Episode 24: How McKesson Used ONA to Drive Sales Performance (Interview with RJ Milnor, VP of Talent Management Operations at McKesson)
One of the fastest growing areas of people analytics and one that garners a lot of interest from practitioners is organisational network analysis or ONA, which could provide a fresh lens on how work really gets done in an organisation.
The challenge for companies wanting to deploy ONA is to identify the right use case or business problem beyond the common use of ONA to identify key influencers within the company. McKesson is one company that identified a prime use case. That of understanding what drives high-performance in sales, both from an individual and sales leader perspective.
I'm joined for this episode of the podcast by RJ Milnor who until recently was the VP of Talent Management Operations at McKesson to walk through how McKesson used ONA to drive sales performance.
You can listen below or by visiting the podcast website here.
In our conversation, RJ and I also discuss:
How the workforce planning and analytics team at McKesson is organised in terms of location, skills and where it sits in HR
The role the team plays to support transformation, workforce planning and organisational design
We also talk about how RJ developed a community of practice for people analytics and developed a data driven culture in HR,
We look at the opportunities and risks for the people analytics field moving into 2020 and beyond
As with all our guests on the podcast, we ponder what the role of HR will be in 2025
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 OrgVue to learn more, visit orgvue.com.
Interview Transcript
David Green: Today I'm delighted to welcome RJ Milnor, my good friend and Global Head of Workforce Planning and Analytics at McKesson to the Digital HR Leaders podcast. RJ it's great to have you here.
RJ Milnor: It's a pleasure to be here, David. Thanks for having me on.
David Green: Over in the UK. Can you give our listeners a quick introduction to yourself and your background and a little bit about your vision for people analytics?
RJ Milnor: Sure. My name is RJ Milnor, I lead People Analytics at McKesson, and my background is a little bit of a circuitous path, like a lot of us. I did my grad work in international economics and international relations, and then, my first job was actually on Wall Street. So I was an investment banker on the derivative score.
So derivatives are options, swaps, things like that. Structuring trading, selling those. And it was actually there that I became fascinated by the impact that our workforce and specifically talent strategies could have on profitability. So, can we, for instance, quantify leadership bench strength and look at the relationship between that and profitability or total shareholder return?
And that led me to Corporate Executive Board and the Corporate Leadership Council for about seven years. And, from there, I then started to build and lead people analytics teams at companies like Citrix, Equifax, Chevron, and then McKesson. And so, when I think about people analytics, the mission that we have at McKesson is to deliver better people and business results through data and analytics.
And so if we break that down a little bit. Delivering better people results is really about getting data back to people, giving their own data back to them so they can be more engaged, more productive, have better wellbeing and that leads to better business results. So we're able to help employees be more engaged and have better wellbeing and be more productive.
We can drive better business outcomes and we can measure those things through operating profit, free cashflow, net promoter scores.
David Green: That's great. And you've been in the space for the people analytics space around 10 years now I think
RJ Milnor: The grey hair is showing...
David Green: Yeah. Well, not as many as me. And we met, I think we met first when you were running the function at Chevron, but over those 10 years, what are the some of the main changes that you've seen and developments in our space?
RJ Milnor: So it's interesting you ask that question. When my team and I are thinking about building an analysis or especially telling a story with data, one of the phrases I'd sometimes use is the three Whats. By that I mean what, so what and now what? And I think our progression as a function over the past decade has actually followed that same curve in many ways.
So if I think back a decade or so, first time as a practitioner, we're really in the what phase. So, much of the of the work was understanding what is happening in the current state. I remember in that first role, the Head of HR asked, he said, we've got great HR data. The systems are good, but help me understand what it actually means and how that relates back to the business.
So a lot of that work, I think at that time was data staging and dashboarding, bringing data together from multiple places. Visualising it. And getting it out to the people that needed it to make decisions, hopefully attached to a meaningful story that was business informed and business relevant. I think a lot of us are still in that place, and there's nothing wrong with that.
It's meaningful work. But as time kind of shifted, we evolve to the, so what, and if I think about the so what, there are maybe two parts to that. One is moving from reporting to analytics. Clearly differentiating those two things and separating the teams, so saying there might be a reporting team. Sometimes that's in HR operations or somewhere else, and an analytics team that's not focused on the data so much as transforming that data to answer a specific question. The second part of the so what, is connecting the people data with financial or operational data to really show the business or financial impact of the analysis or the people's strategy.
And so that's the second piece. We have the what, we have the so what. I think what we're evolving toward now or very recently is the now what. And with the changes in technology and the available data, and then the approaches, machine learning, deep learning, AI, all the buzz words that we hear about, we're actually able to get some predictive scenarios of what may happen next, the probabilities associated with those things and deliver scenarios and potential outcomes to our HR partners and business leaders. And that's where I see the most value right now is in delivering those types of things.
David Green: I suppose that translates to you're a manager in the business or an employee or worker. And actually you get the data to you and it tells you if you do this, you could expect this to happen. You know your team will be more productive or you will be more engaged. And this is how it translates through to business results. That's the ultimate, I guess, those little nudges that make those behavioural changes that can really have a big impact on the business.
RJ Milnor: That's exactly right. And something we're exploring right now is that idea of nudging. So think about employee surveys and employee listening is a great example of this. So in the not too distant past, we would do an employee survey, maybe that was every year or maybe every several years, and that would lead to an action plan.
So, you know, we have an action plan. It takes a while to cascade down and we're saying thank you very much for your feedback. I'm not going to give you this other work to do. Just build up this action plan. Action planning isn't going away. We still need to do that from an organisational perspective, especially for larger, longer scale activities.
But if we can give an individual employee or specifically a people leader, information that's actionable and in the moment to drive that engagement or drive that wellbeing or productivity for their employees. That's wonderful. So that's something we're absolutely thinking about right now and actually doing.
David Green: Which leads on very nicely to your current role at McKesson , what are the key responsibilities of your role and the reason I'm asking that question, there's a lot of people ask me who aren't in the field, say what does a head of people analytics or workforce planning and analytics as it is in your case, what do they actually do?
RJ Milnor: Let me tell you or describe what's in the team, and I can describe what I do, which is a little bit separate actually. So in our team, we have workforce analytics, so transforming data to solve those challenges. We've got workforce planning, we're increasingly doing work around employee surveys. We're increasingly involved in pulsing and nudging. We're increasingly involved with data privacy and ethics and so the team does fantastic work along that, Where I spend most of my time is making and building connections. And that's really most of my work. And so there are really three aspects of that.
One is spending time with the business. So understanding, speaking with business leaders and those in the business, understanding what they're doing and making the connections back to people strategy and thinking about, well, what type of analysis might be helpful to either improve the work for our employees or drive business outcomes.
And that's a bit of scoping, but it's also demand generation. So there's a significant marketing aspect in my role, and that's not to kind of beat the drum for people analytics at McKesson it is really to help facilitate the business. And that's a large part of the role and it develops a much stronger partnership and relationship with HR and with all the different functions and business units. So that's a really important part of what this role does. The second is developing connections across the team. So we have team members with different levels of specialty and in different locations, connecting them and connecting them with different parts of the business to get things done.
And that's something I take really seriously. Where I spend a good part of my time, maybe most of my time is connecting my own team with development. So if you think about one on one coaching, specific development activities, career coaching and career building, that's also a large aspect of my role.
David Green: And I guess this is where your background in consulting helps, cause the role of the consultant or the translator as seems to be the common terminology that's used, is so important in people analytics.
RJ Milnor: It is, I think it's one of the most important things. And so there's the element of doing the actual work, the analysis.
We try to centralise that as much as possible to get scale out of the analysis. But then translating that back in a way that's meaningful, cause you can have the best analysis in the world, but if it doesn't resonate with the customer and if it's not business relevant to them, it's likely to just sit on the side of their desk or worse yet go in the dustbin.
Right. So that consulting piece is important. What we're increasingly finding is to appropriately scope the work. That consulting skill set is so important as well because we need that understanding of the business and why it's important to them. And to make sure we have it, we have it set up and the research setup appropriately.
David Green: And develop the hypotheses and get down to the right level so it's the right questions rather than maybe the questions that could be at the top level, really drilling down to the...
RJ Milnor: It's a fantastic point and I think we've seen examples of that recently and I'm very proud of the team for identifying that where we might be given a question or hypothesis, and we realise, you know, that's a surface level problem. It's a real problem. And our clients and the business are feeling real pain. But if we take a moment to actively engage with the business or the functions coming to us and work it through, we can pry that back and realise that the root cause might be three or four or five levels down. So it's a classic example of root cause analysis, but it takes that consultative approach of slowing things down a little bit, not being reactive and really partnering with the customer to understand what might be wrong and we can get so much more impact when we do it that way.
David Green: That's brilliant. We're going to come back to some specific examples to some of the work that you've been doing McKesson a bit later in the discussion. You've talked a little bit about the skills and the team, how is the team organised? I think you've got a blend between centralised and actually out close to the business as well, which I think is quite important. And also where the team sits within HR as well.
RJ Milnor: Sure. Yeah, absolutely. So we operate in a centre of expertise or COE model, and it might be helpful if I give you the historical context and then we jump into this.
David Green: Definitely.
RJ Milnor: So when I came into McKesson about two years ago. We had a centralised team that sat in corporate HR. And there were also very talented people doing this work, doing people analytics work, spread across the business units and functions across McKesson. And they were doing fantastic work but what we realised was because they were disconnected and not communicating, we were oftentimes reinventing the wheel. So the same work was being done kind at different times, unbeknownst to one another. Sometimes we were using different tools, sometimes different data definitions, different data approaches.
So it wasn't as efficient as it could be. And what we decided to do was identify these individuals and bring them together into one COE model. And what we've found is that not only is it more efficient, we're better able to service the business. But by bringing everyone together and having them communicate and share ideas, we're able to accelerate innovation significantly.
So the way that we're organised is as a, what I call a hub and spoke. And I think the way I think of hub and spoke is sometimes different than how others think about it. So it's probably useful for me to explain a bit. In the hub, we have talent that can scale across the enterprise.
So think about data infrastructure, data engineers, platform architects, and product specialists. So workforce planning, for instance, sits in the hub, and these are all things that we can, they're enterprise wide projects or things that we scale across the entire company. We have workforce analysts that are designated to support specific business units or functions that actually sit in those business units. They're embedded, but they direct line into the COE. and that gives us tremendous insight into what's happening in the business units. It gives us business units, dedicated support, or at least designated support, but then we can understand and share kind of what's happening across the enterprise and also standardise as much as possible.
And one of our mantras is that we want to standardise or create commonality, where we can, so we can differentiate where it's really important. We don't need to be differentiated everywhere. Yeah.
Presumably by being embedded in the business and that gives you access to stakeholders, but also access potentially to business data sources as well.
That's exactly right. And so we can bring those things together and actually create some commonality in those data sources. And what we find, but maybe not surprisingly, is that the businesses aren't as different as, as we might think, but where there are differences, they're extremely important.
And it's very helpful for us to understand what those differences are so that we can tailor to those and respect those things. But we can create a layer of standardisation as much as possible across the enterprise.
David Green: So I know from previous discussions that we've had over the last year or two years during your time at McKesson that you're undergoing significant business transformation there at the moment.
What I was wondering because lots of companies are going pretty significant business transformations at the moment, is what does that translate to from a people perspective and some of the work that the team gets involved in.
RJ Milnor: That's a great question, David. And so we are going through a significant business transformation, both to better serve our customers and to react to a changing market landscape.
So in the US the healthcare landscape is shifting pretty significantly. I think it's an amazing opportunity for people analytics to add value. If you think about, in our case, business transformation involves two big changes. One is an operating model change. The way the organisation is structured and the way we do business.
The second is in our growth strategies. So where are we focusing and what areas are we planning to grow over the foreseeable horizon? And if you think about those two elements of a transformation. The way that we're structured and do business. And also where we focus both growth and foundational capabilities. That is tailor suited for both HR and specifically people analytics to add value.
And so I think we're very fortunate to find ourselves in this position and to be part of so much change happening so quickly and in a very large company like McKesson. Specifically, to answer your question about, what are we doing? There are a few things that I think are really exciting actually where we're adding value. One is workforce planning.
And so we've just started workforce planning at McKesson. We have not had that in McKesson's 185-year history. And so that's a fun thing to get off the ground. And when I think about workforce planning and its impact on transformation, one aspect of it is just understanding the workforce that we need in terms of capacity, capability, cost, timing, location to execute against our strategies.
But another very important element when it comes to transformation is the capability piece. And you know, second, of the ones that I mentioned. So if we're trying to execute a specific strategy, what capabilities do I need to do that? If it's three years out, five years out, whatever the timeframe might be.
Do I have those now? When I look at my workforce now, and if I don't, how do I get there? And which of those capabilities is highest priority in terms of business impact, in terms of scarcity in the labour market? So that's a fantastic and really interesting body of work. It's moving quickly.
The second is pulse surveys. So we're moving increasingly from a once a year model of getting employee feedback to a much more frequent and agile, forms of feedback. And I think that's particularly important during a business transformation because things are happening so quickly and employees are going through so much change.
It's important for us to understand how they're reacting to that change, what their perceptions are so that we can communicate with them effectively and make changes if necessary on our side. And once a year just doesn't do it. And focus groups, as good as focus groups are, sometimes don't give us enough scale or representation. And so that's been an important element.
Nudging. You mentioned, we mentioned earlier is also I think very important during a transformation and that much like pulsing, we're able to react much more quickly with a nudge and apply more science to the approach with nudging.
And I think the last thing I'd mention is, an a very important thing to end on is diversity and inclusion. So as we're going through a transformation, one of the things that we want to understand, for instance, is more about intersectionality. We also want to dig deeper into inclusion and senses of belonging. And we can do that through multiple different methods and also do some forecasting around diversity. And here's what we look like now as we make certain changes, what might we look like going forward? And do we need to make any changes because of these forecasts? So it's a really fascinating opportunity in a transformation to affect meaningful change for employees and also for the business.
David Green: Brilliant, and interestingly the example we're going to talk through now, which is something that I saw you present at the Wharton People Analytics conference earlier this year with Manish Goel of Trustsphere and then subsequently at UNLEASH as well in Las Vegas in May, was how you're using network analysis.
And I think it was the first time that you'd used network analysis at McKesson and initially I think you were going to use it for something I presume that was very much linked to the transformation around identifying key influencers, in the end when you actually got the toy. You decided to use it for something else. And I know our listeners would love to hear a little bit more about that.
And so it would be interesting to talk about. So what did you actually do with it in terms of the projects and scope and what were the business challenges that you are trying to tackle and maybe some of the hypotheses that you maybe had before you did the analysis.
RJ Milnor: Sure. That was a fascinating experiment, David. And it did change as we were moving through it. And so as you mentioned, we at McKesson, we had never used network analytics before, relationship analytics, and so we did this as an experiment to test some hypotheses we had, which I'm happy to talk about.
But also the validity of the method, just because we honestly didn't know what we would get if there was anything there. And we wanted to test that in an experiment or a proof of concept in some ways. So you mentioned transformation. A lot of times, one of the reasons why we were interested in network analytics is that many times when we see it done in the marketplace, there's fascinating work and it's focused on say, influencers and brokers.
And we identify these influencers from brokers to understand how we might have shaped the organisation to be more agile or adaptive. And there's fascinating work in the marketplace on that. As we're going through our transformation. We initially thought, well. We might do this to help facilitate communication in regard to our transformation. As a lot of the communication to that point was either blast communication to all employees or a cascade, and if we could identify groups that were influencers or brokers, we might be able to communicate more effectively through these networks and advocates.
As we started to think through the structure of what network analytics is. And we did something called passive network analytics. So using email data, I can talk a little more about that as we get into it. What we realised was we had a better opportunity to provide, really meaningful data back to employees and to the business and strengthen McKesson's culture by combining this network data with business data.
And bringing these two things together. And those were really our motivations was how can we give data back to employees. To improve their engagement and productivity, really help them be better at what they do by giving data back to them. And then how can we help inform the business by bringing this data together, network analytic data combined with business data.
And so we started to look at business data as, as an example, sales performance and employee turnover. That changed our thinking quite a bit from just looking at influencers and brokers and using this to facilitate communication, to do something that we thought would be much broader and have meaningful impact in terms of operating profit.
So, what we did was we developed three hypotheses. One was, do high-performing sales teams build relationships differently than low performing sales teams? Is there something about the way they build relationships, external versus internal, for instance, that is both in common and differentiated.
Cause if we can understand that, we can teach it, right. And that can have a meaningful impact on gross profit. Secondly, Are high turnover teams different than low turnover teams. So is there something about their relationships that might be indicative or predictive of turnover.
And third we wanted to look at post-merger integration. So McKesson does a lot of acquisition activity. We're very fortunate to do that. But we want to know are the employees that, that come with an acquired company, are they actually integrating into McKesson or are they staying ring-fenced?
So the way that we went about it was this passive approach. We looked at, de-identified, email data. So when we think about what that is, it's email metadata, or log data. So this would be, sender, recipient and timestamp.
David Green: And it's not content and you talk about how you anonymise it.
So you can...
RJ Milnor: Yeah, thanks for pointing that out.
David Green: It's one of the concerns I think people have about doing this, and I think when you actually look, you can quite easily put the protection around that you need to put around.
RJ Milnor: I think it's really important to bring that out. And there's certainly articles written about this type of thing.
We wanted to make sure we're giving value back to employees and the company, but we also really want to respect the privacy of our employees at the same time. And not look at data that's not relevant to what we're trying to measure and so, you're exactly right. We're not looking at content.
We're looking at just the log data, that exists, or email logs, and it's the sender recipient timestamp. And that's how we understand connections and relationships. So, as an example, David, I send you an email and then you send me an email back in say 30 minutes. So through that we have a connection.
Now over maybe 10 days. I keep on sending you emails, and you keep on sending me emails. Now that shows a relationship. And over the span of an analysis, what we'll see based upon how many emails are sent and the frequency of response, and also how quickly people respond is the strength of those relationships.
So we're looking at connections, relationships, and strength of relationships. And what we did over a hundred-day experiment was monitor this information to understand the connections and relationships and compare that to some business data. And we ran this as an experiment for a hundred days and believe it or not collected over 130 million emails in that process.
So there's this tremendous volume of data. Yeah.
David Green: The difference between passive network analysis and active network analysis, which is predominantly survey based, is the volume and the scale that you can do this at.
RJ Milnor: That's exactly right. And actually, one of the cautions is that you can easily boil the ocean, you have so much data.
So it's really important to go in with some clear hypotheses that you want to test.
David Green: So what were some of the key findings?
Cause I know they're pretty interesting findings actually, which really resonated with the business.
RJ Milnor: Yes. So I think one of the biggest key findings for us is that, network analytics can predict business outcomes.
All right. So, which was, and again, going into this, we didn't know what we would find. So much of it was validating the approach, but we saw distinct connections between business outcomes and some predictive validity there as well. So if I kind of break it down.
I think one of the first things we realise is when we send a lot of emails, so there might be something in there that we should look into. But going through those hypotheses, the first thing we realised was that the more effective sales teams have stronger, more balanced relationships.
So a question we had going in was, well, are the best salespeople, the top quartile sales teams do they have stronger external relationships and they just know everybody, or they have stronger internal relationships. They really know the people internally to get things done.
And it was both. You really needed to have a strong network, but as a balanced and strong network. The other thing we saw within the sales experiment was that, the networks of high performing sales reps were different than sales managers and sales managers actually, if they were high performing, had stronger internal networks.
So it's a little similar to individual contributor versus people leader in some ways. When we shifted to turnover, high turnover teams, and again we were looking at teams and groups, not individuals. When we looked at, high turnover teams, their relationships tended to be stronger up and out of the organisation.
So very strong relationships, externally, strong relationships internally above them in the hierarchy, but there are meaningful gaps, peer-to-peer, and then down the hierarchy. And so very useful for us, it was extremely consistent across high turnover teams. And so that's useful for us in terms of both predicting or diagnosing where turnover may happen.
Based upon relationships, but we also can mitigate that. And we can talk about that maybe in a little bit. And then we looked at post-merger integration. So we wanted to understand, are employees that come to us from an acquired company, are they actually integrating into McKesson?
The answer that we found was, yes, typically within about a one-year period. And so that was also a useful finding.
David Green: And you said you could go back to some of the things that would mitigate against the attrition part of things. It'd be good to hear a little bit about that as you dangled the carrot.
RJ Milnor: So I hooked you. One of the things that we're investigating right now with turnover is, first we're continuing to kind of validate that relationship. Is it what we think it is? And it certainly looks that way. But we're exploring whether we can use flexible workspace to close some of the gaps in peer-to-peer and downward relationships.
So if you think about, and again, this is, we are in very much hypothesis mode, but if you think about a fixed workspace environment, that can create literally walls, you know, between individuals. We have some workspaces that are inflexible environments.
We want to understand, can we use that to facilitate more collaboration, peer-to-peer? And if we do that, are we seeing differences in those networks? And are we seeing consequent changes in turnover behaviour? So that is one thing we have underway. We're also working on the sales front to see if we can teach and train those behaviours and build those in, to create lift in sales.
I think there's, there's lot of opportunity here.
David Green: And what was the reaction of the business?
RJ Milnor: Surprise, in terms of what we're actually seeing. So I think there's... One of the things that we typically see with, or that we've heard from some of our colleagues is network analytics, gosh, it's hard to get traction on this.
And we were fortunate to be able to run this experiment and put some hypotheses together. I think the surprise for the business was, wow, that's more meaningful than we thought. So now what we're doing is we're working to the process of scaling this out. And that's part of the fun, but I think there's... We are seeing more and more opportunities to leverage the data.
So we mentioned turnover, sales, increasingly we're looking at other opportunities, whether it's using this to understand diversity and inclusion and create even better senses of belonging. We're seeing opportunities with real estate and facilities to understand the relationship between facilities design and collaboration.
So it's almost like when you look at this and you look at the opportunity that it poses, you end up seeing more and more opportunities. And from a... it's sometimes hard for me to suppress the original investment banker in me. There's the fixed investment, but you're getting the, you keep on getting the incremental benefit out of this.
So there's an economy of scale that happens.
David Green: Well, so I was just saying, from, you know, doing an experiment. You know, which might have failed, one hundred days, you've opened up a window to a whole land of opportunity potentially, that you could do much further and deeper analysis on, which can really benefit both the workers, whether they're sales people, sales managers, and obviously the business as well.
Because the great thing about sales is it's quite easy to see, there's not such a gap to get to the actual business value out of this is there?
RJ Milnor: I think it's a great point. And one things that excites me about this is. Can we look across an entire enterprise to get data?
And let's say it's passive data de-identified and we're seeing trends, right? So it might be trends of a high performance sales person and might be trends of something else. And so that helps us understand the patterns that exist. At the same time, can we give an employee back their own data in a way that's specific to them?
And I don't need to see that from the centre, right? But if I can show, for instance, if I can show an employee what a high performing sales team looks like, and I can show that same employee in a way that's confidential for them, what their network looks like, and then provide supporting tools, whether it's training, whatever it might be to help them close gaps that they see fit. That's meaningful value back to an employer. And so that's kind of what we're chasing after is leveraging data that can drive business performance, but that can also give employees meaningful value, based upon information they're giving to us.
David Green: So RJ I know this is something we've spoken about quite a lot. One of the biggest challenges that we come across at Insight222 when we're speaking to clients is the challenge that they have in developing a data-driven culture across HR, and also that desire from the business as well.
I know you did a lot of work at this in previous roles. I'd really like to understand what you're doing at McKesson to help drive this?
RJ Milnor: Yeah. I think this is foundational. So thanks for asking the question because if we don't have a data driven mindset in the HR function. It's very difficult to execute against any insights that an analytics function creates so it's so important to create, and I think people analytics functions serve a very important role in doing this.
We are in the midst of an HR transformation right now, in part with our business transformation. And we realised there were five key capabilities or mindsets that were essential for the HR of the future at McKesson. One of those five mindsets is what we call data mindset so that, we are partnering in people analytics with our talent management function at McKesson to develop this across HR because it is so fundamental for HR adding value, and for us it's, it's essential for us to be able to execute against our work. When we think about, so what does that look like? What does developing data and analytical skills look like for HR?
It's certainly not the kind of curriculum I would build for a people analytics team. And I don't need them to be, or I don't want them to be analysts. But what I do want for HR is to think analytically. And that's different. It's to certainly understand the data and understand the way the data moves.
But really to take a problem and start breaking it apart. And so root cause analysis is really important and problem identification. And the way that we are tackling data mindset is really through three pillars. One is through executive sponsorship, so making sure we have clear sponsors, certainly I, I might be one of those, but also in HR, outside of HR that are supporting the importance of this. And then we're also providing messaging and consistent messaging across those sponsors. Working this into town halls, into all HR communications, about the importance of data mindset and what that is. We also actually built a curriculum. It's now on our LMS, our learning management system, that's a series of courses to build data mindset. And we're at what I call it, the 101 level. We're layering 201s and 301s into that, and we'll be doing that over the next 12 months. But that 101 is broken down into three key capabilities. Data fluency. So understanding the data, what metrics do we use, why do we use them? Key kinds of statistical approaches, not anything deep. The second is storytelling, and we talk about that a lot. And then the third is analytical thinking. So we were just talking about a problem identification, root cause analysis.
David Green: So if we move now, we look at the discipline in more general terms. So obviously been in people analytics for 10 years. You're doing some great work and have done some great work over that time. What excites you most about the discipline moving forward?
RJ Milnor: Yeah. So it's an excellent question.
There are two things. One is that in people analytics, we have, I think a very unique opportunity and ability to effect meaningful, positive change for the employee. So if you think about their engagement, their wellbeing, their productivity, we can affect those things in a dramatic way by the insights that we create and the activities we influence.
And that's a powerful thing and a big responsibility, the second which comes from that in many ways is the opportunity to impact the business. So a lot of our work, most of our projects, at McKesson have an annual operating profit number associated with that. If we do this, we're likely to influence this much of incremental operating profit, that's significant.
And so we have a real ability to partner with the business and help lift the business. But doing so in tandem with a lot of things that we talk about as a community in terms of being, helping our employees, making sure that they thrive and that we're being socially responsible in the process.
And when you put those two things together, that's a powerful and motivating thing. And it requires a lot of creativity too. So those are some things that excite me about it.
David Green: And I think with the recent announcement from the business round table of 181, I think it's 181 CEOs, and the talk about investing in employees.
I think this is more than PR. We shall see, I guess, from some of those organisations. But really the promise for people analytics out of this is huge.
RJ Milnor: It is. Our CEO signed that, and it's something that we very much believe in as a company and that we certainly believe in as the people analytics team as well.
David Green: Which is great. And I think that's the way society is going. Everyone's been talking about changing employee expectations. I think businesses just have to do more now, than just deliver profits. And clearly you guys are on the road to doing that, which is fantastic. So again, looking at the field, what is your biggest concern for people analytics?
RJ Milnor: So I have two, and I won't go more than two. The first is that in the pursuit of what is interesting, we become irrelevant. And hopefully that's not too strongly worded, but, there's some amazing work happening. There's truly amazing work happening across people analytics functions.
There are occasions and they're typically rare where I really struggle to see the connection between the work or the study and the business strategy or business outcome. And I think while there is room for us to be creative or to pursue things that aren't directly related to business, we run a risk when we do that.
And then we certainly run a risk when we do that too much, because many times for many of us, we are part of for profit organisations. And so I think we need to, we need to balance that, and ensure that we're delivering value back to the business. Now, value comes in different ways, like we just talked about.
There's a social responsibility element, and there are many others, but, but that is one risk I think we just need to be cautious of, or at least visible to.
The second, I think by far the bigger risk in my mind is that we mess it up. And what I mean by that is we are running really quickly.
So the field is moving fast. We are pushing boundaries and in a lot of cases, we're creating entirely new ground. And as we do that, we need to be cautious and very thoughtful of the decisions we make, especially with new technology and especially as those new technologies affect, both our policies as they come up against regulations and as they affect our employees.
And so it's something that both I am and our team spend a lot of time thinking about. So, there's a classic, you can, but should you kind of questions where data, privacy and ethics really come in. But, how might something impact an employee's life?
How might it impact their career growth? How might it affect, from a technical standpoint, other systems? How might it affect how the business runs? So I really want to make sure that we take the time to slow down when necessary, on some of these areas. And that's just something that we're very thoughtful about.
David Green: Well, it's interesting when we were building the business at Insight222, one of the things we wanted to do is understand from our clients, what were their biggest challenges? And the biggest thing that came back, and it was just before GDPR, so may have been linked to that, was ethics in doing the right thing, as you say, and making sure that we're future proofing our people analytics functions from doing the wrong things or being asked to do the wrong things.
So we co-created that ethics charter, which I think you were probably involved with and it's almost, I see the people analytics teams are almost like the guardians of doing the right thing within their organisations, and part of our role is to educate our colleagues in HR, but also our business leaders about, as you said, doing things, taking the time to make sure that we're doing the right things.
Thinking, actually, about the transparency. You were talking about with employees, if we can't articulate this to employees and really should we do this?
RJ Milnor: Totally agree. I think people analytics plays a very important role, if not a leading role in that because of both the familiarity with the data and the view across the enterprise in many cases.
And that, we will see things and see potential impacts and have relationships. We're talking about building connections, right? We have a visibility that, that many other parts of the organisation might lack. Other parts of the organisation are expert in what they do, but they may not be able to see across as easily.
This is honestly one of the learnings that we have, we were talking about network analytics earlier. One of the key learnings is just how valuable transparency is. Even in something like an experiment or proof of concept when we're validating a scientific method.
Our go forward approach is to communicate and be transparent with employees in all of these types of activities, because there's no reason not to. The employee, I think, well, we know has a right to see their data, but they should know what's happening with their data and what's in it for them.
I think that is a kind of a mandate we all should have going forward and there's benefit for the organisation because we may learn things from employees in just that communication that helps us use that data in a better way.
David Green: Perfect. Well, we're coming to the end.
This is a question that we ask every guest on the show, and you can be as creative as you want to be, and you can go beyond 2025. Looking forward, we're only looking forward just over five years. What do you think the future role of HR will be in 2025?
RJ Milnor: Oh, I love this question.
It's such a creative one. So when we look at HR now, and I think historically you might think of HR as the custodian of the workforce. We work with our workforce, our employees, create the right tools and policies to drive productivity that helps us win in the marketplace. Going forward, I see HR as being the custodian of work, and what I mean by that is looking at the body of work that's happening across the enterprise and understanding how to allocate that work to the appropriate channel. And so it becomes slightly less employee focused and much more work focused.
And let me give you a few examples. Right now, I think most of us should have a good sense of what our employee base looks like. Maybe our contractors as well. We may have a good sense of the projects that are happening across the enterprise. I think it's a lot more difficult for many of us, but we've got very little insight into the Corpus of work that's actually happening across the enterprise.
So where I see us moving and where I can aspirationally hope we move is having a much clearer understanding of that full body of work, being able to plan for that work and then being able to help allocate that work to different places so that it can be done more efficiently. Now, one channel is the employee, and I think it will continue to be a very important channel.
But we also have contractors, freelance work, certainly automation, which we talk a lot about, whether it's bots or AI, freelance work. It could be crowdsourced, it could be sent even to customers to do. And so if we think about how HR is going to be the arbiter of that. Of helping get the work to the right place to be the most efficient.
That's for me, a very compelling vision. And as part and parcel of that, we can then think about, within any one channel, what can we do to optimise that, to make sure that that channel has what they need to be as engaged and productive as possible. So if you think about the employee channel and certainly employee experience, these types of things, that we talk about a lot right now, become absolutely critical, but there can be other channels that we may not spend as much time focusing on now.
So contractors or freelance, that we might really want to in the future. and I think they can add a lot of value to both our extended workforce, but also to the business.
David Green: RJ that's a great answer, and I think it shows it that actually the future for HR is a lot brighter than some doomsayers would say.
I think it's a great function to work in at the moment. Thanks for being on the show. How can people stay in touch with you?
RJ Milnor: LinkedIn is a great way to get in touch to me, so if anybody has any questions or would like to connect, feel free to connect with me on LinkedIn.
David Green: That's perfect, RJ thanks. Thanks again.
RJ Milnor: Pleasure to see you, David.
David Green: It's always a pleasure.