In this episode of the Digital HR Leaders podcast, David is joined by Aashish Sharma, VP of Workforce Intelligence at Raytheon Technologies.

As the founding leader of the workforce intelligence function at Raytheon Technologies, Aashish has seen first-hand how the field of people analytics and HR has evolved in the last few years. This is where the ‘workforce intelligence function at Raytheon was born.

In this discussion, expect to learn more about:

• The evolution from "people analytics" to "workforce intelligence"

• Productising people analytics at scale

• Organisational challenges and guidance for aspiring people analytics leaders

• Supporting a company through mergers and acquisitions

• Positioning workforce intelligence during cost-saving measures

• The impact of M&A on workforce planning

• The future of people analytics with AI and machine learning

Overall, this episode offers valuable insights for HR leaders and people analytics professionals navigating organisational transformations and building impactful workforce intelligence functions.

Support from this podcast comes from Charthop. You can learn more by visiting: charthop.com/digitalhr

David Green: Joining us today is a true visionary in the field of people analytics, Aashish Sharma, VP of Workforce Intelligence at Raytheon Technologies.  Back in 2016, Aashish founded the people analytics function and since then, due to its impact and the business value it has generated, the team has grown to an impressive size of around 45 people.  Aashish reports directly to the CHRO and is part of the HR Executive Team.

From inception to what it is today, Aashish has been at the forefront of shaping the evolution of Raytheon Technologies' Workforce Intelligence team.  With a focus on productising and scaling people analytics across the enterprise, Aashish has also successfully navigated the challenges of supporting Raytheon Technologies through mergers and acquisitions, while simultaneously building firm foundations in place for the future.

In this episode, Aashish and I will be exploring how he scaled his workforce intelligence function, while supporting the organisation during major transformations.  We'll also delve into the strategies, best practices and lessons learned from Aashish's experience and the increasing role AI and machine learning is playing in people analytics.  So, without further ado, let's get the conversation started.

Aashish, welcome to the podcast, it's a pleasure to have you on the show.  Before we dive into the conversation, please could you share with our listeners a little bit about yourself and your role at Raytheon Technologies?

Aashish Sharma: Yeah, thank you, David.  First of all, I'm delighted to be here.  So, I lead the Workforce Intelligence COE at Raytheon Technologies, which includes people analytics, workforce planning, as well as intelligent automations in HR.  I've been with the organisation for close to 15 years now; started in what was called the HRIS function, and then moved on to create the workforce intelligence function from the ground up.  And, prior to Raytheon Technologies, I spent a few years in consulting, helping organisations with data and analytics solutions.  So, I love the intersection of strategy, technology and data, and that's where my passions are.

David Green: And you've obviously been in the analytics, or around the analytics space, for quite some time, and you've obviously seen it evolve a lot during that period?

Aashish Sharma: Yeah, tremendously, more so than I would have thought, and I'm sure you would agree, it's been remarkable how the space has evolved.

David Green: And as you said, Aashish, you were a founding leader of people analytics, or Workforce Intelligence, as I should properly call it, at Raytheon Technologies, and back in 2016 I think you started the function.  So, in those seven years, you've grown the team to I understand around 45 people.  Looking at it from the lens of a founding people analytics leader, how have you seen the function evolve over the years to what it is today?

Aashish Sharma: Yeah, David, like we just talked about, I think the space has evolved more significantly and remarkably than what I would have expected, and when I look back to the time we started back in 2016 to where we are now, I can think about a few dimensions in which things have changed rapidly.  I think first, when I think about the business impact and value that solutions coming out of people analytics are actually adding, they've matured remarkably well, there is a lot of business demand and absorption of the solution, so the use cases have really proved themselves out well.

I remember back in the day, we were doing a little bit of the selling, right, "Hey, we should try this, we should try that".  But now, I think the maturity of the solutions and the acceptance from the business --to take a good example, such as business decisions such as location selection, or being able to forecast workforce gaps; or even, certain organisations who are able to drive better profitability or growth by linking people data to the sales data, or operations data, or financial data, I think that is probably the most remarkable development in the function, which is actually great news for the function.

Then I think about the pace at which the data and technology has evolved in the space; and what that has done to the expansive nature of work that the people analytics groups are now doing has been significant.  Earlier on, when we started, it was much more around employee life cycle measurement, like you want to measure attrition, you want to measure engagement.  Now, you've got data that is being collected and tools that are available that are helping us understand even the effectiveness of our own HR programmes.  Even for us thinking about, "What does the staffing for a recruiting function need to look like?" there is so much data that we can use to inform HR programmes and strategies, which again speaks to the evolution of data and technology and the scale at which the solutions are touching stakeholders.  Earlier it was HR was the primary stakeholder, now you can just this giant leap in just the stakeholders for people analytics.

Finally, one of the most exciting developments for me that I look back and now I see is just the level of talent that is available, and the career paths that have taken shape in the place.  It used to be a little bit of a niche space, a boutique function; even a role like mine was really not something that organisations had in place.  So now, seeing people analytics professionals really get themselves educated, there are academic offerings in the space, there are true careers that people can make out of this, so it's absolutely remarkable how the space has grown.  And I'm sure you do this a lot and you would agree with this, I still think we are in the early stages of the growth of this function, I think there is a lot of goodness ahead.

David Green: Yeah, I'd agree, I think there's a lot of ramp still to go.  But I think particularly if functions focus on what you've highlighted there, number one, business impact and value, that's really what a people analytics function should be there to do, and we'll talk about some of the research that we've done at Insight222 during our conversation.  But ultimately, those workforce intelligence teams or people analytics teams that focus on delivering back to the business are ones that tend to have a bigger impact, get more investment and everything else; and the data and technology, as you said there, how it's changed and transformed in the last six or seven years is quite significant, and obviously I guess what that allows you to do is scale, plus bring myriads of different data sources together.  So as you said, it's gone from looking at the employee life cycle to something far beyond that.

Now, I suspect some of the people listening have probably thought, "People analytics, workforce intelligence?" so now we're going to get to the crux here, I think, Aashish!  So, you've named your function, Workforce Intelligence.  Now we've talked about this before, but I'd really love you to share with listeners what prompted this naming and this branding, rather than people analytics, or workforce analytics, or any of the other names that you could have chosen?

Aashish Sharma: Yeah, this is a really fun question, David, and I want to say there is actually a lot of thinking that went into the name.  So, when we started off in 2016, the function was actually called, HR Analytics, and we were in the very early stages of even separating between reporting and analytics, and just starting to figure out what analytics would look like.  And in the first three years of doing this, we grew our capabilities and talent and solutions pretty rapidly, because we were going through a large HR transformation at the time, which brought significant investments and support from the leadership on scaling analytics.

Three years in, we grew our capabilities significantly in a way that we started doing a bit of a step back and said, "Hey, what should we look like in the next three to five years".  There were a couple of really important teams emerging that we were seeing at that point.  One was just the strong emergence of machine learning and a little bit of artificial intelligence.  The other thing that happened was, we picked up intelligent automations work as part of our portfolio.  So now, we were really trying to do work that was "beyond" analytics purely.  It was helping enhance effectiveness of our programmes.

So, we ran an entire session where we revamped our value proposition, we got the team together and redefined our mission, and part of it was naming.  So, we went through a lot of different options and the team really settled on Workforce Intelligence as the choice, because it brought together the emerging teams that we were seeing, the work that we were seeing.  And to make it even more compelling for us, right around that moment, we also saw it going through the big merger between United Technologies and Raytheon, and the team at Raytheon was already branded Workforce Intelligence.  That gave us an even more compelling reason to do it, and culturally for us it just felt like the right brand.

David Green: And I think one of the other things that you've done, and certainly what we've spoken about in our conversations before, it's interesting that you really emphasise how you've built the team with the objective to scale analytics and workforce intelligence within Raytheon.  And our recent research at Insight222 found that leading companies in people analytics have a strong focus on productising people analytics, as I know that you have at Raytheon, and then it's scaling this across the enterprise.

I'd love to hear, and I'm sure listeners would as well, because we get lots of questions about this, around productising people analytics, what is your approach at Raytheon Technologies to productising people analytics; and are you able to share any examples of your work in this area?

Aashish Sharma: Yeah, this is a great question, David, and I would say for us, right from the get-go, this was a central theme of, we not only wanted to do this but we wanted to do this at scale, given the size and complexity of our organisation.  And I would sum it up by using a quote from the book, The Lean Startup, which by the way I'd highly recommend to any practitioner out there.  And it goes, "Think big, start small, and scale fast", and that was the philosophy that I used when we were in the initial stages of founding this function.  That still remains our philosophy today when I think about the next stage up.

Let me play a couple of examples of how we've done that.  In the early stages, we were very focused on just foundational analytics capabilities.  And one of the focus areas for us was, how do we build really good self-service, dashboards and analytics for our global HR partner so that we can put it in their hands, and they can use them to answer really good questions and use that as an opportunity to do some consulting with their business customers?  But as we were thinking about what would really make it successful, or what would really make it work, there were two or three things that became important as part of that.

Number one was, we knew that we had to make sure that the tools are going to be extremely simple and intuitive and easy to use, which then kind of fed into our inputs that we were providing to technology selection, because we really wanted to make sure that the visualisation component of the tools and the ease of use was prioritised on that.  Then, we also knew that the world of living in static dashboards or reports is never going to be enough for our HR community; we would need to figure out ways to constantly and rapidly enhance these tools, create greater functional flexibility to support ad hoc requests, and part of it was, "How do we create an execution framework around it?" and that's where we started really integrating design thinking and product management into how we did the work.  We hired for those skills as we were adding more headcount gradually to the function, and at the end of the day we were able to cut in half the amount of time that it took for us to produce a dashboard. 

Then, on a monthly basis, even today, we are rolling out enhancements to those products, we are collecting feedback, we are learning on the go, so it was fascinating that it was important for us to think big, but we didn't wait for everything to come together.  We started small, but then we were scaling fast because of technology and this infusion of design-thinking and end-product management.  And if I fast-forward that to some of the more recent work that we've done, a lot of people analytics teams are doing productive work around attrition; they forecast attrition and they try to forecast risk of talent leaving the organisation, and we did some of that in the early stages of multiple pilot runs.

But at the end of the day, we figured out that a true customer of that product is a people manager, and it's important that we were not only getting good at forecasting, we were not only focused on, "Is the model performing well; is it doing what it is supposed to do?" but we had to figure out a way to put that into the hands of a manager and do that in a way that was really intuitive and easy and built into their workflow; as opposed to, they're not HR people, they don't have the knowledge and they don't have the time.

So, the analogy was, we were very busy building the inside of the iPhone, the guts of the iPhone, but what we really needed was that front of the iPhone, we needed that interface.  And that has become part of the thinking process that has become part of the execution process and how we scale this stuff.

David Green: And actually, I think you said something really important to enable you to do that, Aashish, was bringing those design-thinking and product-management skills into the team, because you had people presumably who could do great predictive models, and they're thinking, as you said, the inside of the iPhone, but by bringing the design-thinking, the product-management skills in, they're thinking about, "How do we actually get people to use this; how do we make it easy", as you said, "simple and intuitive and easy to use?"

Aashish Sharma: Absolutely.  That is a big part of how you scale this and deliver this, and obviously the skillset matters and the prioritisation of that skillset matters a little bit.  But for us, we always knew scale was a big part of the mission.

David Green: What organisational challenges should be considered when structuring a people analytics team, you know, your operating model; and what guidance can you give to those listening who are maybe a bit earlier in their people analytics journey, or are aspiring people analytics leaders, when it comes to structuring your team and then evolving that over time?

Aashish Sharma: So, let's do this.  I'll start with a bit of what I would consider good news, or potentially a good problem to have, and it certainly keeps me very motivated in my role, which is the solutions and the impact of the solutions in the space have matured so nicely that there is a lot of demand and acceptance for the solutions.  On the other side of it, there is so much data being generated and there is no shortage of types of things that you could explore, or mine and create insights around, that the possibilities, the art of the possible continues to expand. 

That was not the case, like I told, many, many years before and it was a lot of selling and more in the solutions.  So, when I reflect upon some of that, I would offer two or three focus areas, whether it is somebody who's starting, or early stages of that maturity, or somebody even further ahead, because even for us, we continue to think about this, right. 

The first one I would offer is the ability to separate impactful work from interesting work.  It's very important that the leader of the people analytics function is truly spending time and is creating pathways to understand, discover what is truly going on in the business and what matters right now with the business and is able to direct the solutions, or the creation of new solutions towards that as opposed to, like I said, you could be doing a lot of interesting stuff because at the end of the day, you want to create impact, but at the back of the impact you also want to create investment, so that the business leaders and the HR leaders feel like they are getting the return on their investment of these solutions, and they continue to invest, whether it's investments in talent, technology, partnerships, whatever.

The second thing I would tell you is, it's also important to separate the urgent versus the important.  There is no shortage of ad hoc requests and fast-moving things that are needed in the organisation where even though some organisations may have tools in place to help with those things, but because of the expertise and the skillset and the knowledge and the understanding the people analytics professionals have, they're able to quickly put together insights at a faster pace than any others.  And sometimes, what that leads to is you become the be-all and end-all of everything that's going on.  What that takes away from is the important work of what I would call building the machine, which is like scaling your products and creating capacity.

So, I've seen organisations solve this structurally where they try to create a reporting team separately from an analytics organisation; I've seen companies solve it by creating more focus within a larger team, where they'll have an analytics team, but members of the analytics team would be focused on reporting, and others would be focused on other aspects of work.  In my experience, the structure is not as important as the focus.  It's really important to insulate that focus and it's challenging.  It's not natural, it's not easy to do, because you're also trying to build credibility and you want to be out there and letting people know that you are able to produce some great insights.

Then the final piece I would add is stuff that is really, really hard and very few people understand but matters a lot, which is data quality and governance.  It's really hard to get leaders and other constituents excited about being able to do data governance and data quality, and I've seen a lot of teams trying to solve it within their teams, so they'll have multiple people clean, scrub, profile data, because no one really knows how best to go about this in a much more structured manner.

The advice I would offer is, that is, at the end of the day, a core engine.  And whether it is your IT function that has more influence, tooling or resourcing to be able to help address that; whether it is external partners you want to engage on this, you don't have to solve everything on your own.  Building out those key partnerships, being able to do highly focused work, impactful work, I think even today for us, David, that is still very much part of the recipe.  So, I think those things go a long way.

David Green: Are there other skills that you've built into the team as you've moved through the years, because obviously with a team of 45, I guess you can potentially have specialist skills such as NLP or other skills in the team that you may not have had the luxury of having when you had a smaller team at the start?

Aashish Sharma: Yes.  I think we've been fortunate enough to grow capabilities and headcount, but more importantly really put together a team that has a pretty good diversity of the skills.  So, we've got folks with consulting expertise and they're much more forward deployed into our business units and in the businesses; we've got folks that are really great at data engineering and data solutioning and predictive modelling.  I would say, in the last couple of years or so, where we've spent a lot more energy was around how do we get really, really good at communications, driving better adoption and stickiness of our solutions, as well as leadership engagement and stakeholder management, which comes a bit with what I would say the storytelling skills.

Earlier on, we were doing this before, David, but our work product was at a place where we could easily partner and get somebody's 10% time to do this.  Now we are at a place where we've got a diverse set of products and services, we get engaging, complex scenarios, we get engaging, cross-functional, problem-solving projects that when we come out with a solution, I often use a comparison that the first three to five years of our journey was all about building and developing analytical products, a lot of the energy was there.  Now, a lot of the energy is on how do we create impact, adoption and growth out of those solutions?

So, from a skills perspective, I think a lot of emerging stuff for us is ability to do enterprise scale, programme management, change management, communication.  Some of it we are starting to house within our function, some of it we still continue to partner with other areas where we have expertise in communications or talent.  But when I think about what that has created in terms of the shift; yes, we continue to see workforce planning is an example where we continue to see some of the shift happen from a skillset perspective.

David Green: So, we're going to talk about mergers and acquisitions now, which I know is something that you've had a lot of work in.  You mentioned the merger between Raytheon and United Technologies earlier as well, and you've gone through a series of mergers and acquisitions as well as divestitures during your time.  How did you and the Workforce Intelligence team support the organisation doing these transformations; and what are some of the opportunities and maybe some of the challenges that arose as part of this?

Aashish Sharma: Yeah, I want to say, David, that a large part of our own evolution had a very strong connection with the overall business transformation that has happened in the enterprise over the last five years.  We've gone through significant merger, acquisition, divestiture activity, which required us to also adapt and support and grow our own capabilities as those events were happening. 

The way that I see that the team has evolved in supporting that is, when I go back to four or five years back on when some of this activity was happening, we were sort of playing the role of what I would call as a data provider.  There were external vendors that were part of the mix and they would require HR data sets, and my team would get engaged in essentially becoming the data provider.  We would offer a little bit of interpretation in what we want, and then they would go off and do a lot of hardcore stuff that happens from an integration and planning perspective, such as organisation design, you're trying to figure out impacts to locations and workforce costs and other things.

Fast-forward a few years out and having done a few of these, we were able to build a bit of that infrastructure and expertise to essentially become a co-partner on those initiatives.  So, when I look back in the last couple of years, as we were going through the big merger between United Technologies and Raytheon, we were a strategic advisor and a consultant in the M&A work and the integration work.  I was part of the core team.  We pulled together consolidated data to be able to respond and help the organisation facilitate a number of org design activities, a number of location and workforce impact-like activities; so, I've seen this gradual shift of us going from data provider to the co-creator and really having a seat at the table.

It's certainly come with its own set of challenges, because as you can imagine, there are limits to the feasibility of what you can integrate from a data perspective.  There's also a whole lot of definition work you have to do and assumptions that you have to create, make sure that you are integrating data, consolidating data the right way.  Certainly, you can't do a whole lot of historical trending, because systems are not integrated at this point and there is no process harmonisation work. 

But we've had a really great partnership as well with cross-functional teams.  You think about legal, privacy, finance, since we've done this work, and just being able to drive consistent consolidated analysis for the corporation, where there is one place to go, one team to rely upon and one source of truth, that's been hugely beneficial in these types of transactions that have happened.

David Green: And you've pulled out one really key relationship I think for people analytics.  I mean, legal and privacy are key relationships as well, but I think finance, we had Laura Shubert from MetLife on the podcast a few months ago, and she really talked to the importance of that relationship between people analytics and the finance team at the company.  I just wondered if you had any additional words to say about how important that relationship is to the success of people analytics.

Aashish Sharma: Yeah, I think it's tremendously important; it's tremendously important in a couple of different ways.  I think if you were to look at the world where the people analytics function did not exist, finance was essentially largely responsible in many organisations for headcount and they naturally, as part of the work that they do, have to incorporate a lot of assumptions into financial planning and analysis, a significant amount of money that an organisation spends is on human capital, right.

So, you've got finance as a stakeholder that was much more closely involved prior to people analytics being there, and now with people analytics being there, one of your closest stakeholders is finance, because you want to always be in a place where HR and finance are using a common source of truth; there are no discrepancies on what finance thinks is the headcount number, or what HR thinks, which is an age-old problem that I've seen in many companies.  But also, at the end of the day, finance becomes a strategic partner when you think about things such as workforce planning, when you think about even driving investments to people analytics in some cases, when they understand the scope of work that is done and the impact of the work.

We were there last week in New York, and Jonathan talked about the importance of knowing your HR CFO, the financial person really responsible for the HR function and building a good relationship with them, specifically for the people analytics leader.  So, I think it's not a relationship that is transactional, from my perspective, it's a relationship that should become very strategic.

David Green: And I guess the importance of that relationship is magnified during mergers and acquisitions.  Obviously, I don't need to tell you that these things can take quite a lot of time and you've talked about some of the data challenges around the availability, the definition, bringing those data together, aggregating them.  With that in mind, how do you answer some of the strategic questions that you undoubtedly get from the C-suite, while in parallel putting those firmer foundations in place?  I guess you've got to be doing both.  As you said, you made that journey from data provider to co-provider; how did you make that change and how did you answer some of the ongoing questions that you got?

Aashish Sharma: Yeah, it is absolutely one of the most challenging parts of M&A work, I would say, and HR as a function is thrust forward because everybody wants to understand the people side of the implication and people side of the impact as they are working through that.  And like you mention, I think our strategy has evolved; we have a track where we are going to work the larger gameplan of getting the systems consolidated and integrated where again, we have a large role to play, because we need to inform some of the requirements for how data needs to be structured.

But before that, this sort of chaos of the integration if you will, a large part of important work that we've had to do was helping the organisation truly understand the consolidated workforce, and help them understand not so much of the number level, but help it kind of put it and map it in context of the financial structures, because you're looking at a business, you're looking at a P&L level, and you also want to look at your workforce at a P&L level.  And there's oftentimes no natural way to link people data at a programme or a P&L level, and I think that's where the relationship with finance and the collaboration with finance becomes really, really important, because you are helping leaders who are now getting charged with a significant amount of integration and change management work that is ahead of them, and they need to better understand their workforce in the way that they look at their P&L.

The other example I would give you where we've had, I would say, more emerging capabilities and work done, is also helping the leadership teams understand the potential level of change or concern or communication needed by doing sentiment analysis.  So, we've been able to partner with the change management organisation or the communication organisation, where they were running specific surveys to really get a sense of what are people feeling as we are going through this journey, and we were able to port some of the NLP work that we've been building up to work on that, and that has gone a long way in helping senior leaders really focus their communications on the topics that are most important to their employees, whether it be through town halls, whether it be through other communication forums that are being used; it's allowed them to get a better understanding of what the impact and change looks like when you are looking at it from an employee perspective.  It's also allowed them to address the right issues when they are out there talking to people.

David Green: As someone who sits on the HR leadership team, how do you position your workforce intelligence function to ensure that it prioritises the most impactful work for the business?  This will probably bring out a little bit more of what we talked about earlier around impact versus interest.

Aashish Sharma: We have a fantastic CHRO, David, and a fantastic HR leadership team, and I have the privilege of being part of that forum, more so in a business advisory, consulting capacity, I would say, and it has helped in a couple of different ways.  One is around the notion that you're bringing up, and how it has helped the people analytics function is by being part of first-hand discussions around the most important emerging priorities of the business, or shifts that are happening from a business perspective, or things that need to be addressed, or things that are coming around the corner.  And by having first-hand knowledge and visibility to that, it has given me the opportunity to continue to direct the work of the rest of the team that we are doing, continue to direct the work of the projects that we are working on, in line with where those priorities intersect.  So, that has been tremendously beneficial.

There is also a flipside that we've seen of this benefit playout, where because you've got somebody like me, I'm able to sometimes offer much more real-time inputs and consulting in a much more data-driven manner to discussions that are happening in that forum.  So, rather than something becoming a follow-up or a to-do to say, "Let's look at data and come back to it", oftentimes we are having that discussion in the moment and we are trying to address it.  We also have a strategic planning process, a goal alignment process, where every year we go through a little bit of a, "What does two to three years look like for the HR function?  What are the most important priorities and initiatives that we need to be working on from a business perspective?"  Then, by providing a lot more richer input and awareness of the people analytics solutions or workforce intelligence solutions, I am able to integrate some of that into the strategic planning process.

So, at the end of the day, what's really happening is we are closing the loop faster on our responsiveness to the emerging needs of the business, and one of the things, as you pointed out, is that pace of change and the amount of change has just been rapid, which means that the HR function has had to constantly pivot, the people analytics teams have to constantly get pulled off and on, on emerging priorities.  And for me, our goal is not more solutions; our goal is to maximise the impact of existing solutions, where they can be put in place.  So, it's more about re-pointing the laser back to where it will have the highest impact.

David Green: Yeah, really interesting, and certainly the three years that we've been doing the annual research at Insight222, we've seen that more of your peers, heads of people analytics, they are reporting directly to the CHRO.  And even if you don't report to the CHRO, I think the important point that you've made there is you want to be part of the conversation at the HR leadership team level.  So, as you said, you're hearing it first-hand, and not only are you hearing it, you're able to inform the discussion as well with real-time data; really interesting.

I know one of the areas where you're particularly doing that is around workforce planning, which I know is a real passion of yours Aashish, so let's turn to that.  There are several Bs with strategic workforce planning, I'm going to read some of them now otherwise I'd forget them, I've listed them: build, buy, borrow, bot, bounce, boost.  I hadn't heard bounce before, I must admit, until you talked to me about that.  But how have the past few years, along with the M&A activity, influenced the way that you approach workforce planning at Raytheon Technologies?

Aashish Sharma: The biggest shift for us, David, has been around putting more emphasis and energy on strategic workforce planning.  As you know, we've talked about this before, workforce planning is very broad and it can mean so many different things to different stakeholders.  Traditionally, many organisations have put a lot of their workforce planning energy behind what you would consider operational workforce planning or headcount planning and forecasting, where essentially you're really looking to look at the size of the workforce.

But when I think about the type of business that we are in, the industry that we are in now, and then the drivers for a lot of the M&A that we've been doing, what it comes down to for us is not just having the right size of the workforce, but even more importantly it's having the right skills in the workforce.  And by the way, it's also incredibly important for us to generate more learning pathways and growth opportunities for employees if we are going to retain and develop the best talent we need. 

We've all seen the last few years of volatility, in terms of employee departures, employee experience and all of that, so I know it's easier said than done, it's not been easy, it's been tried before; but when I think about where our focus and energy needs to be, and certainly we are putting tremendous energy behind this, it's really about being able to do the skills portion of it, because it's not just good for the business, I think it's really good for our employees too.

David Green: What were the building blocks that you've used to help you successfully tackle workforce planning at scale with that injection of the skills piece to it as well; so it's kind of, as you said, moving beyond the operational workforce planning and looking at headcount, but actually looking at skill?

Aashish Sharma: I mean, we've spent tremendous energy trying to do our best due diligence on this on a variety of things.  In fact, you know this, we've taken advantage of a lot of Insight222 peer conversations and the research playbook that was created by Insight222.  And if I was to put it back to you in sort of a building blocks' construct, what I would say right now, for us the building blocks look like the following: it's people, data, process, technology and partnerships.  Let me hit upon a couple of them; let me start with process and partnerships.

If there is anything that's incredibly most important to doing successful workforce planning according to me, it's to be able to do it in a cross-functional manner.  It's not a thing that one specific function like HR owns, and we've been spending a lot of energy in building those relationships, specifically in areas where we've piloted some of this with our digital team, or with finance and business leaders.  And the idea behind that is, how do we get really smart and effective in the HR function, in the workforce intelligence function, on translating the business roadmap, translating the financial objectives into critical roles and skills?  That translation layer is hard to do and it's more sometimes art than science.  So, we've been spending a lot of our energy on the partnerships pillar. 

Separately, we've also been spending a lot of our energy on really figuring out what our process and technology needs to be around collecting and sustaining skills data.  And as you know, we've talked about, in the scaling piece of this conversation, that being able to put technology around a process and being able to figure out a really effective process and being able to put technology around the process and being able to put good data on top of it is the path to scale for us.  So, we've been trying to figure out, "What's the right set of processes and technologies for us?" and we've also built out our own version of the process and definitions.

When we started talking to many different stakeholders in the organisation, what we learnt was really, there are too many definitions, too many assumptions on what workforce planning even means, and we had pockets of the organisations having their own, let's call it the four-step recipe, or the five-step recipe, on how to do this.  And one of the things that we've done is we've hired in a really smart workforce planning guy, who's leading this stuff for us, and he's put together a really common playbook for us.

David Green: We could have talked about workforce planning a bit longer, but I think we're approaching the end of our discussion now, Aashish.  Before we do though, I want you to gather your thoughts on the topic of technology.  Probably like me, you've seen the advent of ChatGPT has prompted renewed discussion about the increased role of AI and machine learning in people analytics, and you've already talked about how you've used NLP in terms of arming your executives with how employees are feeling at the various stages of the merger.  What do you think the growth of AI and machine learning means for the practice of people analytics moving forward?

David Green: Yeah, David, I think when I put my practitioner hat on on this stuff, this is certainly a hot topic, as you can imagine.  And I think if I put my practitioner hat on, I think there is a lot of opportunity of this to make the work of a people analytics professional more efficient at a foundational level, so you are able to let go or automate tasks that you could have an AI or machine learning capability do for you.  There's also a lot of, I think, exciting development that would allow people analytics practitioners to get deeper with their creativity, innovation and how they are able to explore and mine data.

But I think on the other side of it, what it really will also do is thrust more responsibility on the people analytics professionals to be even more focused towards the data.  I think it's going to put them at a place where ensuring that there is tremendous transparency and explainability of solutions is going to be a big part of their job.  For us internally as we've done this work, we've got a couple of really important guiding principles.  Our first guiding principle is privacy first, so everything that we do starts with privacy and starts with discussions around privacy and the right inputs we need to collect.  Second is we have a, "There are no black boxes", kind of a rule, which is everything that we build, we need to be able to clearly explain that to any audience.  So, I think those are new elements, I would say, that are going to become an important part of the skillset, but certainly a lot of excitement of what the capabilities are.

If I put my leadership hat on, when I think about it as a leader, I think one of the things I would love to see happen more is for HR leaders and in general, business leaders to get much, much more knowledgeable and familiar with the concept of AI and how it works, because at least from an HR perspective, this goes beyond people analytics.  This is about HR being able to inform the strategy of its own function as the businesses adopt these technologies more broadly, right, how does HR function help with things like organisation design when the businesses start adopting?

Then also, I think it's important to create a sense of excitement and embrace for these things, and have the right set of education so that where there is greater relevance and applicability within the HR function, the leaders are able to quickly embrace and adopt these solutions.  I think about simple things such as, "How do we improve response times to employees for their queries?" something really foundational and simple.  So, I think there are implications to both people analytics teams, as well as the rest of the leadership team.

David Green: Aashish, we have two more questions left, so we're going to look to the future on both of them actually.  So, what's next on the agenda for the Workforce Intelligence team at Raytheon Technologies?

Aashish Sharma: This is certainly a question that keeps me on my feet, I spend a lot of time thinking about it.  We actually talk about it as a team and I think the future is very, very bright for the space.   For us, for workforce intelligence, there are two or three big vectors ahead of us.  I think the number one is, how do we get really better at creating more integrated products and services?  We've grown as a team, really spanning separate sets of pillars and capabilities, like we've got dashboards, we've got advanced solutions, we've got consulting.  And now, when I think about what's our mission from a business perspective, which is strategic workforce planning, it's about bringing all of those capabilities and expertise in an integrated manner, and putting that into work for the businesses.

The second interesting vector that we've got is, we need to continue to figure out ways to empower not just business leaders, but also people managers and line leaders.  I think they play an incredibly important role in the development, management and retention of talent for us, and specifically in the hybrid remote, and all the different org types that we are in.  They need more insight into the workforce, because they need that insight to do their jobs better, and employees expect them to do that.

What I mean by that is really not putting dashboards in the hands of people managers; we've done a little bit of that.  It's really about helping develop that intelligence, David, which puts the right insight at the right time in their workflow.  So, they're having a performance discussion and how do they know that so-and-so individual has been this long in the role; this was the last time they received a promotion; and this is the right conversation to have?  How do we proactively give them not only just intelligence, but also context around what actions they could be taking?

Then finally, the third one I would say is we absolutely have to continue to expand and scale our data platform to be able to support more qualitative analytics.  I think there is a lot more that needs to be done in the space of sentiment analysis and really understanding the behavioural aspects that can help with important objectives around making sure that wellbeing, work/life balance and flexibility are still cornerstones of what employees expect from organisations.

David Green: Love all of those, and we're going to stay in the future, the sort of near future now, we're going to broaden it out I guess to HR.  So, this is a question we're asking everyone on this series, and in fact on the previous series as well.  What do you think HR leaders need to be thinking about next in the next 12 to 24 months; and what's your biggest concern and what do you see as the biggest opportunity?

Aashish Sharma: This is my view.  I still think that the shift around future of work that the beginning of the pandemic created is still going through a lot of norming and storming, where we haven't seen organisations adapt to a so-called operating rhythm or predictability around how to figure that out.  And that central theme is driving a lot of other aspects that we are seeing happening.  We are seeing how organisations and the HR function have had to get into a little bit of a reactive mode on how do we think about recruiting talent; what does it mean to our recruiting?  Is it a pool where everybody can work remotely?  How do we continue to offer the right level of insight and consulting to business leaders who may have their own perceptions on what the future of work looks like versus managers versus employees?

From my perspective, I think it still is a top-of-mind agenda item, because so many of the HR programmes have had to go through a rapid shift and probably will continue to get recalibrated, readjusted.  I mean, you talk about a headline story of inflation, where everybody thought that, "Hey, what's going to happen with compensation now?"  How do we think about compensation in a market like that?  And, I truly believe, David, 10 years out, 15 years out, whoever is going to write the best-seller on this, or is going to do a look back, I think this moment in time is going to drive a bit of separation from organisations who are able to continue to learn and adapt and pivot their HR practices, and how they navigated this versus organisations who did not, and they may have seen greater disruption.  So, I think that should be top of mind.

When I think about the concern, what it presents as a challenge to the HR function is, everything that we just discussed has also been happening to the HR function.  So, the HR professionals have also been dealing with a significant amount of change, there has been attrition, there have been concerns about how we do work/life balance; and the challenge for HR leadership is how do we create a better HR function, a smarter HR function, more career development and retention for the HR function, while we are also trying to figure it out for the rest of the business?  There is no script for this, there is no precedent for this, we are all learning on the go, we're here, so I do think that is a big challenge in front of many HR leaders.

David Green: Aashish, it's been wonderful talking to you, really exciting to hear about the amazing work that you're doing at Raytheon Technologies at the moment.  Thanks for being a guest on the show.  Last question, how can people stay in touch with you and learn more?

Aashish Sharma: First of all, thank you very much, David.  This was really tremendous for me as well, I appreciate the opportunity and was certainly very excited to do this.  The best way to find me would be on LinkedIn and if you happen to be a member of the Insight222 forum, you'll often see me in one of those meetings, because I'm constantly learning from the best people, my peers in the organisation, as well as guys like you, Jonathan and others at the Insight222 team.  So, it's been a tremendous journey.

David Green: Well, thank you very much, that's very generous of you to say that, Aashish.  Thank you so much for sharing your story with listeners of the Digital HR Leaders podcast, and I hope to see you in person very soon.

Aashish Sharma: Likewise, David.  Thank you very much.