(Part 1) The Winning Talent Strategy for 2025 and Beyond: Connecting the Dots with Data-driven Talent Intelligence – Interview with Toby Culshaw

PART 1

Toby Culshaw, Vice President Strategy – Talent Intelligence at Lightcast, stands out as a leading voice in the field of talent intelligence. His extensive operational experience at global organizations, such as Amazon and Philips, is complemented by his thought leadership as the founder of the Talent Intelligence Collective. Toby Culshaw’s unique perspective bridges the gap between practical, large-scale talent strategy implementation and forward-looking insights into the evolving HR technology landscape. This interview aims to provide HR leaders, CHROs, and L&D professionals with actionable guidance as they navigate the increasingly complex and dynamic talent environment of 2025 and beyond.

Throughout his career, Toby Culshaw has tackled a wide range of modern talent challenges, including AI-driven workforce planning and skills-based hiring, competitor intelligence, organizational design, and diversity, equity, and inclusion (DEI). His work has not only shaped how major companies approach talent strategy at scale but also positioned him at the forefront of emerging best practices and industry trends. With experience spanning multiple sectors and a deep understanding of both internal and external talent dynamics, Toby Culshaw is uniquely equipped to address the critical issues facing senior HR leaders today.

In this two-part conversation with Margaret Jaouadi, Toby Culshaw will explore how organizations can leverage data-driven talent intelligence to build more agile, inclusive, and future-ready workforces. Key topics include the impact of AI and automation on workforce planning, innovative approaches to skills mapping and internal mobility, and the strategic use of talent intelligence in executive succession and leadership pipeline development. He will also examine how talent intelligence can drive meaningful progress in employee experience, and look ahead to the emerging technologies and trends that will shape talent strategy in the years to come. Finally, Margaret will ask Toby Culshaw for his practical advice on building and scaling a robust talent intelligence capability within any organization.

Margaret Jaouadi
To start, how would you define talent intelligence, and why is it becoming critical for HR leaders today?

Toby Culshaw

Talent intelligence, at its core, is about leveraging external labor market data and blending it with internal data to provide context for better business decisions and strategy.

The scope of that external data can be pretty broad. It might include information on skills, job roles, people, or even competitor activity. However, the real focus is on utilizing external insights and integrating them with what’s happening within the organization.

Where things get a bit tricky is that, historically, definitions have varied. Practitioners—the people doing the job—tend to use the definition I just gave. But some vendors have a different take. For them, talent intelligence can mean something closer to talent management analytics: analyzing the internal talent lifecycle and deriving insights from that. That’s important work, but it’s distinct from what I’d call true talent intelligence.

There’s a bit of a buzzword effect at the moment. More and more people are adopting “talent intelligence” as a job title. Still, when you look closely, their role might be focused on sourcing, executive research, or even agency recruitment. All of these are valuable, but words do matter. It’s essential to be clear about what talent intelligence is and what it isn’t, because there are fundamental differences.

I’ve had plenty of debates with people analytics practitioners about whether talent intelligence is a subset of people analytics or if people analytics is a subset of talent intelligence. Or are they completely separate fields? Sometimes it feels like we’re just splitting hairs, and it’s all the same difference. Then you throw strategic workforce planning into the mix, and they’ll say, “Actually, we do all that as well because we’re looking ahead from a workforce planning perspective.”

I think these are all artificial silos within HR. Typically, HR or people analytics functions originate within HR leadership or HR operations, and they begin by assessing the current state of the workforce. They analyze, report, and, as they mature, move into forecasting and projections. Eventually, they start looking externally to add context to their findings.

On the other hand, most talent intelligence teams come from backgrounds in talent acquisition, executive search, or research. These teams spend their days focused on the external world, gathering data and insights to inform their decisions. When they need to escalate a situation, they use that data to make their case, and soon enough, this becomes a regular part of business operations. That’s how you end up with a dedicated talent intelligence function.

So, it depends on where these silos have been formed. But in reality, I think they’ll all come together eventually. It’s like a yin and yang—they’re all just different, highly specialized parts of the same whole. To get an accurate picture of what’s going on, you need all these perspectives working together.

Margaret Jaouadi  
Why do companies need external data?

Toby Culshaw  
The last few years have been wild for the labor market: massive overhiring, huge shifts, and now, of course, we’re seeing significant reductions. This level of volatility makes planning incredibly tough, especially if you’re only looking at your internal data.

If you’re only focusing on internal metrics like your attrition rates or succession plans, you miss the bigger picture. Why is your attrition rate rising? Well, maybe your competitors are hiring more aggressively, or offering better compensation, or providing a more attractive working style for software engineers. Without understanding these external factors, you’re making decisions in the dark.

Take location strategy as another example. If you’re thinking about expanding into a new region, you might see great incentives or low property costs. But unless you look at the external context, you won’t know if there’s any workforce available. You could end up saving millions on real estate, only to spend even more relocating people because the local talent pool isn’t there.

The bottom line is, if you don’t have that external context, you’re shooting blind. You’re reacting to internal parameters without understanding what’s happening out there. And with the market getting more unpredictable—from post-COVID growth to recent layoffs—decision-making windows are shrinking, companies are becoming more reactive, and there’s less stability overall.

Right now, for instance, there’s a pent-up attrition issue: many employees in large companies aren’t happy, but they’re not leaving because there aren’t enough roles available. As soon as a competitor starts hiring, your attrition risk spikes. If you don’t see that coming, you’ll be caught off guard. Training investments will go out the door with those employees, and your talent acquisition team won’t be ready for the surge in backfilling roles.

Ultimately, to have any hope of stability internally, you need to understand what’s happening externally.

Margaret Jaouadi
Let’s say you have a company in industrial goods manufacturing with global operations. What kind of data should they be looking at when considering new locations or analyzing existing ones? You’ve mentioned competitors and local trends—where do these companies typically begin, and what specific data points are most helpful in making informed decisions?

Toby Culshaw
I think there are two angles to approaching this. First, if you’re in talent acquisition, you naturally look for red flags, those outliers in the data. Typically, you’d ignore outliers and focus on the primary trend, but for talent intelligence, it’s the opposite. The average trends tend to be stable, so it’s the outliers that matter. Areas with unusually high time-to-hire, excessive hiring costs, or elevated attrition rates compared to other regions—those are the red flags that signal real issues. These are great starting points because they highlight existing pain points. If you can address them, you’re solving a problem with a measurable impact on the business.

More broadly, everything should tie back to the company’s goals. As an industrial manufacturer, you might look at your global footprint and decide if you need 60 manufacturing sites. Perhaps you would like to consolidate down to a dozen key sites. So, which locations should you keep, and where should you expand? To answer that, you need to analyze the labour market, available skills, and competitor activity. Sometimes you’ll want to co-locate near competitors to tap into their talent pool; other times, you’ll want to steer clear if you think they’ll outcompete you for resources.

Beyond that, you’ll start overlaying other factors like ease of doing business, real estate pricing, and tax implications. Talent intelligence quickly becomes a cross-functional effort. You’ll need to collaborate with real estate, finance, and other teams. The goal is to present the business with a unified recommendation, rather than a list of conflicting options. Otherwise, the company has too many choices and no clear direction. So, it’s about bringing all these data points together to support a coherent, strategic decision.

Margaret Jaouadi
What about the impact of AI or other significant trends in HR, like skills-based recruiting or skills-based marketplaces? How do these fit with Talent Intelligence?

Toby Culshaw
As these trends start to overlap and accelerate one another, things become truly interesting. I’d say recruitment has always been skills-based at its core. I don’t know a single recruiter who hasn’t tried to expand their candidate pipeline by focusing on skills. Recruiters have always wanted to widen the net; it’s usually hiring managers who insist on candidates with particular backgrounds, saying they don’t have time to train someone new.

However, this connection with talent intelligence is particularly significant in the partnership among talent intelligence, talent management, and people analytics. To truly embrace skills-based hiring—or to become a skills-based organization—you need a deep understanding of your job and skills architecture. That means you have to overlay your internal data with external market data. If you only look at one or the other, you’re comparing apples and oranges. For example, how do you know that a “software engineer” in your company means the same thing as a “software engineer” in another? Unless you dig into the specifics, such as roles, responsibilities, required skills, and levelling, it’s impossible to make meaningful comparisons.

That’s where things start to take off: when you get these datasets working together. It’s one of the reasons I joined Litecast. They’re bringing all this data together in a way that makes sense.

I’ve seen firsthand how this can go wrong. I once worked on a compensation benchmarking study for customer service associates, where we were paying well above the market rate, but still couldn’t hire anyone. The problem? Our definition of “customer service” differed significantly from the market’s. In our case, we needed technical engineers for first-line support on MRI machines, but in the market, “customer service” meant call center roles—different skill sets, but the same job title. This kind of mismatch occurs frequently.

Alignment is important. When we talk about internal talent marketplaces and skills-based hiring, the idea is that you’re hiring people for their skills, not just to fit a predefined job architecture. This shifts the whole paradigm. You need to reimagine your competency framework and career paths, as they should be skills-based rather than job-based.

I advise a company called Zigtal, which specializes in various areas, including internal marketplaces, skills mapping, mentoring, and development. What excites me is how this empowers individuals.

Historically, employees looked to their employer for career guidance and development. However, as we transition to skills-based models, individuals will have significantly more control over their career paths. The more you invest in your skills, the more opportunities you’ll have. It’s a much more proactive, empowering approach compared to the traditional “take this course to move from level 5 to level 6” model.

Margaret Jaouadi
Thank you, Toby Culshaw. The next step is to explore how companies can utilize data-driven talent intelligence and skills-based strategies to transform executive succession, leadership pipelines, and the broader future of talent strategy. In Part Two, we’ll dive into the practical application of talent intelligence at the senior leadership level, examine the evolving partnership between humans and AI, and share actionable advice for organizations looking to maximize the impact of talent intelligence in their decision-making.

For a confidential chat about how Pacific International can assist you with your Talent Acquisitions and Diversity challenges, please contact Adam Nuzie or one of our Executive Search Consultants specializing in your sector.