In this episode of the Digital HR Leaders Podcast, your host David Green explores the transformative power of data-driven HR decision-making in one of the world's leading pharmaceutical companies, Novartis

Joined by Ashish Pant, Global Head of People Analytics and Data at Novartis, David and Ashish unravel how Novartis has harnessed the full potential of data to revolutionise its approach to HR.

Throughout this episode, you can expect to learn more about:

• How Novartis strategically laid the groundwork for harnessing the full potential of HR data and analytics;

• Invaluable insights into the three-stage approach that played a pivotal role in crafting a successful People Analytics team at Novartis;

• Novartis' recent business transformation and how the People Analytics function under Ashish's leadership played a critical role in facilitating this significant change;

• How to bridge the gap between bottom-up understanding and top-down organisational intentions;

• The metrics and KPIs used to gauge the success of the business transformation;

• How the transformation impacted the structure and operations of the People Analytics team at Novartis.

Support from this podcast comes from Visier. You can learn more by visiting: Visier

If you would like to discover Visier’s groundbreaking research ‘Unlocking Manager Effectiveness: The Next Driver of Value clicking this link.

[0:00:04] David Green: In this episode, we dive into the impressive story of the growth of the people analytics function at Novartis, a journey that began with a vision four-and-a-half years ago to transform Novartis into a data-driven people and organisation function.  Ashish Pant, Global Head of People Analytics and Data, took on the challenge to establish the function.  In our conversation, Ashish outlines the three-step approach he developed to build the flourishing people analytics capabilities Novartis has today.  But this is more than just a conversation about people data and analytics, it is also a narrative of transformation and adaptation. 

In April 2022, Novartis embarked on a significant transformation into a focused medicines company.  And as Ashish supported the organisation through these monumental changes, the role of the People Analytics team proved pivotal.  Today we'll explore how people analytics helped support the transformation, the key metrics and KPIs that guided the way, and how these challenges impacted the very structure and operation of his team.  So, please join me as I welcome Ashish Pant to the show. 

Today I'm absolutely delighted to welcome Ashish Pant, Global Head of People Analytics and Data at Novartis, to the Digital HR Leaders podcast.  Ashish, welcome to the show.  It's great to have you on.  We've known each other for a few years now and you kindly contributed a case study to Excellence in People Analytics when we published that in 2021.  So thank you, first of all.  And then can you give a brief introduction to you and your journey at Novartis in establishing the People Analytics team.

[0:02:03] Ashish Pant: Thank you, David.  I'm glad to be here.  I lead the People Analytics and Data Function at Novartis, in the role for about four-and-a-half years, and have had a very, very exciting and learning journey, you know, during the course of these four years.  Of course, we've been collaborating closely with Insight222 during that period as well, which has been fabulous.  I have had a varied career, but almost all of it in HR, ranging from business partnering to talent management, talent acquisition, HR strategy, and so on and so forth.  I think it's a beautiful culmination in a sense that I can bring in the experience from all of those disciplines within HR and merge it with the passion that I have for first principles thinking, numbers, data in my current role.  I'm an engineer by first degree, so again I've been close to this field as well, and it's just a beautiful combination for me where I am at the moment. 

[0:03:05] David Green: Yeah, it's great.  It's as you said, a nice combination, the HR experience and background across a variety of different practices in HR, including business partnering, which we know is so important, working together with people analytics to get business value out of people analytics, but also the engineering background as well, and then the passion for data and analytics.  It's a nice combination, Ashish, and it's impressive.  We're lucky to have been privy at Insight222, and obviously talked about the book where you shared the early part, I guess, of the first two years of the journey there.  It's certainly impressive how you've built the people analytics function at Novartis.  So that is four-and-a-half years now, isn't it?  Could you walk us through maybe some of the key highlights or milestones during this journey?

[0:03:51] Ashish Pant: Sure.  In 2019, we got a mandate from our CEO, Vasant Narasimhan, to become a more data- and digitally-enabled P&O function we call HR P&O, People and Organisation, at Novartis.  The reference that the organisation had for people analytics was a bit of people reporting fundamentally, and there was a small team of four individuals who were supporting some global initiatives that needed this information.  But beyond that, the access, the thought process around how to do proper analytics, how to potentially even think about advanced analytics, was at a very nascent stage at that point in time, I would say.  I like to call the duration, the early years, the first 18 months more of startup.  So we were very, very focused on identifying a few critical business problems and showing what impact people analytics could make.  And the idea was not to go across the organisation, you know cover everyone, but just go really focused and show value.  And we picked up a few use cases and delivered some solutions, some products on those. 

As you know, Novartis prides itself for being one of the most focused organisations towards organisation culture, so we helped build some solutions in that space.  We are really, really focused on enabling learning for our masses at Novartis, and how learning was enabling better business value was a question that landed on our table and we worked closely with our learning function and ensured that learning had a major impact on how engagement of the organisation was going up and how voluntary attrition was trending down.  So, these are some of the early examples where we showed the organisation how people analytics is really fundamental and should be key and central to the business strategy, and that kind of got us out of the door.  And we were, of course, very, very closely supported and sponsored by the P&O leadership all along, which I think is equally critical for us to be able to make an impact, right?  So I think it was a confluence of factors that kind of helped us go through that very intense, but very rewarding phase, which I like to call the startup. 

Then, I would say 18 months into the journey, we started to feel that we need to now scale up these solutions, also expand the reach.  And one of the key elements for us to do things at scale in people analytics is availability of high-quality, clean, well-categorised data at scale.  It was at that time that the responsibility to start thinking about people data in a more structured way and how it could add business value also got connected to my role.  So, phase two, we spent a lot of time in creating the enablers for the scale-up, so putting together a strong Governance and Compliance team around people data, working very, very closely with our digital P&O organisation, not just in terms of, "We would like to collect information and data off of your systems", but really integrating with them and working together on a lot of strategic decisions. 

For example, we are very close to a Workday rollout at this point in time with Novartis, and my colleague who leads the Workday implementation and I, we've been working hand-in-hand for the last almost three-plus years to ensure it's not just about an implementation of system that runs certain processes, but then we are also able to extract the right information, the right data, the right reports out of it, and also ensure that the data that is there is of high quality and is well managed.  And this enabled us to then start building a few solutions at scale, and as we go live with Workday next year, some of these will get deployed in terms of high-quality dashboards, high-quality reports for use by business partners, P&O leaders, all the different population sets that we have within the P&O organisation. 

The third phase, which we are on now I would say, is what I like to call maturity.  And I think that the key pivot we have made in this phase is, we have started to get closer and closer to our different businesses within Novartis.  The whole idea, the whole approach was in phase one, let's show impact; in phase two, let's try to build infrastructure and capability to deliver things at scale and also where needed, go custom, because Novartis as an organisation is a very, very diverse place, right?  The needs of our research organisation are fundamentally very different from the needs of our production organisation or our commercial organisation.  So, we clearly see the need for that nuance to be brought in into how we do our jobs, but we needed some time to build up to that, and I think we are there now. 

In this recent phase, we have now embedded what we call People Insight Partner roles in each of these businesses within their P&O organisations, who work very, very closely with us and the central CoE, where we hold a lot of the people analytics capabilities.  And this network together is adding value, where we get proximity and better articulation of what the business needs are on the one side.  And then, depending on the nature of the question that we are looking to address, we can bring in the right expertise from the CoE to address that.  And this phase, I think, is still relatively new, we are still maturing in this phase.  I would say we've spent about eight-odd months doing this in a very systematic deliberate manner.  More to be done in the coming months and years. 

[0:10:43] David Green: And thanks, Ashish, for sort of going through in some detail there the three phases.  So, as you said, phase one was all about impact, really focusing on specific business cases.  And I know at Novartis, you very much tied, and certainly this is probably good guidance for anyone out there who's looking to do something similar, you know, you tied the people analytic strategy very close with the people strategy, which was very closely aligned with the business strategy.  And I think all those three things need to be working in sync.  By creating that impact, by focusing on business priorities, you created momentum, interest I guess from the business and other areas of P&O, P&O leadership as well, which gave you, I guess, the width then to, "Okay, well how can we do this on a more consistent basis at scale?" hence why you then invested in the infrastructure, particularly in phase two and obviously honed that capability. 

I know we're going to talk later about the behavioural science muscle that you've kind of built into the People Analytics team there as well, and now you're really thinking, "Okay, well, how can we be even more closely aligned with the business from a maturity piece?"  So, you've got people and insight partners that are facing directly off to different businesses within Novartis, and as you said, recognising that the needs of your R&D business are going to be very different from the needs of your commercial business.  And I appreciate that that people insight part of the role has only recently been embedded, and obviously you're probably starting to see some early signs of success that.  One question before we start to talk specifically about the business transformation that I know Novartis has been going through, what are the early signs that you're getting from having that people insight partnering role and how is that impacting the work of the team?

[0:12:32] Ashish Pant: So I think a couple of reflections maybe here.  The first one is that in a complex organisation of the scale of Novartis, even though we are very diverse in terms of our needs, we are also very similar, right?  I think that's one realisation, because I'm corralling this community of practice now where these insights partners join us on a monthly basis and we have started to exchange use cases, and what are the priorities that each one of us is working on, and you see there's just tons of translation that you can do across.  So clearly, we were leaving value on the table earlier, so now we are trying to be even more focused, more networked, and borrowing stuff with pride.  We don't need to start from scratch on a multitude of use cases that we're working on.  Our colleagues in a different function would have probably already travelled 80% of the journey sometimes.  So, I think that's one thing that's coming up very clearly. 

Second thing which I would say is an early realisation/success is, I would say, and this is more for me when I was doing my discussions about talent landscape within people analytics at Novartis, and of course we are a nascent function in the P&O space, whichever company we might talk about, and therefore the talent pool is always a little bit limited and career pathing is not very clear.  Having gone through this evolution on the journey and then looking at who we have hired into these roles, I now start to see a much clearer path, a much clearer view of not just the variety of capabilities, but also how career ladders could potentially look like. 

For somebody who's been an expert within the CoE focusing on employee listening or just data science, how they, through this network, and getting exposure on the other side of the house, could eventually translate, make the jump into an insight partner role, and vice versa, where the insight partners might not be deep into a certain expertise, but they're front-ended with the business and they understand what's the requirement on that side, and through a structured, active developmental path, they could move into roles within the CoE.  I think that's very healthy for us at Novartis, and I think this is how the practice is also going to evolve in the future.  I would say those are the two early wins and we are looking for more and we'll share in due course.

[0:15:21] David Green: Obviously, the work that you did in the first three, three-and-a-half years set you up well for a major piece of work that you did last year within people analytics to support quite significant business transformation that Novartis has recently undergone.  For those that maybe aren't aware, what are the key elements of the business transformation itself and maybe more importantly, for the context of listeners, what is it that the role will be of the people analytics function in supporting the transformation? 

[0:16:32] Ashish Pant: Let me take maybe just a minute to talk about the transformation itself.  So, Novartis has been on a multi-year journey of moving from being a pharmaceutical conglomerate to becoming a really focused medicines company.  So, we used to have a vaccines business, an animal health business, a consumer health business, an eyecare business, and over the course of the last decade, we have either sold off or spun off some of these businesses, right?  Very recently, in fact not recently, but imminently, we're also going to spin off our genetics business, which is Sandoz.  So this is one train of thought that Novartis has been on from a strategic perspective.  The other one has been about becoming really, really focused and efficient in how we deliver impact to our patients. 

So, these two elements kind of came together in the transformation that's been happening at Novartis over the last, I would say, 18-odd months now.  It was announced on early April last year, and the fundamental focus was on optimising the resources in some of our commercial divisions, which had synergy amongst themselves; at the same time, also aligning some of the key global functions into an aligned structure.  So, for example, the whole of the finance organisation was brought under one umbrella, the whole of the P&O organisation was brought into one umbrella.  Earlier, some of these resources were embedded in specific businesses. 

What it meant for Novartis was that prima facie, there were about 30,000 associates who would be directly or indirectly impacted.  So, it doesn't mean people were going to lose their jobs, but it meant that somehow their association with the organisation would shift or would become different than what was existing.  And as you can very well imagine, a lot of these transformations are first strategic concepts, then they are commitments from the senior leadership, and a lot of it happens rightfully under the rules of confidentiality.  But then at a specific moment, there's an announcement. and then there is a huge machine that's put in place to execute on that announcement.  And we were involved very, very closely from the very beginning, once the execution phase started.

The two areas in which I think we really, really drilled down and focused was number one, helping establish a clean, clear baseline for the part of the population that is in scope of this transformation.  It might sound like a very simple, straightforward activity, but translating that strategic executive thought into what would it really mean for an Ashish or a David, given their roles, given their position in the organisation, are they going to be in or out, is an activity that takes effort.  And I don't think we should take all claim for doing this well; we had an important role to play, but we were working very closely with the change office that was set up.  But it was a very, very close partnership where a multifunctional team, including people analytics and reporting experts, worked night and day to articulate who would be in, who would be out.  Again, the pace is important in these things because you want to do it in a way that you minimise the anxiety in the system.  And more information available early helps. 

So, it was an intense period for our team, but I think this really, really helped build that comfort and credibility for the function as well, that we could partner and we could support and help in a major transformation from this perspective.  And once the scope was in, we worked very closely with the change office to continue to provide metrics on how the transformation is getting executed.  And this is a rolling activity.  This takes months sometimes and I think in our case, given the nature of the transformation, it was almost a one-year programme, where the People Analytics team was continually helping and working closely with the change office, with our P&O Services team, to help validate whether the changes have been made correctly in the system. 

Of course, a lot of what happens in transformations like these is manual entry into systems, because of course, there are a lot of decision rules.  But when folks are involved and you want to be respectful to them and give them the right message, there is a lot of double-checking and triple-checking that happens.  And P&O services does that in most organisations, but again, when we look at the data from an analytics perspective, we do a lot of sanity checks to say, "Okay, is everything good?  Are there things which could have been done better?" and so on and so forth.  So a lot of those validations were done by the People Analytics team.  And this activity still continues, because we are now consolidating those line items and sharing metrics with our senior leadership, even till late, just to show, "Are we tracking as we had agreed at an organisational level?"  So, this was one big workstream where we played a fundamental role. 

The second big contribution we made was around helping the organisation understand how the change was landing as we were going through the change.  And our Employee Listening team played a very critical role here.  We again were fortunate that we connected very early to the Change Office.  There was a cross-functional team of folks from our Organisation Development Change team, from our Global Communications team and people analytics that was put together to think about how do we best help the organisation during this time.  Of course, leaders want to know the pulse of the organisation during times like these.  And there is always hunger for more of that pulse rather than less of that pulse in situations like these. 

We took a very conscious call in this group to say, less is more.  And we actually stopped all of our employee listening activities, except for the one engagement pulse that we do, because in early phases of such a change, the likelihood of the sentiment going in a direction different than down is remote.  And also, if you bombard the organisation with multiple surveys at this point in time, you also create a lot more pressure and a lot more anxiety for leaders and managers to then follow through, which they would do during the normal course.  But right now we wanted to give them the space and the time to really focus on a few things, give them one clear signal of how the sentiment is, and basically just double down on a few things that we thought were very, very important.  And I think this was crucial for us to be able to add value and create meaning and insight for the leaders, rather than give them three or four different sentiment sets and then create more cognitive load for them at that stage.  This was the initial phase, of course.

In the early days of the transformation, we also worked very closely with our Comms team, whose key focus was on ensuring whether all the information and messages that our leader and Novartis, as an organisation, is sharing with associates is landing well, is landing clearly.  And we also cross-referenced it with some of the sentiment that we were collecting to see, "Are there real oddities between these two or not?"  We didn't find many, which I think was very, very comforting, that we were kind of in sync and doing it well.  But I think this was a check that we continue to do for the first four or five months of this journey. 

The text data that we collected from our surveys was again very, very critical.  We received on an average 30,000 to 40,000 comments, and our Employee Listening team and the Data Science team started to parse these comments to figure out what would be useful for setting a baseline for the sentiment that we have.  We did some keyword-focused searches around words which are closely related to transformation, and how it was being positioned within Novartis.  And we shared the sentiment data on a regular cadence with the change leads that were set up in different countries, just to give them a sense of where probably to focus their guns.  It wasn't to say this is the be-all and end-all, but it was more like an additional piece of diagnostic that they could have in their toolkit as they start having conversations within different sections of their businesses or specific countries.  I think it was much appreciated. 

Then, once we kind of got through the initial waves of involuntary attrition in the organisation, which these transformations bring in, we also started to connect voluntary attrition data to these sentiment scores.  And I believe we continued doing this till mid Q2 this year.  So now, I think the tail of the transformation is left, but we have gone through the chunk.  And again, this was an augmentation we did at the opportune moment for the transformation to see, "Okay, do we see a relation between the sentiment in a certain part of the organisation that has gone through that massive transformation and voluntary attrition that's happening there?"  Because it's not just about doing right by the leavers, but it's also equally important to provide the right environment, the right messaging for talent that stays on with the organisation.  And I think this was again much appreciated by the change leads and the HRVPs with whom we shared it. 

So, around middle of this year, we've kind of put most of the activities that we were doing on a cadence to a pause, and now we are doing episodic work in this space where there is a need.  So, I think that was a long answer, but I think that's where we have been focusing our effort and our energy to support the organisation with the transformation. 

[0:27:29] David Green: No again, really good, because I know our listeners like to get the detail, because a lot of them are people analytics professionals, HR professionals themselves, that are maybe either doing this in their organisations currently or maybe looking to do similar things in their organisations.  So, I think it's interesting as you went through the kind of two main areas where your team was supporting the transformation, very much you are helping generate understanding from the organisation itself and giving that to leaders, but also then helping leaders understand how their communications, for example, were landing with associates in Novartis as well.  So, quite interesting. 

You gave some examples, I think, of the types of analysis that you were doing, particularly around looking at comments in text and then starting to look at how some of that sentiment was tying with voluntary attrition as well, just to give signals.  So, really interesting stuff.  I mean, I'd be interested, in terms of measuring the success, maybe, of the transformation, what were some of the key metrics and key performance indicators that your team were focused on?

[0:28:42] Ashish Pant: I'll again answer this in two parts.  So, for the first big activity that I talked about, I think around helping the organisation build a clean baseline, being able to share information around the heart progress of the execution in a clear, transparent way.  The metrics are very clear: accuracy, timeliness, and availability of information, because there's a lot of pressure and heat in these moments, especially in the early days. 

On the second one, where we were helping the organisation understand the sentiment better and helping leaders understand and change agents on the ground understand what they could do, I think the key performance indicator here was the anecdotal feedback we got from the change community.  This is more of a soft thing.  You are reading some information sitting in a survey, but you never have the context that somebody who has boots on the ground does.  So you're always making an educated assumption, unless you go deep and you say, "Okay, I want to focus on this country or this department or this function within this country".  For that, we had the change leads. 

So, what we did was on the basis of the collective feedback we received from them, we kind of created a package of metrics and insights which would be helpful.  And I think I already mentioned some of those in the earlier question.  But equally, we said very, very clearly, we said, "We will put some commentary around what could be the possible reasons for what you see here, rather than being prescriptive", and I think that was really very, very appreciated by the change community, because it kind of gave them a starting point if they did not have one.  But on the other hand, it also did not straight-jacket or box out analysis in a way that they could not position it in a flexible way with the business.  Or, if they saw something completely different on the ground, we had situations like those as well.

So, I think input and feedback from that community was probably how we played the second part.  Also, the addition of the voluntary attrition element was one of the inputs, one of the feedbacks that came in one of these change agent calls, where one of our talent transformation leads said, "Hey, great, but now I see this on the ground.  How could you guys help me?"  And that triggered us to then say, "Okay, let's build another layer into the solution that we have".  So, it was really those things, and we got really into a collaborative, "Let's roll up our sleeves and continue to evolve this product", kind of mode.

[0:31:42] David Green: Yeah, it makes a lot of sense, that close communication with that sort of multi-functional team that you talked about, that collaboration across different areas.  And as you said, that kind of continued, made you hone the work and the insights and the research that you were doing as the transformation progressed; makes a lot of sense.  I wonder, Ashish, how much did this change, the transformation and the work that the team were doing, how much did it impact the way that you've structured your team and how it operates now?  I mean, you talked a little bit about the people insight roles at the start of our conversation.  How is the team structured now and what impact perhaps did the objectives of the transformation have on that?

[0:32:28] Ashish Pant: I would say the transformation had a positive flip for the People Analytics and Data team overall.  The addition of the People Insights Partner into our broader community, this was one of the proposals that we floated as part of this transformation.  It was an accretive, it was a build to the People Analytics practice overall within Novartis.  That's the other reason why I said this piece is still maturing and we're eight months into the journey, because we worked through the design last year and now we are in the early, early steps of execution.  So, I think this was really, really good, and I firmly believe it's going to add tremendous value mid to long term. 

They were not structural changes, but I think the ways of working for the team, for the People Analytics team, changed during times of this transformation.  So in general, you have a very well-balanced cadence of activity that a People Analytics function puts out.  There was a very heavy load on a couple of areas that I just mentioned, employee listening and reporting and visualisation.  What we saw very clearly, with massive amounts of change happening in the organisation, a lot of the more targeted, focused, deeper people analytics programmes and projects were kind of put on hold for a bit, for like a quarter or two.  And that started to create a bit of a lull for the Data Science team at the same time.  And this was a very challenging dynamic to manage.  We have very talented folks in this team who would like to continue to add value, grow and so on and so forth. 

A couple of things which we tried, and again, we are no experts here, so always keen to listen and learn more from the community as well; a couple of things which I think helped us to a good decree was first, helping this team work on topics that are allied to the transformation, so some of the work around NLP that I talked about and helping set up a baseline for the sentiments on so forth.  I think it helped that they could get involved.  The second area where we utilised data science capability was in also helping our reporting team clean up, automate the massive amounts of data that they were processing.  And it was not as if it was getting pulled out of systems; a lot of it was residing in a different change management system and so on and so forth.  So, bringing in a couple of data scientists who could help clean up, automate this process, probably build some sanity data science checks into looking at the data sets in a more robust way, and bring efficiency into how the reporting team was working, which was very helpful. 

Thirdly, we also encouraged quite a lot of them to continue investing time in their own learning during this space.  The combination of these three helped, I'm sure there are other ideas, it's not a unique situation that just we have faced.  I'm sure a lot of our colleagues would also have faced it.  So, I'm curious to learn more as well as a follow-up on this one.

[0:35:48] David Green: So, listeners, there's an open invitation there if you're a people analytics leader, or part of a team that's thinking about how your team supported certain business challenges that you're solving, around data sciences, continue looking at upskilling your Data Science team or any of your people analytic professionals.  There's an open invitation there from Ashish to get in contact with him, which I presume, Ashish, will be probably best via LinkedIn, and we'll put your details obviously in the show notes. 

It's interesting, you've talked about two areas.  So, at Insight222, we do an annual research on the people analytics field.  And back in 2020, we presented an operating model which had about 14 different roles in it.  And then last year in 2022, one of the focus areas of the research was to understand the key roles within a People Analytics team that enabled those People Analytics teams to deliver value on a consistent basis over a long period of time.  And interestingly, the three roles that we identified as being particularly important that these companies were investing in, both from a hiring and development and retention perspective, were the consulting roles and the People Insight Partners that you mentioned, actually data scientists and behavioural scientists.  And I know that you have successfully integrated behavioural science into your team at Novartis. 

Maybe, could you explain how having this capability helps generally, I think, because again talking to some of the work that you mentioned at the start around supporting Novartis's organisational culture, but also maybe how that behavioural science muscle, as it were, would help you to cope with maybe some of the requests that you received during the transformation as well?

[0:38:33] Ashish Pant: Disclaimer there, I would say we are still early in the journey on exploring how behaviour science really truly gets embedded into the fabric of People Analytics at Novartis.  We see some very good early science and I'm very happy to talk about that, but equally, open invitation from my side to the community to have a deeper discussion on what you guys are seeing and learning in this space.  So, I don't claim to be any expert but happy to share my experience on this one. 

[0:39:07] David Green:  You're being very modest, Ashish, which is great! 

[0:39:11] Ashish Pant: But that's how we all learn and grow, right, and it's a great community here, so I would like to tap into the bigger brain of the collective as well.  But again, to share how we think about behaviour science and how we think it can add value, there are three spaces within the whole behaviour science area where I truly believe there's tremendous opportunity.  The first one is what I call behavioural psychological constructs.  This is the frame on which almost every survey, every instrument that we design and use in people analytics is anchored upon.  I think as a community, we all can do better in this space and the behaviour science capability can help us with that.  So, the behaviour scientists in my team are helping me build better quality employee listening instruments.  And they're also helping me and the team at Novartis doing a better job of customising these as needs change, and that's one area. 

The second one is in the whole space of change management.  For People Analytics professionals, this is still kind of disputed territory because there are always, if you're working in the HR or P&O function, there's always a big change in OD team, so from my perspective, the opportunities and how you co-opt your OD leader or change leader to work in close cahoots with your team, where you could then start deploying some of these capabilities into pure change projects.  Because fundamentally, a behaviour scientist can help you match behaviour from X to Y, and there's a scientific process to do that.  So, there's an opportunity to explore further there. 

The third one is again connected to this, but I still would like to call it differently, which is the whole space of nudging.  In my view, there is an over-reliance on thinking about nudging as a technology, but fundamentally nudging is a behaviour shift; technology enables it.  Having a psychologist or a behaviour scientist really think about what is the behaviour change, and how then potentially a technology, a well-defined communiqué, or whatever it might be, or an intervention can help nudge that behaviour in the right direction, is something that's an area where I think we all can do more. 

Within Novartis specifically, on the construct piece, the first piece, we have done a lot of work, and we are constantly improving and evolving the employee listening instruments that we have, and our Behaviour Science team really helps us with that.  On the change piece, we piloted, during this transformation that I talked about, embedding the behaviour scientist on a trial basis to enable movement of a change in a specific business.  They had decided they want a new operating model post the transformation, and we got a behaviour scientist embedded who basically was there to help articulate what steps could be taken to actually facilitate that behaviour change, and I'll be honest, with very limited success, because there was this whole massive dynamic going on when a transformation is on.  So, our learning from that was, it's better to embed behaviour science capability in peacetimes, pardon the euphemism there, but it's still a nascent capability.  It needs to be deployed in peacetimes on programmes where there is more openness for exploration. 

So I would very, very transparently say the value we got out of that engagement was limited.  On the nudging front, I think we have one good example of where it's added value.  Our talent management organisation launched a talent matching platform last year, and the behaviour science capability from our team got deployed there to help increase the adoption of that platform, both in terms of completion of profiles and then quality of matches.  And I think those are some of the wins which we're very proud of. 

We are also exploring at this point in time how some of these nudging concepts can help behaviour scientists support leadership development.  Because again, leadership development is fundamentally behaviour change.  So, we are working closely with our leadership development organisation to see where could there be value.  And again, as I said, go after willing parties, go to a place that's relatively stable and then deploy a high-quality behaviour science experiment, and see if we can help move the behaviour from A to B.  So that's what we are exploring at this point in time.

[0:44:25] David Green: No, it's really interesting and you're right, it's a nascent capability that some People Analytics organisations are looking to develop, and ultimately I guess, what are we there to do in people analytics?  We're there to provide insights that inform better decision-making, that's better decision-making by leaders and managers, but it's also by employees as well, to support their development.  And actually, what nudging I think can do, and certainly I think you've just talked to this, Ashish, is it can actually get these insights and start translating for outcomes, outcomes for the organisation but also outcomes for employees and people managers themselves as well.  And actually understanding the whole psychology around change and behaviour is so important to that, otherwise, I guess we could come up as people analytics professionals, we can come up with some amazing insights, even if the organisation decides to implement them, but if the individuals themselves don't, then we're not wasting our time per se, but it's lessening the impact that we're having. 

[0:45:34] Ashish Pant: Absolutely. 

[0:45:35] David Green: Yeah, really interesting and really based on everything we've talked about so far, I've got a couple of questions left.  And we're probably more now talking, I guess, to the maturity phase that you talked about, the third phase, which you're sort of in the midst of at the moment, from a people analytics perspective.  And again, when I ask you to look and envision into the future, even if it's the near future, I appreciate that it's just thoughts and ideas at the moment and it may change, of course, depending on both internal and external events.  But how do you envision the People Analytics team structure and focus evolving as Novartis continues its journey? 

[0:46:17] Ashish Pant: So I think for us, probably a better way to address this is to talk about the key levers that I see and what impact they would have; I think we will figure it out as we go along.  I think one key lever, which we've already kind of put into place, is the whole insight partner role and community of practice.  So, I see us operating more and more in the future as a hive rather than as a waterfall structure, and I think that's the way to go.  This is a business where we learn from each other, where there is value in translating what one has done into a different context, and where capability rides supreme.  It's not just about where the capability sits.  It can be deployed in a variety of different areas.  So that's one thing. 

The second one is around technology.  So once we go live with Workday, I think we'll have a massive opportunity to democratise a lot of stuff that currently, we have to brute force.  And I think that creates a massive opportunity for the organisation to get more value from us.  Equally for the team, it's a massive opportunity to move up the value chain and let the operational activities be taken care of by technology.  And this will, I'm sure, both of these will have impact on how we are organised and structured in the next years.  Still early days for us to really nail that one.  But these are the two themes that I see making an impact on where we go from here. 

[0:47:56] David Green: That makes sense, the first one around the insight partners and the community of practice really shaping the work that you're doing, and obviously increasing the impact by being more closely connected to the business; and then the technology element helping you to scale and automate and focus from there.  That makes a lot of sense.  And then the last question, actually, this is a question we're asking everyone in this series and I think talks to maybe one of the enablers of this as well, and I know it's something that you've been focused on at Novartis, as you mentioned, the learning element there; how can HR leaders, and people analytics leaders for that matter, how can they build a data-driven and digitally-literate culture in HR?

[0:48:42] Ashish Pant: My personal take on this, I think there is a plethora of information, knowledge, programmes, whatever you might want to call it, both behind curtains and openly available as well.  So in my early days in this role, I used to think access and availability is important.  I think it's still important, but it's just so ubiquitous at this point in time.  But again, from where I sit, I still see a massive opportunity.  So for me, the real lever is, how can we get people curious about the topic?  If we really deeply understand somebody's needs, I think we can get them curious.  So, really helping leaders, helping associates, helping every HR professional to think about, how can people analytics add value to their day-to-day work or their decision-making?  I think that's a constant journey that every People Analytics team member, it's not just the leaders, needs to do and we all need to do a better job of that. 

The second one for me is, how can we demystify that this is not a very complicated thing?  A lot of folks just sit on the back foot because they think, "Oh, you know what, this is not for me".  I try to go out of my way in multiple conversations to say, "Hey, we're talking about, even if you are building a great AI model, at its core is fundamental first principles thinking".  It says, what do you think the problem is; what's your hypothesis about that problem; where can you go and collect the data for that problem?  Forget about the analysis, the analysis will be done by some experts.  There are enough of us out there and there is beautiful technology that in a few years is going to enable that to be happening very, very fast.  If the output is supportive of your initial hypothesis, great; if not, then let's be very objective and say the hypothesis was wrong, the problem still stays.  What's the next hypothesis that you can think of?  And go through the cycle again and again. 

We do it in our day-to-day lives, we do it in our professional lives in a variety of different ways.  All we are asking, as people analytics folks and with analytics folks, is to just apply it a bit more rigorously.  That's something that I try to do in every engagement, every partnership that I'm trying to get into.  It works in some cases, it's challenging in others, but again, hey, it's part of our job.

[0:51:16] David Green: Two really good points there, I think.  And I think by having the People Insights Partners and that community of practice, you'll be generating more curiosity, I guess, and a greater level of understanding from P&O professionals as to how P&O, sorry, how People Analytics can support them in their day-to-day work and maybe actually help them be more impactful.  And as you said, the second one, it's so important to demystify, isn't it, because we read so much about how everyone who works in HR is going to have to become a data scientist, when obviously that's not the case. 

If you have specific skills to become and be a very good data scientist, we're not asking that, we're just asking, as you said, good problem definition, ability to create hypotheses that we can test, and then probably support in thinking about the data sources that we might want to bring together to test those hypotheses.  And then the ability to look at, what's the insight from the day; what's the recommendation; how can I present this in a language that will resonate with my audience, whoever that is in the business or in P&O that I'm working with.  So, yeah, and obviously as people analytics professionals, we've got a vested interest in helping our colleagues in HR and P&O to increase their curiosity and increase their aptitude around some of these skills as well. 

Ashish, fantastic, always good to talk to you.  Obviously, I had the privilege of seeing how you've built the People and Data Analytics function at Novartis over the last four-and-a-half years, and certainly such a firm bedrock, I think, for you to be even more successful in coming years as well.  Can you let listeners know how they can stay in touch with you, follow you on social media if you do social media, and connect with you as to your invitation around learning more about each other's work?

[0:53:13] Ashish Pant: Sure.  So, first of all, David, thanks.  Thanks for the invite and again, it was a fantastic conversation.  And we haven't done this journey alone, we've learned from Insight222, we've learned from a lot of the colleagues in the people analytics practice.  So, as I always say, we stand on the shoulders of a lot of others.  I'm available on LinkedIn and I'm sure you'll probably leave a link there with this podcast as well.  Otherwise, I'm very open to receiving email.  My email is ashish.pant@novartis.com and I'm looking forward to connecting with the community in the days to come.

[0:54:04] David Green: That's brilliant.  Ashish, thanks for sharing some of the journey of People Analytics at Novartis, and particularly as it relates to the business transformation, and I look forward to seeing you soon.