Humanising the Future of Work podcast

Host: Sam Shindler-Glass

Speakers: Rachel Phillips, Partner and Head of Workforce Planning and Analytics, Davinder Kang, Workforce & Talent Analytics Lead.

SS: Hello, listeners. We're very excited to welcome you to our fourth podcast in the HC Trends series to talk about, appropriately, the fourth element of the trends this year, which is perspective. As ever, I'm your host, Sam Shindler-Glass. And I'm delighted to be joined by Rachel Phillips and Davinder Kang. Both are a key part of our workforce transformation practice and have ample experience across the areas we're going to be diving into today.

Rachel, how do you differentiate between business strategies and workforce strategies?

RP: Thanks, Sam. For me, really, a workforce strategy is a key enabler to the business strategy. Without a workforce strategy, you're not able to align the resources that you've got to achieve the goals and the outcomes of your business. And really, the focus on the workforce is focussing on the enablers of your business to achieve the goals and ambitions that you have as part of your wider business strategy. I think what’s really interesting is that the rise of the workforce strategy has really occurred over the last five years or so.

They have the right tools that they need, they have the right other enabling processes that they need, that they're operating in a workplace that is suitable and effective and actually, that they want to work there. And people are a priority commodity at the moment and attracting and retaining those people is really key to success of your overall business strategy.

SS: And you talked about people as a key commodity. Do you think that's going to start to change now that the relationship that did exist over the last five years has shifted a little bit? With the unemployment rising due to COVID-19, do you think we're going to see a slight shift in that or actually, the people imperative is going to continue to increase?

RP: I actually think that the people imperative is going to continue to rise. I think that the employment structure in the UK is absolutely going to be changing. I think there will be rise in unemployment. But actually, the labour market at the moment is very vocal and very strong in terms of what it wants from its employers. Different types of job roles, different types of conditions, different amounts of flexibility. And the workforce these days really have a sense of purpose about what they're doing as well.

And they will be looking for organisations to work for that can deliver on multiple dimensions, not just the basics of simply having a job.

DK:I would add to that point. That just highlights some of the complexities that we're probably going to see in terms of the external landscape. Yes, absolutely, you identified the impact of C-19 in terms of how we're working. But that is going to see a trickle effect and also increase the emphasis of the people imperative as well as how that feeds into what delivers on your workforce strategy.

Other things we're going to see really changing the complexity is the regulations that will need to obviously be in place and support new business models as organisations will strive to continue to adapt and grow in fundamentally a new world as we start to come out of what will be a recovering economy.

RP: What's interesting about this actually, Davinder as well, it's a great point, is that organisations are starting to change how they view their workforce themselves. This rise of the workforce strategy and the chief people officer is reflected in the fact that our surveys tell us that actually, 83% of organisations produce lots of information on the state of their workforce. This is very topical and organisations do know that the workforce is a real priority for them.

But what's interesting about that is that only 56% said that they've made moderate or significant progress in the last ten years, which does suggest that while it's a big priority, actually, there's still quite a way to go.

DK:And it does come back to that point around getting insights in order to make some of those informed decisions. We know that the way in which you want to actually predict the future, the ability to have foresight on what your future workforce is going to be delivering on and also, therefore, what it needs to be composed of from a skills perspective. But also from a composition perspective around type of worker, I think that really does show that the data aspect and the insight that you collect on your workforce is just as critical.

And I think we do see varying levels of maturity of where organisations are in doing just that.

SS: I think that moves us really nicely, actually, on to our second question, which is all about how you get the most out of data. And you talked, Davinder, about some of that long-term piece around what's the strategic future, but also in terms of the value of real-time data. What can organisations look to get out of that?

DK: Real-time data is an interesting topic, especially when it comes to insights on people and the workforce, which is essentially quite a dynamic and a consistently changing body, so to speak. But I think what we know is that only 11% of organisations today produce workforce data in real time. And I guess what we also know is that the lack of being able to collect real-time data or really to push forward decisions is very much down to the questions that are being asked.

A lot of organisations are still struggling to really define, what are those key hypotheses that they've got that are going to enable them to deliver on growth or to enable to deliver on their talent strategies and workforce strategies? And that's where it then comes to a question of, do we need real-time dynamic data to answer these questions?

Or actually, do we really need to be more informed about the types of questions we are trying to answer and therefore, get an understanding of the type of data we need, the frequency of that data and the volume of that data?

RP: I think some great examples of that are the difference in the type of data that you require. E.g., your real-time workforce data could be incredibly valuable to you if you have a workforce that's working in a high-risk setting, e.g., where you need to understand the location of your workforce, the health, perhaps the tiredness or the activity that they're undertaking. In some of those situations, real-time data can be incredibly valuable.

And the progress that we've made over the last ten years and the ability to track a person's attributes such as location, health or tiredness in real time are really monumental. And I'm sure many organisations will be able to point to instances where that's both improved the health and safety and wellbeing of their workforce quite dramatically and also, frankly, enabled them to be significantly more productive.

But I think to Davinder’s point, that real-time data analysis is really only relevant to some very, very specific use cases. And when we think more broadly about the other types of data that are required, you really need to understand what the use cases and what the hypothesis is that you're answering. And frankly, at this point, I think it's worth us just reflecting for a few seconds on the fact that while it might be a fantastic ambition to have real-time workforce data, many of the organisations that we work with at the moment struggle with some of the most basic data when it comes to information regarding their workforce.

We are seeing, at the moment, a turning point in people implementing new ERP solutions, other type of data management systems. But actually, the state of data at the moment is not that strong in many organisations.

DK: I would totally agree with that. I think if we look across where pockets of real clarity is found in using data, it's across things such as headcount, e.g., or turnover rates or hiring insight. Which you could argue is probably something that we should be moving away from. And if you try to then marry that up to the types of questions we're being asked now to answer on the actual workforce, the data is really not there in terms of being able to answer the questions.

Because we're still getting to grips with how we get real, good quality, frequent data across some of those previous areas. I think another area where HR and organisations as a whole are being held back slightly is just the understanding of what this data really informs. There’s a big question around the ethics of using data that is real time, data that is external or data that's unstructured, so to speak, versus how much value it really brings.

A couple of examples are having sensors and using data around workplace. There are now really good examples of smart buildings that can really inform bespoke or personalised styles for employees, right down to being able to set room temperature in meeting rooms based on client preferences. And in the same vein, wearables and data that can really help inform, as Rachel mentioned, insight to yourself around, what's really going to impact your wellbeing and therefore, your productivity?

What holds us back in that is that there's still no clarity on how else that data is being used. And from a data protection and GDPR perspective, there's still some catching up to do on really being able to unleash some of the value in this type of data that's real-time, unstructured and external.

SS: That makes a lot of sense. And we've talked a bit about data storage and data collection. Into the how it's used, organisations are often seeking this phantom of the easy answer that data can provide, often defined as productivity. And what are the challenges with the thought of looking for the data to get a single productivity metric?

RP: It's an interesting question. And I think productivity is a concept that is being forced to be revisited, if you like, by the situation that we find ourselves in now with the COVID-19 pandemic, where significant proportions of the UK’s workforce are working from home. Employers are now starting to ask themselves, how do they measure productivity effectively? How have they measured it in the past? And how should they measure it, frankly, going forward?

And with the advent of the data world that we live in at the moment, there's a natural assumption that there will be data available to help you with the analysis of that productivity. It's not to say that there's not data available for that. But for now, the data sources available for productivity are going to be perhaps softer data sources around employee experience, e.g. Or sentiment data to understand experiences, feelings and environment data for where your workforces are positioned and what they are doing.

There may be other external data sources that could be used as well. E.g., be able to track what your workforce is doing on technology and devices that are not work-related. But again, to Davinder’s previous point, I think this starts to raise some very interesting questions around data protection, GDPR, e.g., around the tracking and monitoring of your workforces. And I think it's fair to say that this has taken this approach very differently, depending on the type of organisation and the business that the workforce is working in.

DK: Another thing to just highlight there is that we have a tendency to jump into the data first question, so to speak. It’s almost like, what data have we got? Because we need to get insight into productivity. But for all of the data geeks out there, you probably know that you really have to start that conversation from a place of, what is it that you're trying to change or what is it that you're actually trying to achieve? And use that to really frame a view of what good looks like.

If you want to create a productivity index or if you want to be able to create a maturity index or any index, for that matter, you really need to start with the, what is it that you're trying to change in your environment or gain insight on? Build that framework and then get a sense of, how now do we answer this question and through what types of data can we answer that question? And as Rachel mentioned, that there's lots of various different types of data that can utilise.

But I think that common thing that we tend to see is that we always go from a, what’s the data that we need? And then, now let's see what we can answer with that question. Which almost gets a lot of organisations stuck in this continuous loop of maturing data that they ultimately never really use.

SS: And that moves us really nicely on to our question, next question, all around how workforce data can facilitate the return to work in light of COVID-19. As organisations start to move their people either back into the office or actually keep them at home to work, that's in the future, how can data and the answers that people… The answers and insights that people get from data really enable that return to work?

DK: I'll probably be saying something very close to Rachel's heart here, but workforce planning and the way in which that leverages data to really understand your workforce a little bit better from a talent and skills and work perspective. But also to really understand your external environment and what really drives demand in your business, I think personally is absolutely fundamental in organisations thinking about what this new operating model is going to look like.

Whether it's a return to office in a phased approach or whether it's a hybrid remote versus physical way of working or whether it's something completely new. But I think that that to me would be absolutely key and what I would be focussing on as a priority capability to really inform some of those decisions.

RP: And as part of that, to build on Davinder’s point, is workforce planning is indeed close to my heart. And I think the key to being able to do that successfully, actually, is to take the opportunity perhaps that this situation is providing us with and to assess what the jobs are to be done in the organisation. It may be that actually, the work has changed. It might be actually that you decide that in order to be able to bring back a significant proportion of your workforce into the office, e.g., you need to change certain job types.

You need to change the job roles for the people who are going to remain at home. You may need to change the job roles for people who will be doing a mixed in-person versus virtual working and so on and so forth. And I think fundamentally, as we think about facilitating the return to work, we need to understand exactly what those job roles are going to be going forward and how they might have changed to the job roles that were being undertaken previously.

And then be able to actually understand using some workforce planning methods, the data that tells us what the demand is for those job roles, how many people you might need doing them. What the different types of efforts and activities are that will be undertaken to achieve those job roles. I think fundamentally, it's about redesigning the work that's going to be done and then using data to understand what that means for the size and the structure of the workforce.

DK: I guess one of the ways that organisations could potentially fast-track some of that insight, because we are very much hindered by relying on technology or process to get real visibility of how work has changed. And we know that that doesn't exist across most organisations. I think the use of workforce sentiment, I think is also quite important to really get an insight around what's changed, what type of work has changed, what type of work has completely stopped and the business hasn't fallen apart as a result of it.

I think there's also a way in which you can get access to data that comes from the actual workforce itself that has been living and breathing through this for the last few months.

SS: And as organisations start to use data more and more, questions are going to arise, actually, that we've just mentioned earlier when we're talking about real-time data, the ethics questions that keep coming up. And these are questions that are coming up far more broadly than just in the workplace as major tech organisations start to collect data in a way that hasn't been done before. As certain government agencies start to collect data in a different way too.

But workforce strategies start to bring in the need for different types of labour. And this is where the ethical challenges around workforce data can really come into their own and really start to show up. How do you start to balance the contingent workforce with the associated ethical challenges?

RP: For me, on the contingent workforce is a really big question. And it's a really interesting one that causes me a lot of reflection, actually, on what my perspective is on the use of the contingent workforce. The contingent workforce or the gig economy, if you like, has been very popular as a phrase, as a concept and actually, in reality, over the past probably five to ten years now. The rise of that type of workforce model was driven out of the need for flexibility, e.g., in the workforce.

But also from the perspective of the labour market where we were seeing millennials, at the time, demanding flexibility in the jobs that they're undertaking, being able… I suppose the vision was being able to hop from one exciting, interesting job with their hot skills such as data science skills and data analytic skills. Being able to move from one job to another with those skills. Constantly being able to learn, grow in their careers and constantly being kept interested.

The employee value proposition associated with the rise of that gig economy was a very powerful one. I do wonder if the reality has met that vision. We see examples of the contingent workforce actually being, we call, power-by-the-hour, e.g., where you have a mass workforce used on very zero-hours contracts or short-term contracts, temporary contracts and deployed as needed. Now, again, that has some very strong benefits for the employees, but also for the employers.

And what we have to be careful of here is the real ethical dilemma here about how you enforce good practice in managing and deploying a contingent workforce. And for me, I think that this is something that really needs legislation and governance to catch up with, with the reality. Because I think that the vision of the millennial gig economy worker is not the same as the reality of the living wage, power-by-the-hour workforce.

DK: I would definitely agree with that. And I think there's also, if you look within organisations, I think where you've got total contingent-led organisations, there’s definitely a lot of things to grapple with, but even within an organisation where the contingent workforce represents a smaller percentage of the total workforce. And it's increasing over the years and we've seen it increase significantly. In the last two to three years, there's also a lot around the processes that organisations put in place for that specific type of workforce.

Some of the things we know that really need areas of focus is simple things like actually being able to determine the job title of a contingent worker and having that properly tracked in your HRIS systems. Tracking the work that the contingent worker is doing and therefore also tracking some of the compensation and therefore, some of the benefits that that worker will get.

What we do know is that the contingent worker in an organisation is definitely underrepresented when it comes to having the same policies and processes and mechanisms to almost track and support any career development, than you would have for the more traditional permanent/semi-permanent type workforce. I think there's also some work to be done there, which you could argue that what we seem to be seeing is that if you increase flexibility in your work, you seem to decrease the amount of benefits and, I guess, commitment you get from organisations as a result of that.

And I think that's something that we can definitely do a bit more in. But as Rachel has said, I think legislation really needs to potentially step up in that respect. Because right now, it sits in one camp and it is struggling with really being able to capture something that supports all types of workers.

RP: I think that… To build on Davinder’s point there, I think that what's interesting is that there are two parallel trains of thought emerging at the moment. One is that we need to have some contingent workforce to provide the flexibility that organisations need and indeed the flexibility that employees need. And at the same time, there is the rise of the strengthening employee value proposition where the labour market is looking for and seeking certain types of work

They are asking things of their employers and they want to be employed by brands that have some strength or resonance with them. I think it's interesting that 25% of the organisations that we've surveyed do actually consider authentic workers as an ethical concern and only 21% of them include them in their wellbeing strategy.

There's definitely some work to be done here, which is to align the fact that the employee value proposition requires employers to put some priority on the contingent workforce with the fact that the contingent workforce does provide that flexibility and possibly scalability when organisations need it.

SS: And it raises an interesting point. Because I know over the last few years of the Human Capital Trends report, we've seen the rise of social enterprise. And it's been all about how organisations take the imperative to make that change in the societies on the ecosystems that they exist in. And we've talked a bit about the need for or the potential need for new legislation. What's the onus on organisations themselves and what does getting it right mean to them?

DK: I think they've got a really good position to actually shape the legislation and actually shape what support mechanisms look like. They’ve got the first-hand experience. And also they are the people that ultimately make the decisions around their own workforce composition and make the decisions around how much flexibility they want and need to introduce. And I do think that organisations actually have quite a key role to play in how they start to take lead on maybe building some more of those processes.

And I think that's a really interesting stat, Rachel, that you mentioned that only 21% of organisations include their contingent workforce in their wellbeing strategies. If you think about the impact on society and some of the wider themes that you would have, then absolutely. Organisations are really missing a large population there when we start to think about general wellbeing of the population. I would say that it's an accountability as well as a nobility to lead the way.

SS: And linking back to what we were talking about earlier, can organisations use their workforce data to monitor shifting ethics within their organisations?

RP: This is a really interesting question, Sam. Quantifying ethical behaviour and getting data on that can be very difficult. And it can be very difficult for lots of reasons. It’s difficult because it's not necessarily a KPI, e.g., that is tracked proactively as a defined metric, because it's very difficult to quantify it. It's also difficult because ethical behaviour will necessitate people providing input data information to a system, to a company, to their employer, that relates to ethical behaviour.

And that's a very sensitive topic for the workforce. First of all, you have to engender an environment in which the employees or the workforce feel comfortable and are willing to provide that information. From an employee perspective, it can be very difficult. Now, there can be some data analysis around policies and practices and procedures. You could certainly analyse those types of things to work out on a maturity scale, e.g., how strong your ethics and compliance procedures may well be in regards to those points.

But I think actually having internal structured data available for ethics and compliance is very difficult. You may well need to look to other sources of data. E.g., companies like Glassdoor who provide very public reviews of people's contribution in their thinking about how ethical matters are dealt with in certain organisations. And that's a significant dataset that's gathered there on a public platform that can be accessed for this type of analysis.

DK: That's a really interesting point. But I think the way in which I would also look at it is that as one thing around monitoring workforce data to understand shifts in ethics within an organisation to also thinking about the organisation's role in those shifts in ethics as well. If we think about what has really changed the dynamics of workforce and also dynamics of some of the ethics that we see within the workplace, one of them is around the increasing use of technology to deliver work and also to deliver products.

And we know that the rise of technology within an organisation also has a direct impact on the role of the workforce and the role of humans to be more direct within a traditional role type. I think there's definitely something there that is shifting the very nature of how humans versus technology is being treated in relation to that. And I guess a way of actually using data is the increase in AI within organisations, not just in HR in making workforce decisions, but also in making various different types of decisions.

And that, in itself, has raised a lot of big ethical topics around, e.g., there's an increased use of AI specifically within recruitment to automate recruitment processes. But also to make some key decisions to just make it easier for organisations to be able to get people onboarded as quickly as possible. And we've seen examples where there's actually been bias in the way in which AI will use or select candidates.

It does raise a lot of topics in terms of actually the investments that organisations are making. And the way in which they are actually changing and disrupting their business models will have a big impact on the role that the human plays in their organisations and therefore, the ethics around that. And really, what are we comfortable with as a society around how much of this we actually change?

RP: I think this might be a point that makes many of the organisations that we work with or many others around the world actually quite uncomfortable. Because as Davinder has alluded to there, there are some very real challenges in the ethical frameworks when it comes to deploying new technology, making decisions. And actually, I think the advent of the AI and additional digital tools has actually expedited, if you like, the discomfort around the ethics question in organisations.

Prior to that, I think this was a difficult question for organisations to answer. How do we evidence our ethical decision-making within an organisation in relation to people? And now that we can deploy tools to make those decisions much, much quicker, and potentially without understanding the logic and rationale anywhere near as easily, that ethics dilemma has actually just compounded by a significant degree.

DK: And I guess also the huge increase in the data that is created as well as the way in which people have access to data. Across specific industries, from what we've seen, is that now employees themselves have access to a huge amount of data. And that data is being consolidated and being pulled together in the form of data lakes and integrated systems. And that also poses a very ethical question, is that there's a lot more information and visibility across processes, across people, across products, across customers than there's ever been available before.

And that's also going to increase the complexity within the workforce because then there's a big piece around increasing risk with having more access to data and more transparency around what you can actually do with that.

RP: And I think a key to approaching it in that case, Davinder, because what you're describing here is it is a huge, huge challenge. And I think it's fair to say that when we talk about ethics, we think about them flowing throughout the entirety of the organisation, all the way from the strategy down to the day-to-day business operations. And when it comes to using workforce data to monitor shifting ethics, e.g., in an organisation, I think it's worth approaching it at all of those different levels.

And trying to break this question up into multiple different pieces to see, actually, what are the hypotheses at those different levels of the organisation? And are there any ways that we can start to address them using any of the workforce data that we do have available?

DK: And also how to potentially increase the understanding across what it means, because I think that does factor in or contribute to the fear factor around holding back. And what you don't want to see is a slowdown in innovation or a slowdown in use of technology because there is just lack of understanding around what it actually means. And that then translates into the ethics question when actually, it could be something completely different.

SS: And I think that wraps us up really nicely, gets right to the heart of the paradox that I talk to between technology and humans that run throughout this year's Human Capital Trends report. I hope you'll agree that it's been a fascinating conversation. And thanks very much to our guests, Rachel and Davinder. And do make sure you join us next time for the final podcast in the series which is going to look at the final chapter of the trends, MMA [?] to HR. Thanks very much.

Read the related blog post here.