage a global team spread across Asia, Europe and the US, looking after our Digital HR and Data transformation. I actually joined Merck five years ago where I was hired to build a people analytics team, pretty much from scratch and we have gone quite some way to where we are today.

David Green: Brilliant and we are going to hear a lot about that over the next 40/45 minutes or so. And technology is wonderful, I am speaking to you from a very snowbound UK at the moment, no doubt it is not snowing in Singapore.

As you said, Alexis, you came into Merck five years ago to found the people analytics function, so you are one of those people that I know that actually have founded a function within a company. Since then you have developed and scaled it into one of the world's leading functions, certainly in my opinion, and always with a focus on delivering value. What have been some of the key milestones along that journey?

Alexis Saussinan: It has been quite a journey, indeed. When we started, there were basically a couple of us starting the function and really trying to get into raising awareness of how people analytics can deliver value to the business and to Merck as a company.

So at the very beginning, when we started, we did quite some work on our data. Making sure that we can have a really good base of our data, harmonise data, work on quality and make sure that we can hit people analytics at a global level, which is the first milestone that we got into. We actually put together a global people analytics platform that was covering insights, basically from pre hire to retire, that we have been using all the time. When we initially launched this global people analytics platform, we actually decided to make it available in a very democratised manner in the sense that we not only opened it to everybody in HR, but also to every Senior Business Leader. Where everybody could access their own insights across the whole Merck group, of course with the right level of privacy in there, but a very strong bold move, I would say to go for data democratisation. From there, it has really been a journey around showing the value of people analytics and insights to the business. Working with a number of HR Leaders and Business Leaders on strategic use cases around sales, production and manufacturing, really showing how much value these insights can help to empower Leaders to make more strategic people decisions. That is something that we have been working on over the last few years to really drive awareness, but also adoption and being able to ensure that the way we look at people decisions at Merck become really data-driven, in order to make the right strategic people decision. Then over time, that awareness and that option grew actually and we had a few milestones, very important ones, such as working on some group level, very strategic projects around diversity for example, and sort of strategic topics at a group level. We also had a key milestone where we were able to showcase Merck’s people analytics capabilities to The Global Executive Forum, so to all of the top 3/400 Leaders globally to really again, open the eyes of the Business Leaders when it comes to what value can be delivered from people analytics.

Then we also got into more complex analytics, bringing in a small data science team, working together with the rest of Merck’s data science network to engage into more predictive analytics, go into more complex and value adding type of people analytics, to increase the type of insights that we could deliver.

And today, as you said David, since the beginning of this year actually we have decided to expand the scope further to not only bring the data analytics together on the people side, but also to add the technology. To combine people data and technology to deliver on that strategic priority, which is around accelerating our HR digital and data transformation very much in line with what the group is pursuing, to become a vibrant science and technology company. So it has been quite a journey, very exciting.

David Green: Yeah and it is clear how well aligned the work you are doing and the way you have set yourself up, is to the business strategy. There were a couple of things I would like to dig into there, but I love what you said there about, we worked on strategic use cases around sales, production and manufacturing. You would be surprised the amount of time I speak to other people in similar roles and they say, we worked on attrition, we worked on learning and they say HR things. So I think that a real feature of the work you are doing is it is very much business focused.

One of the other things I think we can dig into a little bit is, when you said that the data science team worked with other data scientists across the business, they weren't just in isolation in HR. Obviously you have to start small with a data science team, with one or two people, and the importance of connecting them to other data scientists in the organisation means you have got access to skills, technology and resources, but you work together to solve business problems.

Alexis Saussinan: Absolutely, David. And of course the topics you mentioned around attrition, learning, diversity, are very emotional topics that we have been touching on but, as you said, always with a very strong business focus. At Merck, one of the ways we do that is we operate a pretty robust portfolio management approach to make sure that we are spending our resources and our efforts on the so called “must win” areas. I think we are quite clear and we became clear over time, that we cannot win everywhere and it is really about identifying areas where we can build as a company, a competitive advantage and to really prioritise on these items.

David Green: Yes, because you can't do everything and it is easy to get lost in stuff that actually isn't that important to the business. Requests for data, pet projects from Senior Leaders and stuff like that.

So you mentioned that you are based in Asia, but you run a global team and obviously that team has grown with the additional responsibility you have got. How is the team structured currently?

Alexis Saussinan: So currently, as I mentioned just before, we have part of the team that is looking at portfolio management, we are making sure that we put our efforts in to the right strategic priorities and constantly review the impact and the value add of the portfolio initiatives that we are running. Very much in line with our global HR portfolio management initiates and very strong collaboration with my peers in HR and in the business. We have another area that is, to a certain extent, an HR data office. We really want to continue and improve our capabilities around data governance, data quality management, data privacy management, which is a key topic as well and making sure that we have the right data and we are able to access the data faster and in a better quality. Not only in HR but also connect this data to broader data catalogues, that can be accessible across the organisation.

Next to this data office we have a small people data science team, that I mentioned earlier, looking into more of these advanced analytics type of techniques and deliver more advanced use cases.

We have a digital HR, UX and enablement pillar that looks at the whole data and technology landscape as a big picture, in its totality. We want to make sure that we deliver data and technology based people solutions that create high business impact, but also best in class for employee experience.

And to do that you really have to have that big picture in mind, of how to operate with the end user in mind all the time. Running next to this digital HR UX enablement pillar are, let's say, more “specialty areas” on data and technology that are looking at specific pieces of our ecosystem. For example, analytics for our core employee lifecycle our future workforce, or our cognitive and digital assistants, which is also an area where we want to continue to develop in the future to further the size of our people solutions.

David Green: I think you have got all the best stuff to look after and I think we are going to explore a little bit more around the thinking around bringing those things together. So I think that will certainly be a good conversation. If we just focus for one last moment on the journey so far, what would you say have been your key learnings over the last five years?

Alexis Saussinan: I think one of the key ones is what I mentioned earlier, that you have really got to make sure that you are putting your efforts on the right strategic priorities. Of course, we also run mini R&D as a team that looks more at early development, especially in data science. However we have got to make sure that the priorities that we are working on are aligned with the business and people priorities of the company, that they can deliver a value and that that value can be delivered in two areas. On the one hand you have got to deliver at scale, you have got to make sure that you can move away from the pilot syndrome, if you know what I'm trying to say? And really unleash the power of these data analytics insights. Then on the other side, what is very important as well is to be able to operate some business differentiated solutions. At Merck we have three business lines and they are operating within a specific context and it is always very important to shoot for use cases that would serve the group as a whole, but also use cases that will serve specific business lines, strategic priorities. So that has really been one of the key learnings.

I would say the other key learning is that to be successful, it is always better to show than talk. Being sucked into concept and questioning should we do it? What is it going to do? Ending in years of discussion. So what we have decided to do is to go in a very pragmatic manner, to show the value of what we were talking about so that people can really understand this target to really drive change and the mindset within our company.

So I think that has been a very strong second learning.

A couple of more, adoption. Sometimes, the way I look at people data and technology is very much like a product, where you have a market, which in our case is largely our company and you want to make sure that the solutions or the products that you are developing on data and technology are really being adopted. Sometimes you might have the coolest innovation on the data and tech front, but if it is barely being used there is no real point. So it is really around making sure that everything that you are investing in, delivers return on the investment that we are targeting.

The last one, which for me is extremely important, is sponsorship. I personally don't believe that without the sponsorship of our Global HR Leadership Team, of our CHRO himself and of our Business Leaders, we would not have been able to go that far today. So the journey is far from being finished, but this has been some of the key learnings that I have had so far.

David Green: Again, so much to dig into there and we are going to, I think you mentioned sponsorship and working with stakeholders both in HR and the business. It is funny actually, when I speak to some of your peers and they will talk about “we have got to get our data sorted out. We have got to get technology sorted. We need to hire a data scientist.” And I think I say, yeah, all that is really important, but you have got to start with the stakeholders, start with the business because if you are not showing the value of what you are doing, you are not going to get the budget to hire people, to spend time cleaning data, to buy technology. It is all about delivering value, so I really liked that. And I think that adoption piece, I guess it is about usability, it is not about cool tools. It is about making them usable and helping people to use them, which I know you have made a huge effort at Merck to do that. I think we will touch on that a little bit later around how you have helped colleagues in HR, but also the business. actually use some of the tools that you are providing.

I think you have talked about this a bit, but it may be that we can summarise it a little bit. You have really focused around the business, it is about the business question, it is about solving the challenge that either helps the group or one of the other three business lines.

How have you managed to elevate the conversation at the business level? What tips would you offer your peers trying to do something similar? Because it is very easy to get stuck in the weeds with analytics, so any tips that you can provide to help people get out of those weeds I think would be good.

Alexis Saussinan: I think it boils down to a few things. The first one, which I already mentioned before, is to show the value. Being focused on the value add and the impact.

Thee other very important thing is to be very collaborative. The level of collaboration that we have within our HR organisation and together with the business, for me is pretty amazing and really helps us to go to the business as a people function, to not just talk about this data and analytics product in itself because when you look at it from an end user or business perspective, that is not what really matters. What you are looking at is how does it blend and add value in to the overall value chain that you are looking at from a business and people perspective. That level of collaboration that we have had with our HR regional, centres of expertise, or our business partners, has been a critical success factor.

Then I think being able to have a full transparency on how this type of work can bring value. What I mean by full transparency is first of all, being very transparent on what are some of the key products or use cases that the team is working on, so that sometimes there might be some opportunities that we might not necessarily have identified at the beginning, but somebody can come and knock on your door and say “Hey, how about we maximise even more that data and analytics asset so that we can increase its impact.” So transparency I think is quite key. Being able to bring data and technology early in the strategic decision, I think is also key to elevate the dialogue. Because if you just look at data and technology as a tool, as I hear it sometimes, I think you are actually hindering yourself from some of the potential that data and technology can bring you. So being involved in some of the strategic design or more early stage strategic discussion can really help to maybe look at things differently, compared to more traditional ways of thinking. I would say being able to position the power of data and analytics on these strategic initiatives, there are areas where in the past HR was not necessarily at the table of certain business discussions, for whatever reason and I think thanks to the investment that we have been making into people data and technologies we are also able to help our global HR Leaders to bring data at a very strategic level on the people side, when they are working together with the business.

So I think these are really important steps, if you want to move away from just doing your thing and making sure that you are supporting your whole global HR strategy and positioning HR where it should be.

David Green: That is all great advice. I think that we should now dig into some of the examples of the work that you have done. I think the work that you guys have done around workforce planning, utilising skills, I think is particularly interesting. I think listeners would really welcome that. Can you share some of that story?

Alexis Saussinan: Yes, absolutely. So again, working in an extremely close collaboration with our other colleagues in HR we wanted to reshape the way we look at strategic workforce planning. I believe like many companies, we had tried in the past to go about strategic workforce planning via various ways. We realised that the impact that this type of initiative was delivering was not exactly where we wanted it to be. So we engaged going into a rethinking of that particular solution, actually mandated by the Global Executive Board, which helped a lot because strategic workforce planning is a key enabler of our global HR mandate to shape the people dimension of Merck. So based on that, we looked at how to best look at strategic workforce planning and we did that in very close collaboration with the business Leaders, looking at real use cases, not so much approaching it from a pure methodology standpoint, but really try to blend it into a business planning exercise. Looking at how the business conducts business planning and integrate strategic workforce planning into it along with people planning. One of the key things that we have realised is that for strategic workforce planning to be really impactful it needs to be heavily data driven. We really wanted to move away from guessing how certain jobs or skills might evolve or maybe just relying on predictions that might be out there on the market, but be in a position to actually translate external mega trends that are relevant for us at Merck, through data. Understand the right workforce for specific type of jobs or areas, what are the skills out there on the market that are going to be in more demand or in less demand. What are some of the jobs out there on the market that might not be existing anymore, that might be different, or that might be new. And to really take that as a very strong input to inform the way we want to work. It is really about how you want to be doing these business type of discussions that you are having through this data and strategic workforce planning. As soon as you are clear on that, you can help the business think how they want to be doing business tomorrow, then fairly naturally we realise what type of skills or what type of jobs we are going to need and how do they compare with the current skills and jobs that you have. Then from that fit gap, you have the priority areas that we want to further invest in.

So this has really been a pretty successful way to reshape how we look at strategic workforce planning and today it is actually embedded into our overall people plans, which are part of every business plan now.

David Green: And I believe as part of that work, using some natural language processing I believe, to do some skills inference?

Alexis Saussinan: Absolutely, I am sure you would admit that especially out there on the market, there is a wealth of data that is untapped. And just relying on structured data, relying on already existing fixed skills databases that we have any way to maintain, or we do every other year, or asking your employees to complete a list of skills that they might have and ending up in thousands of lines to compete on a regular basis is just a killer from an end-user experience. So we kind of took it the other way. How can we make the most of that data that is out there, which is largely unstructured. As you said, through natural language processing techniques and all the different technical methods, we were able actually to translate that unstructured data into insights that we can use.

So it is something that has been a pretty big eye opener also in the way we can make the most of that analytics in this space.

David Green: Yeah, very interesting and we could probably do a whole episode on that alone. Are there any other examples of the work that you and the team have done that you would like to share? I know you have done a lot of work around future ways of working, in the last year or so obviously.

Alexis Saussinan: Yeah, absolutely. There have been number of use cases and as you say, we could talk about it for a whole day as I am very passionate about it. One of the areas where we were able to position data and technology very strongly was, as you said David, in our future ways of working program. I think at Merck already last year, we have engaged into that very strategic initiative, directly speaking with our Senior Leaders and the Executive Board of how we want to shape future ways of working. It was a broader program that was part of that, that was looking at various components and flexibility of work or different ways to approach the way work gets done. But for sure, the whole area of how to digitise people solutions, was a core area of that. Here it is actually always a fine balance in making sure that our core or our basics are working right and to innovate on the must-win. And for me, when you look at the way we manage our portfolio, it is always around these two dimensions. I remember having so many discussions with the Business Senior Leaders, who very rightfully said that if our core basic solutions like how to manage performance or things like that are not working, then we are not talking and there is no point trying to bring some more innovation around that. So that is one thing where we make sure that we spent the right level of effort and manage that balance with a very strong employee experience in mind. And then we also work on more innovative items. We have been developing some pretty advanced robots that help navigation through data or help provide some standard answers. We have been and are still actually continuously working on how to create more AI driven people solutions, for example in recruiting, to make sure that we can facilitate the job selection and assessment and of course, making sure that we never end up in biased algorithm. That is a key item for us as well. And also trying to put AI in various people solutions as we move forward. So quite a number of use cases.

David Green: Well, funnily enough, we talked about the technology piece at the end there and obviously as you said at the start, your role has expanded. The team has expanded now, you have brought people, data analytics and technology together. What is the thinking behind this other than the obvious and what are you seeking to achieve?

Alexis Saussinan: I think really that that is a pretty bold move that we have decided to make, as a company. When you look at the business, we are not the first one on the business side, there have been digital, data and technology departments being brought up, so we really want to operate like a business in that sense.

And by bringing both people data and analytics together, I think we really wanted to get to the next level of our HR transformation. To look at things with a lot of value adding impact and scale. Right now, by bringing this together, we are able to look at the big picture. We are able to see how various pieces of the puzzle, various use cases need to be combined. How data can be further integrated, how maybe our landscape needs to be simplified because it is not always about investing in new things. Sometime it is about reviewing what you have and make the choice to maybe integrate certain technologies, then commission some others, so that you can free your capacities and investments and maybe invest in different areas.

So I think making that move brings us the scale and the opportunities to deliver value even faster for the business and for our people solution. So we are still at the early stages of that, but we have lined up our five year roadmap and are very actively working on that. So I am sure that there will be a lot more things to come in the next few months and years.

David Green: We will look forward to that and what is interesting that you said was that right at the start of the journey back in 2016, you brought the data together across your pre hire to retire. Then what you have just talked about there was by now enabling some of that with technology, with an eye on the employee experience and bringing some of those use cases together and integrate them, so you can start to look at employee experience across rather than down. Candidate experience, experience in on-boarding, experience around learning or moments that matter, you actually can go across and obviously you have got the data to underpin that. So yeah, a really good opportunity to bring things like learning and careers together.

Alexis Saussinan: That is clearly the direction that we are heading in, we are not there on all topics, but we are really striving for that. But I think you really said it well, at the end of the day, when we were really looking at business impact and experience, it is almost about being able to inject data and technology insights across the Business Managers and the employee journeys without having them really notice it or at least that is as my dream. I sometimes say that if one day we are able to put the right data and the technology insights, work on automation and more prediction, and really blend those into the natural journey that our employees and Business Leaders do, I think this is really where it would be able to shape the way work gets done differently. So that is kind of the goal.

David Green: Well we will have to have you on the podcast again in a couple of years time, so you can tell us where you are on that journey and some of the other great stuff that you no doubt would have delivered by then.

So in terms of bringing those teams together, you talked a little bit at the start around how your team is comprised. What does this mean in terms of the mix of skills in your team? So i.e bringing the technology piece in and bringing in that kind of people experience, that digital HR user experience and enablement in there.

I assume that is the new piece that has come in? If not correct me, but what does that actually mean in terms of skills and where did you get those skills from? Because, I am guessing that you are not always going to get those skills from HR professionals, you are going to have to look outside the function a little bit.

Alexis Saussinan: Absolutely. So in terms of different types of skills this has evolved, as you said earlier, when it comes to the various stages of our journey and maturity, we have been building up skills over time. Today, being able to have very strong portfolio management skills, also running business casing, financial modelling is really important. So that you can make sure that once again, we will provide a little bit like a business with the end ROI in mind. Skills around data governance, stewardship data, data quality management, as well as data privacy and ethics are critical. Just to touch on the ethics piece for a second, I think what we have realised is that the more we are going to grow in terms of impact and scale, the more we are going to have to anticipate and ask ourselves the question of what we, as a company, want data and technology to do and not to do. It is not because you can do everything but that you should be doing it. At the same time, also one of our success factors, we have always worked in extremely close collaboration with our data privacy offices, our work council, we have a very strategic partnership at Merck which is a true competitive advantage, at least that is what I think. And that sort of sets up the skills.

Then we have data science. Different types of data science, I would say, more data science sometimes on the very technical data techniques, but also you have got to look at data science in terms of industrialisation and it is a different skill-set. As I said earlier, if you should just focus on the first one, you are going to end up with great mini pilots but you are never going to be able to scale them. So looking at industrialisation, digitalisation is important. We have skills around UX, digital HR, as I said earlier enablement, focus on people knowing the end user, can connect with the end user, involve the end-users, so that we never end up in an HR centric approach.

Then you really have to have people who can very nicely reach them, so core business or people requirements and the technicalities of things and this is another type of profiles that are in my team. We work in strong collaboration with our IT department, various other departments so you have got to make sure that you have the skills at hand.

And now to your point David, where do I get the skills? Of course it is always a very interesting journey. First of all we develop a lot internally at Merck, we put a number of our people on development journeys and make sure that they can grow together with us at Merck. I think that is extremely important. We actually have quite a number of people who are not coming from HR but have more of a business background and add actually a tremendous value to both sides of the equation together.

Then what you might have noticed from my team set up, a global team, the diversity of thought profiles that we were able to bring at Merck is definitely something that I believe helped to bring us to where we are today. I am personally a strong believer of, if you really want to operate a global function like this one, you have got to be located locally to where Merck is. Maybe not just sitting in the headquarters or in one particular area, you need to understand Merck. Merck has grown a lot, Merck today operates in more than 66 countries, we have facilities in China, US, Europe and so on and so forth and we need to understand that we need to stay close while the business develops. So these are some of the ways we tried to do this David.

David Green: Great. It is not just about the team, obviously I know you have done a lot of work around helping your wider colleagues in HR and the business. What are the steps that need to be taken or have you taken rather, to improve data literacy amongst the wider HR community? Because that is a challenge that a lot of your peers say that they either got or they have had and they have tried to overcome it, but I know you have done some really good stuff at Merck around that topic.

Alexis Saussinan: We did a few things, one of the things that we realised pretty early, especially three/four years ago, is that if you want to increase data literacy forget the tool, it is not about the tool it is about what you can do around it. This is where we have been building communities within HR and even more broadly in the business, that come together to share how they have been getting value out of people data and technology insights. So being able to build some ambassador networks that serve as a multiplier into your up-skilling efforts is something that has been proving to be extremely successful.

Being able to go beyond the HR community, we are very involved for example, in the overall Merck data science network, that actually is more of a business network. But having these touch points is something that we are putting a lot of effort on.

We have also been working on rotational programs where different people from various parts of the organisation, either have been working jointly with us for a period of time, or maybe even swap jobs with some of our team members or join a rotation. I think that has also helped a lot. But the main thing is really the fact that data literacy in HR and technology is actually one of our global HR strategic priorities and as soon as, from a sponsorship and a messaging standpoint, you make this clear it has really been giving us quite an accelerator.

So various ways. We also tried things that didn't work, I will be honest with you, but these are some of the big things that have been proving very successful so far.

David Green: Yeah, I know because you kindly invited me to speak to one of your Ambassador Networks, towards the end of last year, and I was struck by the enthusiasm, the questions, I think it was the end of the first year of that ambassador program and you could see that the level of interest but also awareness and capability really struck me because that was a group of around 40 people and as you said, they act as a multiplier. I think it is very important and it is something that really has to be a highlighted that having that clear message from the CHRO or the HR Leadership Team, that this is the way we are going as a function in HR, that really is important in setting that path for people. They know that if I want to be successful in my career at Merck in HR, then I need to do this and actually part of the ambassador networks is seeing that it is not that I need to do it, it is actually going to help me have more impact with my customers in the business as well. So yeah, I think it is a really good template that other companies could follow.

So last couple of questions, obviously as part of your portfolio you have been running people analytics for four or five years now and obviously being pretty successful in doing that. I think that is great and you are setting an example to all of your peers. What are the key tips that you would give to a People Analytics Leader or a CHRO who is looking to scale people analytics in their company? Maybe they are where you were, back in 2018 or something. How do they get to the next level? Or maybe they are starting, there is probably some of the stuff you said about focusing on the business, but if there is anything additional that you would like to add?

Alexis Saussinan: Absolutely. Yes focusing on the businesses is key. I would say don't think that when you are starting, it is all about data science or having data science skills within your HR team, I actually don't believe so because a couple of years before we started bringing our own data science into the people space, before that we were very much working with the network. What I am trying to say with that is, that it is not so much around the technicality of the insight that you are able to produce it is much more around how much can the insight deliver value to a strategic business question or business problem that you are trying to reach. So really start there, not so much HR centric, but again, look at the impact that is being delivered.

I think another thing that I sometimes hear when I speak to some of the peers also out there in the network, is spending years maybe trying to clean up the very best data at global level. I mean data quality is critical, don't get me wrong. What I am just trying to say though, is that there are definitely ways to look at bringing the right data together, based on the demand that you are going to face from the business, more than just trying to go and fetch every single data point that is out there.

But it is something that I sometimes hear, where we kind of start on that consolidation piece and it might take us some more time before we can start. I don't think that is the case, I think as soon as you appear on demand, then you can already start running the data analytics front.

And the last minute tip, I think it is just a repeat from what I said earlier, but it is sponsorship. You have got to walk what you talk. If you really want to bring people analytics and technology at the core of your HR function or the people analytics function, you really have to speak with one voice. Make sure that all the way from the Global Leadership Team to your partners, to your employees, everybody speaks with that same voice. Understand what is in it for them and we are all together in that journey. So they are a few tips that I can think of.

David Green: Very, very, very good tips and that leads us nicely onto the last question. So it is on a theme that we are asking everyone about, in this series. Will jobs now be more deconstructed and instead be based on skills?

A nice easy one to finish.

Alexis Saussinan: It is a really good one and one that is extremely time relevant to us. I think, especially as we look at the current pandemic that we are unfortunately going through and how a number of businesses or organisations have managed to navigate through that so far with more or less success. What is clear is that the way work is going to get done is going to be different, maybe not at the same speed, maybe not at the same scale and with a lot of differentiation, that is for sure. But what is clear is that different types of work are going to be done differently and as soon as you become clear on that, it becomes pretty natural to think that the way that jobs were assembled in the past, by a set of activities, to a certain extent might not be assembled in the same manner. There might be opportunities to look at activities and tasks in a new context with new enablers around us. We talked about technology, be it automation, augmentation. This is why personally, I believe in that model that I hear sometimes, that skills is one of the key new currency. Where we should be thinking a lot more in terms of skills and not just in terms of jobs, if we want to be ready to tackle the next years that are ahead of us successfully. So definitely something that I am sure we will hear more about in the next few years. I am actually extremely curious to see that, I am curious to really see the results in how companies are able to progress in that direction beyond just the fact of saying it. I think you would agree that we hear a lot about that, especially out there on the market, around how jobs are going to change and the future of work, which is great. I think that it is a trend.

However, I would want to see how much of this becomes real and how fast. At Merck, at least we are trying to approach this very proactively. We don't want to be caught by surprise or try to not be disrupted as much as possible. So trying to engage again as a whole company, with all of our partners and Leaders, into making sure that we can think or rethink about the different types of work that will be made and the implications on jobs and skills.

David Green: Great and I think actually having that kind of employee experience as part of your responsibilities is great because I think a lot of it will be driven by employees anyway or the workforce. Because you know, we can't try and force the workforce to do stuff that they don’t want to do.

But I think a lot of it is coming up from the workforce now and companies are having to adapt to that, which is no bad thing.

Alexis Saussinan: Absolutely, again it is all about being driven by the impact and the outcome. What would you want to have versus having too much of an HR centric approach. Staying close to how the internal and external markets are evolving and making sure that you can influence that to shape how work gets done and the people element of it, it is really exciting.

David Green: Well Alexis, I think we could carry on talking but Ian, he always laughs when I say this, he will cut us off at some point. So I am going to end the conversation now. Thanks so much for being a guest on the show. I think there is so much learning there for listeners. How can people stay in touch Alexis?

What is the best way?

Alexis Saussinan: I think LinkedIn might most probably be the best way to stay in touch with me. I am actually spending quite some time hearing out some of the great practices that might be out there on the market, exchanging ideas or even co-creating ideas sometimes. Sometimes with you David, sometimes with other peers, so I think that might be the best way.