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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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