Episode 31: How J&J Uses People Analytics to Drive Business Outcomes (Interview with Piyush Mathur, Global Head of Workforce Analytics at Johnson & Johnson)

If the main purpose of people analytics is to improve business outcomes through improved decisions about people, who better to lead people analytics than someone who spent most of their career as a business leader?

My guest on this week’s podcast is just such a person. He is Piyush Mathur, the Global Head of Workforce Analytics, Data Strategy and Governance at Johnson & Johnson, where his team are helping to drive business outcomes at the same time as improving the employee experience of J&J's 140,000 employees. The title of today's episode is how Johnson and Johnson uses people analytics to drive business outcomes.

You can listen below or by visiting the podcast website here.

In our conversation Piyush and I discuss:

• How to set up people analytics and engage stakeholders in the business

• Why insight without outcome is simply overhead

• Examples of people analytics case studies at Johnson and Johnson, including one link to the business value of J&J's employee wellness program

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

This episode is a must listen for anyone in a workforce or people analytics role, HR and business professionals interested in how people data can drive business outcomes and CHROs looking to build or scale their people analytics capabilities.

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

Interview Transcript

David Green: Today I am delighted to welcome Piyush Mathur, the Global Head of workforce analytics, data strategy and governance at Johnson and Johnson to The Digital HR Leaders podcast and video series, and we are doing it live in your new offices in New Brunswick. Piyush welcome to the show.

Piyush Mathur: Thanks David. Thanks for having me.

David Green: Can give us a quick introduction to your background and your role at J&J?

Piyush Mathur: I lead workforce analytics, data strategy and governance at J&J. I have a varied background, I did a couple of decades of business experience, leading businesses around the world and then more recently, in the last four years, I have pivoted to HR and started to lead a people analytics function within Nielsen and J&J.

David Green: We are going to come back to why you pivoted as I think that is a good point. So let's start with your time at Nielsen, less so about Nielsen but more about the fact that you moved from the business, as you said, as a business leader, you volunteered to move to New York to start the people analytics function.

So first question is why?

Piyush Mathur: That is a great question, David, and I get this all the time. Many times people tell me what's wrong with you? Why would you move from business and pivot to HR, but people analytics as a function was always close to my heart and I was always passionate about unlocking the power of people and analytics is something that I always did for my clients for over two decades. So when people analytics came to me as an opportunity based in the US and setting up that function, I believed it was my sweet spot. That is the reason I took it on and the other thing that comes to me many times from different people is why would you stay with one company for so long and I spent 20 years with Nielsen different managers and learning from them and that was a big move for me as well.

The other aspect is when I was running a business, I was leading South Asia for Nielsen, I had 3,500 people in my team and when I moved to New York I was the sole person setting up that function. So that was a big change as well.

David Green: So I would be interested in what was your approach when you took on the role? How did your background in the business help? Also how did you select the initial projects that you worked on?

The reason for asking that is, I know that for a number of new people analytics leaders this is something they really struggle with. What should I do?

Piyush Mathur: Yes exactly, you are exactly right, David. My business background really helped because when I got into the role, moved to the US, I did not really know how to set up this function or what are the kinds of things we should be prioritising? The first thing I did in my first week, I met the president of our North America business, and I asked her what was going on with clients? So the discussion was really around the business and she told me that there was a lot of churn and clients were complaining and she wanted to know what was happening and how we could bring this churn down.

She said that she understands her directs and their directs, but she does not really know what is happening in the middle management and when we went back and looked at the data, we saw that the attrition was largely at the middle level and at entry level, and we started working on that project. So it really helped me prioritise for the impact and that is what we did.

So I think initially as you get into setting up a function, coming from leading a large team in to just looking at key projects, it is always good to put the business lens in front of you and go for priorities that are critical for the business.

David Green: So you can have an impact and gain some momentum.

Piyush Mathur: Exactly and get some quick wins when the senior leaders are rallying around those issues.

David Green: And as you said, if you have got a president of the US business, if you do something and do it well then she is going to advocate for you with her peers.

Piyush Mathur: Absolutely and in fact that is what came out of that result, you were able to figure out high risk associates, she got her leadership team to start taking action and then it led to really good outcomes.

David Green:  So other than engaging the business on stuff that is really important to them what are some of the other tips that you would give to a new People Analytics leader? Someone coming in to pretty much start a function.

Piyush Mathur: I mean, David, there is so much to learn from that kind of experience with starting from scratch and not knowing where to go. I would call out three things as I look back, and this was almost 4 years ago, so the first one would be: just get going.

Many times you kind of start imagining, oh I need this kind of tool or I need that kind of data. If you know the gender of your employees and if you have Microsoft Excel you can do people analytics. My first key learning was that whatever we have, we can actually start doing analytics and imagine in that example, if you looked at gender by level you can start seeing where the tipping point is and you can start taking action, to build women in leadership. So that is a simple way of just getting going.

The second piece was to keep building the foundation as you go along. So interesting example when I came in, I think it was my first month, I called my unit from foundation to foresight.

It was a lot about let's build that foundation first and then we will do some foresight work, like attrition modelling, and very quickly, in three months, I realised that foundation is a journey. Right now it is about, let's say Workday data, but as it evolves it will include LinkedIn data. It will include glassdoor data, so this is a journey that will keep going. Very quickly, in three months, we renamed that unit and called it foundation and foresight because you can do both of them.

David Green: In parallel and as long as you identify the right business questions and challenges. And get sponsorship.

Piyush Mathur: Exactly. The third learning was be resourceful in finding resources. So usually the people analytics team starts small, you do not have people. What I realised is that there is so much passion about people analytics, not just within the HR function, but across all functions.

So I think, again, in my 90 days of setting up this function at Nielsen, I realised that there were so many people who raised their hand wanting to get involved in this initiative, and I did not have the resources or the budgets to do that. So what I did was I found a community of people analytics initially all the HR people who were interested they joined in and when I left Nielsen 18 months later, that community was 67 strong. It had people from finance, from commercial, from IT, from data science, all putting their hands up and wanting to really add value for the community. So I think as you start this function, start with that kind of a mindset.

Look at whatever you have in terms of data, keep building that foundation and get going, and then be resourceful around finding resources.

David Green: Great that is some really good advice. You mentioned after 18 months, so you did move from Nielsen and you took on the current role that you have got at Johnson and Johnson, and that was a preexisting function.

So what was your approach when you started the role here? How did you identify the key priorities as well moving forward? I guess from looking at the team but also looking at the work that you are doing.

Piyush Mathur: I can narrate it as a story. I came in, got interviewed by six leaders at J&J and I was going through those interviews, I was reading J&J's credo and I was fascinated by it. Many companies have different things that are on the walls of the company but when I met six leaders, including Peter Fasolo our CHRO, I realised that our credo at Johnson and Johnson is not just on the walls of the company it is in the hearts of people and that was a big driver for me to jump and take the plunge. I came in and this was a four year old function at J&J at that time. I was wondering how do I add value? I set up that kind of a function at Nielsen, but here it was already up and running.

There were 18 people in the team at that time and we were looking at how do you add value? So the best way to understand how you can unlock value for that function is to go and meet the business leaders and HR leaders. In my first 90 days I met 60 plus business and HR leaders and I was fortunate enough to meet our CEO and some of his direct reports and really tried to understand where is it that we can add value as a function.

A couple of themes emerged from those discussions. One was, yeah you do some analytics, but you do it in your shop, you are not focused on my product was one piece. The other piece was, yeah you give a lot of data but not insights that I can action. Now, that is something we have all heard for many many years right? Then the third one was, we were just coming out with our workforce DNA tool that brought all of HR data together. So there was a lot of effort that was done before my time but it was getting close to launch. A lot of people told me that this could be transformational, this can change the face of HR and then Peter Fasolo told me to be careful, do not let this tool go to the graveyard. I think the message he was giving me was, it is not just about the tool it is about really uplifting our HR community to become more analytical and to start working on their analytics quotien as we call it in J&J.

So those were my themes as I came in and on the other side I was having lunch meetings, one-on-ones with all my team members, and I was trying to understand what they were most passionate about, I was asking them the question, what part of your job would you rather not do? That actually told me where their real passion lied. I found that there were a lot of people who are very analytically oriented, the data scientist, people with statistics background and then there was another set of people that had commercial analytics experience, that had HR experience, that were more of the consulting type, so I felt that if we were to give them those dedicated roles I could address the business needs at the same time, structure the team based on passion. So that is what I did in the first hundred days. I went back and restructured the team, we called it advisory services for teams that really go and engage with the business and address their issues. Then we had a modelling and insights team, that really runs the analytics and then we had a survey COE team later on, we got in the data strategy team to work in tandem so those were the initial pieces that we put together, and again like in any function, we found out what were the big business issues and we found that in China we were having a big attrition problem and the regional head of our Asia business talked to us and said that we should be trying to bring the attrition down. So one of the ways we got that going, in the first six months was with that model.

David Green: In terms of the size of the team and how it is structured, you spoke about it a little then, how is the team structured? Is it centralised or do you have people out in the regions as well?

Piyush Mathur: That was one thing that was missing at that time. It was largely a US team trying to do global work. I have lived in the regions, I have led those businesses, so for me it was important to build a global team. So we started expanding. Now we have a person based in France, one person based in Singapore, another one in Brazil and then we have some people that are not part of my team, but are based in the US that focus on analytics.

So we kind of gave it a global view and in terms of the structure at that time, it was more about advisory services, modelling and insights, we had a survey COE team that does all our large enterprise wide surveys and then built another team for workforce planning and org enablement is what we called it, because it was about building the analytics capability within the organisation.

David Green: So let's talk a bit about how the role expanded to include data strategy and governance. How has that increased scope helped the work of the team?

Piyush Mathur: The simple thing about data strategy and governance is to have clean data that is connected. That is it. If you do not have clean data you are making a lot of decisions based on data that is not clean and you lose credibility pretty quickly.

In the last six months we have data definitions that are very clear for about 700 fields. It clearly articulates what is the source of truth, if your name, for example, David appears in multiple systems, we have said this system is the source of truth. So now it is clear that this would be the name that we would have organised in our system.

Then we are connecting the data, so we have created a HR data hub and tested some of our data to flow through that hub. So it is getting interesting with this area as I think it can actually unlock a lot of value because a lot of that manual work should go away and the team is really capable of doing higher value added work, but they are kind of stuck with doing a lot of stuff in Excel and in multiple places and the data not flowing.

But I think this is the power that the technology can bring into HR.

David Green: And presumably helps you with the quality, but also things around privacy and ethics and stuff like that as well.

Piyush Mathur: Exactly right. We are very much in partnership with our data privacy and legal teams every time we look at the data. This is another way of protecting our data and making sure that it is going through the systems, It has all the security checks that are required. So this really helps us to govern our HR data.

David Green: And provides a firm foundation, I love your insight without outcome is overhead, which I have heard you say a few times. You talked earlier about moving from insights providing action and now you are talking about insights actually providing outcome, which is ultimately the most important thing. I think it really resonates and it is something that many people analytics teams do struggle with.

So what are the steps that you take to ensure that the outcomes are realised at J&J?

Piyush Mathur: When I came up with this, insight without outcome is overhead, it was really thinking through that many times as people analytics we come up with insights, we hand it over to our stakeholders and we walk away.

We just expect them to take actions and we did not really know what happened with those actions. Right? So if we are providing those insights, either the actions are not happening or actions are happening with no real outcomes, then all of this was a waste. So that is where we started making sure that if we were to propose any insight we want to follow it up to see what actions were taken and then measure the outcomes. So we are really involved in that end to end journey. And increasingly every project we do we now start to measure the outcomes of those projects. A great example I can give you, this is another thing in HR it takes a little bit of a while before you start to see outcomes.

So in this example, it is an 18 month old example, and it is where we are really seeing outcomes from what we did. So I think I talked earlier about China and how that business was going through high attrition. We quickly dived in, started to look at the different variables, build the model and then one of the things we found is that if you did lateral moves in J&J you would have people stay back longer and perform better. And we found that people are actually doing twice the number of promotions versus lateral moves, which means that we were actually not leveraging lateral moves in China.

So that became an action that the HR team was going to lead. We may measured it through 2019 and we found that in one of the businesses we did two and a half times the lateral moves in 2019 versus the previous year. That brought that attrition down substantially. That really led to millions of dollars of productivity for that business.

So again the insight was lateral moves, the action was actually doing more lateral moves, the outcome was millions of dollars of impact. So imagine if you were to take any people analytics project through that cycle. That is what our ambition is.

David Green: I think it is a good ambition, a sensible one as well.

And it is something that can really help mobilise people analytics amongst executives, which ultimately is what you want to do. And then you can get some more resource, some more of the budget and actually continue growing the team and enriching the work that you are doing.

Piyush Mathur: You know, it is interesting you say that about the executive sponsorship. So this project was articulated and the story was put together and then I was invited to come and speak to our executive leadership with our CEO and all his directs who showcase the story of what is possible.

I think increasingly in people analytics you need such use cases, to build that credibility, where can you take the business? Tell us what you can do? This is like with a real outcome you can showcase what is possible.

David Green: What are some of the areas that you and the team will be focusing on in the next 12 to 18 months?

Piyush Mathur: In our journey I think we have evolved to a level where we are now looking and making direct business impact. So three areas that we have called out this year, which we believe can have a real impact.

The first one is on people experience. So last year we started by setting up our office of people experience, and then we started by segmenting our 140,000 employees. We knew we wanted to be more customised to their needs and the experiences that they are looking for so that is how we started. It is interesting how we segmented this because it was not really based on behaviours it was more around our businesses and our functions, so that every data point that comes in can actually go and add value to each of the segments so we are able to do that. Then we did surveys with those segments to understand what they felt about our digital ecosystem, how good they were with doing transactions in Workday and then really trying to understand their end to end journey and at every touch point in that journey how were their experiences and which were their pain points and moments of truth. So we went through all of that. We have now reached a point where we know exactly where we want to focus on in terms of pain points and moments of truth and we have the team now structured in a way that will really go out and address those pain points.

So I think this year there will be a lot of work in terms of measuring the actions that we took. Are they leading to the outcomes that we want? So that is people experience.

The second one is salesforce effectiveness. So we did some work last year to really look at how can we make the salesforce more effective?

One of our businesses is a $42 billion business, a pharmaceutical business. So imagine that is like a company in itself so how do you enable the salesforce to become a much more effective, and they have spent enough amount of effort in the past with all of the commercial data.

So they have looked at access to the physicians, they have looked at the markets, they have looked at how they are structured, but they have really not looked at the characteristics of a high performing sales rep. They have not looked at some of the HR variables, the amount that a manager spends with a high performer versus a low performer. Does that make a difference in terms of how their sales quotas are achieved?

So we got in with our HR information and put it together with their commercial analytics function and are really beginning to unlock the possibility of making them even more effective.

And then the third one is really around skills. How do I understand the skills of our 140,000 employees? If I can understand them better then I can pay them based on skills. I can develop them based on skills. I can given them personalised content that will be relevant for them. I can match new roles that come up with my own employees. Like all of the that, the foundational piece of skills. So we are doing a lot of effort in this space by asking and inferring skills. We want our employees to go into their Workday Skills Cloud that we will be launching soon and talk about their skills, talk about something that they may have done recently but it is not there in our systems. But at the same time we are also looking at inferring skills, we are doing pilots with a couple of companies to figure out how do I infer the skills of our employees given the digital landscape and using the information I have about them.

David Green: It is a nice fair exchange of value there, so for the employees it helps personalise their career pathways within J&J but for you and the team, it actually helps to support workforce planning and you can understand gaps and start to think about how you might close some of those gaps.

Piyush Mathur: Precisely and it is foundational, you would require those datasets as the business models evolve, and you do more of digital surgery and robotics new skills will be required and you do not know if you do not know what your current base has.

David Green: I think what is interesting is all three of those areas are clearly areas that can have huge potential outcomes for the business.

Because sales effectiveness, if you can improve sales by 1% of a $42 billion business, it is a big number. And then as well those sorts of insights are helpful for sales managers because as individuals it will help them to be more effective with where they should be spending their time. If you can unlock insights about what makes a successful sales person then that helps others to become more successful as well.

So there is individual benefit and there is a huge potential benefit for the organisation. I think we will have to come back in 18 months and see how you are getting on with those.

So if we look towards the future of People Analytics, I think we are at an exciting juncture for People Analytics. LinkedIn have called it out as one of the four big trends for 2020.

They also called out employee experience as well, and I think we both know how closely related they are.

What excites you most about the function moving forward?

Piyush Mathur: I am really excited, in terms of how it can unlock business value. Like we talked about, my past experience, I think bringing in the people analytics perspective into unlocking that value for the business is going to be huge. We have just started that journey, there is a long way ahead of us and we are beginning to see some use cases which are unlocking that value. So I am truly excited about that.

On the other side I am also really excited about what we do for the employee as a function, if we understand their skills and give them roles that they are most passionate about and technology is actually enabling that, data science is enabling that, if that happens and if you are able to do that, we are actually improving the lives of our employees. So imagine David, if you were doing this job that you are doing now and you are so passionate about it, going to all these conferences, putting it all together, you love it, right?

Making that extra effort. Imagine if every employee 140,000 of them were able to do that. Imagine what it does for them and what it does for the business. So to me, I think on one side our function can really unlock that value for the business, but on the other side, it can improve the lives of our employees.

I think as a function, we should be proud that we are improving people's lives.

David Green: Exactly. That nice littlel mix of benefit for the business and benefits for the workforce.

Any concerns about where people analytics is headed or could head?

Piyush Mathur: I think one of the things that I sometimes think about a lot is how do you prioritise for impact?

I think our function will have a lot of demand. Sometimes we will not be able to supply and what are the ways in which we do the most impactful work. I think sometimes we do get bogged down with reporting and just supplying data, but then that creates the perception that you are a data supplier. So how do you make sure that you keep a good balance of all the impactful work. But of course you sometimes have to run those score cards, which are also very important for the organisation. So how do you keep that balance is one thing that I always think about for our functions.

David Green: This leads onto the final question, that we are asking every guest on the show this year, AI and Automation, do you see them as an opportunity or a threat to HR?

Piyush Mathur: David, I am the glass half full kind of guy. So for me this is a big opportunity for the HR function. The fact that AI and Automation can help us to remove these repeatable and routine tasks that the HR function has to do and then for those people who are doing those tasks to upskill them to unlock real value for HR I think is a big opportunity. So for me embracing it fully and making sure that we keep elevating HR is the big clarity.

David Green: And ultimately it helps HR to have more impact with the business and actually be more outcome driven.

Piyush Mathur: Absolutely.

David Green: Piyush, thank you very much for being on the show and for having us here in your office in New Brunswick. You may have heard the odd train go past, lets just  say that J&J's beautiful headquarters is located quite near to the station, so it has been nice to hear some of the trains as well.

Piyush how can people stay in touch with you or follow you on social media?

Piyush Mathur: I think the best way is LinkedIn. I do get a lot of people reaching out to me on LinkedIn and I make sure that I respond to each one of them. So I guess the best way would be to reach out through LinkedIn.

David Green: Piyush thank you very much for being on the show, it has been a pleasure.

Piyush Mathur: Thanks, David.