The Kinetic Energy of Talent

We live in a world where the very nature of work is constantly changing. New technologies have emerged to augment our work, new means of collaborating across time and space and new ways of learning and sharing, all contribute to constantly evolving ways of work and, therefore, constantly evolving talent needs. Managing those talent needs effectively is a critical priority for thriving and succeeding in this environment, and talent itself is a strategic driver of growth and innovation.

As more companies realize this, they’re seeing the power of data and technology as an invaluable way to see their employees’ capabilities and potential. Taking a data-driven approach to talent management allows us to make more informed, objective and strategic decisions, but more than anything, it changes the fundamental way we see our people. It helps us go from cataloguing our workforce as “how many of what type” to looking into who that person is, what they’re capable of, what motivates and drives them to grow and learn and how we can harness that growth, motivation, and capability.

Let’s talk about how that can work for you and your organization.

Objective and informed decision-making

One of the greatest benefits of data-driven talent management is that it allows you to make decisions based on objective insights rather than assumptions, intuition or anecdotal evidence. Often, decisions around hiring, promotions and performance evaluations rely on subjective judgment without a means to provide context. Is that person what we would consider “good”? How “good” are they compared to other people and at what particular jobs, or benchmarked against the state of the field?

It’s difficult to make decisions without being able to answer some of these questions. However, performance metrics, employee feedback, skills and capability assessments and behavioural data can all come together to form a much clearer picture and provide context for an employee’s contribution and potential. This helps bring consistency, transparency and accountability to talent decisions as well.

Enhanced talent acquisition and recruitment

Recruiting and talent acquisition is the foundation of your organization - you need to build an effective talent bench to pull your teams from. A data-driven approach can dramatically improve the processes you use to build that bench.

Analysing patterns, trends and correlations in personnel data helps you identify the characteristics and qualities indicating success in certain roles. Which then lets your hiring teams focus on finding candidates with the greatest potential for success within your organization. When tied in with your development plan, you can look for indicators of success at multiple levels and pull in new team members with lots of growth potential within your organization.

You can also use data to identify patterns informing your recruitment strategies. Where are the talent pools where you should be recruiting for those successful candidates, and what kind of recruitment strategies are most likely to reach them successfully? How long does it take you from the first recruiting touchpoint to filling a position, and where can they potentially get caught up in your recruiting funnel? Answering these questions with data helps you understand the most effective and efficient ways to source high-quality candidates and get them on the job quickly while also helping you best figure out where to allocate scarce resources.

Using experience metrics, you can also gauge how employees and new potential employees see this first experience with your company. Analysing feedback from candidates about their application process, coupled with application and onboarding performance metrics, can help you pinpoint areas for improvement and lead to a more positive experience for future applicants and, ultimately, a better corporate brand.

Improved employee engagement and retention

So, you’ve recruited them. Can you keep them? Recruiting and retention go hand in hand, and you can pair them up by linking that data-driven first experience with the rest of your employee engagement and experience metrics. Data-driven talent management allows you to look at drivers of employee engagement and helps you pinpoint areas where your employees may feel undervalued, underutilized or otherwise dissatisfied. Employee engagement surveys and pulse surveys are easy starting points for this, and let you get a sense of where employee morale and motivation lie and what are the influential factors affecting them. Exit interviews can reveal common reasons why employees leave. One idea would be to ask the same questions to those exiting and to those staying in the company so you can see if there are particular experiences driving people to leave.

These indicators help us build predictive models identifying employees who may be at risk of leaving the organization before they start to show outward signs of disengaging. By proactively addressing concerns and leading indicators and creating personalized targeted retention strategies for the individuals you most want to keep, you can significantly reduce turnover, retain critical talent, protect your investment in employee development and figure out how to best utilize the resources you have available for retention.

Finally, you can use data to inform initiatives boosting employee engagement. Data on employee preferences, interests and learning styles can help tailor professional development programs and broaden opportunities. Data on initiative awareness can help you see if some incentives might be failing just because your employees aren’t aware of them to begin with.

Streamlined learning and development programs

Because the world and the nature of work are changing so quickly, it’s almost impossible to predict what specific skills your employees are going to need in the next few years. Those will often change. The explosion of large language models and generative AI in the past couple of years have demonstrated that, and the growth in quantum computing is on that same trajectory. This puts even more emphasis on our organizational learning and professional development programs, and the need to promote and incentivize an adaptable, curious, creative, learning workforce.

A data-driven approach can help enhance this to ensure you’re offering targeting, relevant and effective training. By identifying individual and team-specific skill gaps and predicting emerging skills trends, tracking the effectiveness of your programs and continuously refining learning interventions through data, you can build programs leveraging the capability and energy of your current workforce to meet emerging requirements.

In an environment where agility is a competitive advantage, predicting emerging skill trends to assess those gaps becomes critical. By regularly analysing data on workforce trends and market changes, you have better means to benchmark talent goals and then identify those gaps your training needs to fill.

Predictive workforce planning

The identification of future requirements - the demand side of the labour market to talent management’s supply side - is critical for future-proofing your organization. By looking at workforce composition, employee performance, skills inventories and industry trends, you can model different work scenarios and project future workforce needs, leading to proactive recruiting and learning/development programs. It also helps to posture you to the right amount of anticipated growth, and lets you decide if you’re going to invest in full-time employees or a smaller temporary surge capacity. This leads to more transparency and accountability for hiring, and therefore better employee experience.

Predictive workforce analytics also play a huge role in succession planning or identifying how your current employees grow to fill future roles. If you build a deep bench, you want to know who on that bench is a rising leader and what subset of the population is your best group of candidates for future roles. Through data, you can identify and grow these subsets in a timely way, reducing the risk associated with the unexpected departure of key personnel.

Bringing this all together

The formulas, code and scientific method used for data-driven talent management are important, but not nearly as important as understanding the benefits. Therefore, the objectives of your talent management effort. Knowing what you want to achieve helps you ensure your organization is collecting and tracking the right data at the right time over time, feeding that data into the right analytics and that those analytics are supporting the right decisions. Laying out the benefits you want to achieve from your program helps you collect and analyze the data you need to make your talent management decisions and truly unlock the potential of your organization. Don’t let your analytics be the tree that fell in the woods, embrace data and analytics as the foundation for your decisions on talent, the decisions needed to guide your organization to success.