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Attract and retain top talent by advancing pay-for-skills
Challenges
- It’s difficult to attract and retain the skills required to transform for the future.
- Our traditional compensation methods are not aligned with new workforce requirements for agility and flexibility.
- The lack of transparency in our compensation programs is an obstacle to building employee trust with the organization.
- We don’t know which skills are most valuable, and we’re concerned we’re over- or underpaying for the wrong skills.
Rethinking compensation plans is a top-five agenda item for HR, with 36% of respondents citing it as a top priority.
Mercer Skills Edge solution can help you advance pay for skills
Skills Library
Lay the groundwork for skills-based decision-making.
Skills Map
Use review and approval workflows to map skills and proficiencies to your jobs.
Skills Pricer
Determine which skills are most valuable to your organization.
Skills pay planner
Reinvent your rewards with pay for skills.
Watch our interviews on approaches to skills-based pay
What set IBM on the path to include skills in compensation decisions?
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What was it that set IBM on the path to include skills in compensation decisions?
Let me start with the external factor what we were experiencing. And what we were seeing was the emergence of new technologies that was redefining the talent needs. We were seeing new professions emerging, higher skill levels needed for those new professions. That was a disruption we were seeing in the industry that was helping us understand the need for skills.
Second thing that was happening within IBM was we were changing how we pay for performance. We were making a fundamental shift in our pay philosophy. We were moving away from considering performance as the only factor to consider when looking at salary decisions. And we were moving towards using multiple factors.
And we believed that to assess performance, we don't need to necessarily use base pay, but we can use a variable pay program. So that shift we were also experiencing internally. And the final thing was we felt that our employees were demanding greater pay transparency, and we needed to make sure that as we talk about base pay, we needed to explain to our employees what could they do in order to have a more competitive base pay.
This is part of a larger shift we undertook at IBM. We knew that the half life of skills was five years, so half of what's learned gets obsolete or forgotten in five years. And so we really needed to rethink how we embed skills across the employee journey, all the way from who we hire, how our employees learn, how we grow people in terms of mentoring and other experiential learning promotions. And pay was just a natural evolution of that journey, as well embedding skills across the lifecycle.
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Who were the critical stakeholders and how did you build your business case?
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Who were the critical stakeholders that you had to get on board, and I'm sure our listeners would appreciate hearing how did you build a business case to make this type of change happen?
So like all good ideas, they're best when they come from somebody in the field, and this was actually not an idea that germinated from our corporate headquarters or some senior leader. It was actually a practitioner in the field. Actually, somebody in compensation out in one of the markets who saw the need, and the need that the practitioners saw was, how do I help managers make much more fact-based decisions?
Managers still have the final decision rights, but how do we equip them with the information so that they can make the right decisions. And if you think about a company like IBM, 350,000 employees in multiple business segments from software to services to hardware, and you take a manager in a market. How can he or she better understand what's happening in another city, in similar skills?
How do they see the more macro lens at their fingertips? Otherwise, he or she is just seeing their own world view of their 10 employees and making decisions based on that. But if you can bring the information of 350,000 IBMers, as well as what's happening in the wider industry at their fingertips so that they're making fact-based decisions. That was the idea of this compensation practitioner.
And so when we started, we didn't just go whole hog and deploy this worldwide. We started with a very small pilot of 30 managers in the small market where we beta tested this concept. And obviously, to take it to the next level, we needed investments. This is one of those areas where actually the investment case is a no brainer.
For any company of our size, compensation spend is such a huge portion of our expense that even if we spend our money 1% better in terms of efficiency as well as better quality outcomes in terms of retention of key skills, the payback is huge. So this is a win-win for the company, for IBM in terms of business, but also for the [? IBMer ?] because they transparently can understand what they're being rewarded with. What pay investments are getting, as well as for managers who can now allocate investments in the right areas.
Very interesting.
[INAUDIBLE] add to that, Jean. I mean, I'm in compensation, and I often hear from managers or business leaders. They're saying, look, I want to pay everyone competitively. That's our goal, but I also want to differentiate. So I want to make sure that my investment is not only going to the right people but even the increases are in the right size.
So I think that was something that, initially, when we didn't have the AI tool, we were hoping the managers were able to do that differentiation.
But I think with the help of the AI tool, we were able to help put together the recommendation, and that saved managers a lot of time as well. They don't want to spend a lot of time on HR transactions.
So we were able to meet both the goals. We were able to show the business leaders that here is our recommendation, which helps us or helps your businesses to differentiate as well as pay competitively where we think we have those gaps. And at the same time, your managers don't have to spend hours and hours doing those analysis themselves.
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How did you manage the transition and change across the organization?
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When you were managing the transition then in terms of implementing the system and encouraging it to be adopted, obviously, a traditional way of investing in talent based on historic measures for most organizations of performance and potential and other types of variables. We would love to hear, how did you manage to reframe from that traditional system into the new system of skills-based rewards?
Were there some key factors you used to manage that change process across the organization?
Yeah, definitely. I think one of the things we were changing at the time, when we're thinking about comp advisor and we were launching this, was, within IBM, we were changing our performance management system. So we were moving away from those traditional ratings, which is then tacked to salary increases.
And we co-created our new performance management system called Checkpoint. So as we transitioned from the performance management system into Checkpoint, we just felt that was the perfect time to pivot and talk also about what this means to us in terms of our rewards strategy.
So we went through the change in the performance management system, and then we introduced to our managers and employees how we are going to look at pay in this new performance environment. And that's how we introduced the concept of, OK, performance is very important for us. It always will be. But when it comes to compensation, there are other factors that we want to emphasize more on.
So we had to really start with talking about, what is our reward strategy, what is our pay philosophy, why it is changing. So we really had to also explain what we were experiencing externally. As I said, the market was also going through this disruption. So I think it resonated well, and the timing was just perfect because we were in the technology sector, and I think managers and employees were seeing that new skill was becoming very valuable and that they had to either keep up with the market or with the technology.
They also had to upskill themselves. But it really started with us talking about the new pay philosophy and the reward strategy and then saying this is how we are going to implement some of our programs based on this new strategy.
Very interesting. And then I remember, actually, you saying that the training and the upskilling, both you and Binny spent a lot of time focused on that. And your point, Binny, that this is a philosophy change I think sometimes maybe under-recognized when we think about shifts in compensation. Just the magnitude of the impacts there, very helpful.
I would just add, Jean, just one more thing that, don't expect overnight changes. It's a journey. So it took us maybe, what, five years now to get to where we are. So we didn't see, overnight, things change. We were able to change the mindset. But you have to work at it. And every year, you have to repeat the message. You have to be consistent and frequent in talking about the change and why that is important and how that will add value not only to the individual, but also to the company.
So we kept repeating that message year after year. So that's important.
And the beauty of this domain, Jean, is it really hits home to everyone that this is real when you implement skills-based pay because pay is such a deep, emotional, personal topic for everyone. It becomes so much more real for everyone in the organization. It's also a big cultural shift for our teams.
Our own teams in compensation, in analytics and technology, they have to reinvent their ways of working. They're no longer just doing process and administration. They're now understanding, are the investments going in the right areas? It's a very different way of working the responsibilities that they have much more around design and much less about process and execution.
And design was such an important aspect of this as well. It's no different than your experience when you watch a movie online or hail a cab. That's what we mean when we talk about transparency adding value to the user, which is a manager here. They need highly personalized information. And the only way you get highly personalized information at scale when you're talking about such a vast company is through AI that brings all these data points together into one personalized recommendation, but with evidence.
It's not just a black box that spits out a number. It helps you understand the rationale behind the recommendation so you can make an informed decision.
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What were the business impacts and how did it affect recruiting and retention practices?
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What were the short, medium, long-term impacts that you saw from moving to pay for skills? How did it affect recruiting say, your retention? Did it change the culture or the demographics of the workforce?
So certainly, Jean. A variety of different aspects of business impact. The primary one being, retention of key skills. Did we see that? And we're definitely seeing that. We see that when managers follow the recommendations, the retention of their teams is one third higher than when they don't.
So we're talking a significant-- it's not a 5% improvement, it's a one third, 33% improvement in retention of key skills. So that's huge in terms of retaining our key talent. And making sure that our talent is paid competitively.
Then obviously, there are broader market shifts occurring with transparency and Binny talked about that. This helps us get ahead of that in terms of pay equity and other aspects that are-- there are broader compliance shifts as well as-- being thought leaders in the space. So this brings us much closer to setting the standards and the bar by which we lay out our pay philosophy and are seen as market leaders in the space.
And then finally, our own HR organizations, as I said earlier, we have been on a journey to move away from administrative work to more value-added work. This helps our HR practitioners-- are freed up, get freed up from that administrative work and focus on more higher value work.
This actually helps the practitioners as well, because then they can get upbanded and promoted. We have fewer number of those roles but they're doing higher value work. And that's a significant part of their journey, as well.
Between short term and medium term, that was clearly-- we saw the shift in people's thinking. And they started asking, OK, what do I do and what skill set am I in? So a lot more conversation around skills started happening when we introduced the skill-based compensation.
And I think long term, some of the things that Anshul has talked about, it has clearly helped us to reduce attrition of our high scarcity skills because we do see that the market pays differently. And there is a differentiation in pay for them. So that really has helped us to look at that group and make sure that we are not lagging the market. And we are able to prioritize investments in those areas.
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How did you link your performance review program to the pay-for-skills program?
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How did you make the link happen to the performance review process? What was the connection there in adopting pay-for-skills? Did it naturally lead to a different way of evaluating skills? Or if so, how long did that take, was there a fairly dramatic change needed to involve other HR systems in moving around the pay-for-skills adoption?
I think for us, as we were starting the conversation around performances, the natural course of discussion was also, OK, you know, you're performing well or you're not performing well. And the reason why is because you may need to go and develop your skills further. And then, linkage of that performance to skill, to career progression, right?
And then, that part from career progression, that if your career continues to progress, then clearly, your pay will continue to grow. So I think it became a more holistic conversation within IBM, where it was just not siloed, OK, this is your performance, these are your goals, these are your achievements. Rather, we started having a much more integrated conversation around performance, and career, and skills, and pay.
This change in terms of when we began to adopt and drive pay-for-skills occurred at the same time at bringing together our career conversations, our checkpoint conversations, which is our performance management. And those became much more, the word checkpoint, informal, not episodic but continuous. And pay became a natural extension of those conversations as well. So it all came together.
And also, the other thing to keep in mind is pay-for-skills doesn't mean performance doesn't matter. It is a factor, it's just not the primary factor. So I think the focus around performance was the primary factor before.
Skills is the primary factor now, but there are other factors that matter as well, competitiveness, performance, potential. Those are all factors in the salary decision as well. Skills is just the primary factor. That clarity of communication, those four categories, consistently, was also very important as part of the change.
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Did the pay-for-skills program bring a pay change across all job families, including for soft skills?
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One of the other question is whether pay-for-skills can be applied in roles that are much more centered on soft skills, such as communications or leadership. When you had rolled out the system, did the program bring an actual pay change across all the job families in your organization or were there certain jobs for which managers noticed a significant change more so than other job families because of pay-for-skills?
So certainly, we rolled this out enterprise-wide. So this is applied enterprise-wide across all job families and skills. And ultimately, we do see differences wherever it shows up in our data. So we're not-- it's not like we're going and asking people, all right. You're a subject matter expert. Tell us whether the skill is high scarcity or not.
We infer whether a skill is high scarcity or not by looking at things as like our time to hire, the offer rejection ratio on the hire, the new hire salary of the hire, as well as the number of jobs in the market for that particular job category. So as long as you have differentiation along any of these data points, it automatically gets picked up in our data.
Having said that, I do think the point that you make, Jean, is a natural one, and it's easier for us to have a conversation around more technical jobs and validate those. On the softer skills, we do see less differentiation, but we do see differentiation in those job categories as well.
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How do you see pay-for-skills developing in the future?
Looking forward then into the future having accomplished so much with this global rollout of a pay-for-skills system, how do you see this developing or what's next in your roadmap, what are your plans to get to the next horizon in terms of this vision?
Definitely, I mean we'll continue to have the ITIL run during our pay cycles. What we want to do is kind of go beyond our annual salary cycle, and see how we can bring the concept of infusing AI, and also looking at scale in other pay programs. So when we are doing for instance, promotions, right how the skills play into that, and how can AI help us or help managers make better decisions on promotion using similar concepts like using these four factors.
So that one thing is about scaling this current program, and using it in other programs for sure. I think the second area would be how we can kind of even get more crisper on skill. And Anshul and I, we were just talking about that we started on journey for skill. It is hard work even for us to kind of keep up to date, right. How are the skills evolving or how can we kind of get more into the depth of the skill? You talked about the soft skill part right, how can we bring that into the decision making? So I mean, the world of skill and specialties, this is just waiting to be explored a lot more.
So I'm hoping that we will add a lot more sophistication on the skill side, and then scale this program into other compensation areas. If you think about where employees are on their own skill development journey, and what clients are asking of us. Five years ago, employees wanted to be data scientists, clients were asking, I want a data scientist. Nobody asks for that anymore. Some people want to develop a skill in Hadoop and Python, that's what clients ask for. So client needs as well as employee needs have gotten so much more granular, and as our pay philosophy evolves to address those needs, that's going to require a significant shift as well. So that's going to be exciting as we go forward.
Only 12% of respondents indicate that they formally monitor market demand for skills, but this figure is rapidly increasing with access to new data sources and technology.