Latin America at GroupM

Federico Demarin

Succession planning has been around for several decades now, and with good and bad applications, it is still a prevailing talent management practice for medium and large companies.

In its narrow use, companies identify potential successors for management and leadership positions with the process. Clearly, this view only focuses on the company's interests around business continuity and the costs associated with recruiting leaders, which could have a significant impact on personnel costs for companies with high turnover.

Broadening the perspective is also a way to understand where your leadership talent sits in your pipeline, though these companies also need to enrich it with a definition of what leadership talent means in that organization in particular, and that is no easy task. When it comes to ‘potential for leadership,’ most companies struggle to define it, understand it, and apply it consistently. The usual scenario is to have a broad definition of leadership competencies with elevated words about what it means to lead, while in practice, people get promoted due to their individual performance, mostly driven by hard results and technical skills. When this happens, the actual success model gets projected into the future once those being promoted use the same criteria to identify the potential to lead others. Even rarer is to have companies clearly explaining what would happen after they start a leadership path, getting involved in 'people' issues they thought belonged to the HR department.

Research shows the new generations are less interested in set paths as they prioritize exploration and choices. The concept of career navigation addresses this idea as different routes for development, which could include side moves and drastic changes. A good analogy would also be a climbing wall, with multiple possible routes with different difficulty and effort levels, so each individual could define the balance between progress speed and stretch, understanding they could grow in different ways depending on that combination. Needless to say, this poses a very different challenge for companies trying to manage talent. While the ‘set path’ concept demands clarity and commitment through decisions and budgets, the ‘navigation’ would require the search for alternatives and risk-taking in terms of performance, understanding opportunities may not necessarily fall in the hands of the most qualified people for the task, but in those with a clear potential to continue growing. It also means these alternatives would require strong collaboration across the enterprise, which is usually hard in companies with strong departmental cultures and silos. Lastly, mapping diverse opportunities with people's desires and expectations also demands data, business intelligence, and good technology applications in order to be sustainable. Companies with precarious data strategies will struggle to go beyond a ‘box ticking’ exercise.

So, how could this be done successfully, and where should it evolve? The companies that manage succession planning and career development successfully invest in data management and talent management technology, while they also have strong commitment and follow-up through decision-making and budgeting. The only way this could work is by having consistency and continuity, making sure career opportunities decisions such as promotions or recognition correlate with those assessments and plans and are not cut short by any short-term financial struggle. This means companies with a clear talent strategy tied to a mission and a vision.

"Companies with precarious data strategies will struggle to go beyond a ‘box ticking’ exercise"

The future: Succession planning and individual development plans could easily profit from the AI evolution we are experiencing now. Although the technology is still rough, there are clear gains companies could achieve if they manage some basics:

1) Collect and Organize the Right Data: AI could eliminate the hard task of combining the data from multiple internal and external sources to produce development alternatives for people, where anyone in the organization could ask a virtual assistant (bot) to model potential development plans that consider their preferences. All learning content and opportunities available inside and outside, all job details in the entire company, all open vacancies advertised internally, and more. Logically, it will not be perfect at the beginning; mistakes will happen, but that is where the current power of this technology lies: learning from experience.

2) Experts in learning & development could assist AI in evolving and sophisticating their outputs by incorporating career success data, promotions, exits, exit interviews, and feedback from participants.

3) Embracing AI as an enterprise tool that will change the way people work, whether we like it or not. Everyone should understand its purpose and capabilities, as well as the best ways to prompt it and improve it. This is not a technology that learns from the IT department and programmers alone; it needs massive learning that can only be achieved by massive use from users.

Of course, all this will be in vain if companies are still worried about ticking boxes. Success will still rely on solid talent strategies sponsored by true leaders who believe in the long-term edge talent differentiation gives when compared to short-term P&L results.