This shift to 3.0 enables companies to have a more sustainable workforce model and also flexibility. While only 10% of companies have made it all the way to 3.0, everybody's going down that same path.
Pryor: What are the barriers? Why haven’t more people moved more aggressively to the 3.0 world you describe?
Wright: Well, it's hard, right? It's not just, "Hey, we have a project. Let's move to 3.0 this year." We’re shifting the way we work—moving the entire company, not just HR, to operate in an agile way. So those functional boundaries that exist even in what has been viewed traditionally as a not-so-hard process like onboarding, that involves the IT function, security, HR, and so on bringing down those barriers. And you're able to do that because you're operating in an agile way with design thinking at the core. Using design thinking means everything's about the employee experience, and through that lens, the organizational boundaries don't matter anymore. It's getting your data in a place where it's consistent and can be utilized in a different way.
It also requires cultural change; leadership behaviors that are different and transparent; and the ability to interact with employees in a very different way—particularly important now that so many of us are virtual—and co-creating the future with your employees.
Pryor: In the research, you identified five critical imperatives, and one of those is a data-driven decision-making capability powered by AI. Can you give us one or two examples that might surprise us in that space?
Wright: One of the interesting research findings was that outperforming companies invest in analytics and data four times more than the other companies. That enables them to do things that others just aren’t in a position to do. Moving to 3.0 allows you to use data in a way that's predictive, versus just reporting on the past, so we can now predict things like attrition. Companies can infer skills and predict attrition based upon other individuals who have the same characteristics—location, skills, pay, the team they work in, or whatever it might be. Companies are also using data as a way to determine which of their processes, if any, have bias embedded in them. If you can use data to do that, you can then fix the underlying issues.
We can also use data and AI to identify what skill sets we need to learn. My core skills are different from yours, for example, and what I need to learn and grow in the future is different, too. We also know the half-life of skills is declining dramatically, and the number of times people need to be reskilled in their career is increasing—over 100 million people will need to be reskilled in the next three years or so. This need to gain more skills is important, and we can use data and AI as a way to not only help people stay competitive in the future, but also help organizations match skill sets of an individual with open roles. Moving from a role-based environment to a skill-based environment is critical as the skills gap becomes more and more important for us.