10 ways to future proof your performance management strategy 

Businesses are challenged to do more with less. Whom we hire, who gets development opportunities, and even whom employers let go all become critical to improving performance and building a robust pipeline of future skills. However, today, too few employers have clear guidance on what talent data to use and when — let alone access to valid insights.

Action: Establish a clear talent insight strategy. This includes what data to use when making decisions, from hiring to retiring, guidance on when managers can or cannot rely on AI or algorithmic decisions, and the impact of these decisions on diversity and inclusion.

The evolution of talent science is a major opportunity for business acceleration thanks to rapid evolution in the data we have on our people, the insights into what drives productivity and the role of AI in leveling up efficiency. However, few organizations have developed the culture, data and insights to deliver on the promise of talent science.

Action: Start by integrating internal data, such as employee performance and skills insights, with external sources, such as information on the rising cost of skills and market data on talent availability, to drive enhanced decision-making on when to buy/build/borrow talent.

Despite advances in performance management technology, goal clarity remains the cornerstone of managing people’s performance. In Mercer’s latest study, 67% of companies focus on aligning individual goals with business outcomes but are challenged to do this at pace. Clear, consistent goal-setting is critical, especially as more Gen Z workers, who are looking for direction and purpose, enter the workforce. Spending time on this exercise is the best way to retain this talent.

Action: Cascade strategic goals from leadership throughout the organization, and calibrate expectations on both the what and the how of work. In addition, define a clear process for adjusting and revising employees’ goals throughout the year in response to evolving business priorities.

One challenge many organizations face is the atrophy of managerial skills when it comes to performance management. This is due to the relaxing of measurement during COVID, which saw a general trend away from ratings and the evolution of different ways of working.

Today, most managers (90%) still view performance management as an annual task focused on reward allocation, which falls flat when employees fail to meet expectations. Building capabilities in defining what success looks like in a role and what skills will be valued in the future is critical.

The same goes for managers’ ability and willingness to give regular feedback. Our 2025 Global Talent Trends Survey highlights that improving people managers’ skills (including in performance management and feedback) is a rapidly rising priority for HR. AI can help with some elements of performance management, but nothing beats a face-to-face conversation with a capable manager.

Action: Provide training for managers to enhance their ability to connect goals to business performance, to share what is needed for future success, and to feel comfortable offering regular feedback and coaching.

AI can revolutionize how companies approach performance management by automating tasks such as goal-setting, feedback collection and performance analysis. AI tools that “scrape” employee data to detect performance trends and areas needing improvement can help spot patterns. Generative AI is already being used to provide direct or indirect coaching to both managers and employees to help them improve their performance.

Action: Implement AI systems that can gather or prompt real-time feedback and align any advice AI gives with organizational goals and values. This can help to provide more nuanced and relevant development suggestions.

Employees thrive in environments where feedback is frequent and goals are clear. Companies that promote open communication and regular feedback tend to see higher employee engagement and productivity. Only 42% of employees report receiving regular feedback on their performance and career prospects. If it’s not achievable for managers to give feedback more often, consider how this could occur among peers and mentors.

Action: Equip managers (and coaches or mentors) with the tools for ongoing feedback. Foster a culture of peer-to-peer or skills-matched coaching in which reviews of team effectiveness is the norm. Consider the role of skills data to “match” mentors or set team goals. Over one-third (36%) of companies report that skills impact their goal-setting processes.

AI and skills-powered processes demand a rethink of which people insights are used when, such as inferred skills, rated skills or validated skills data. With job roles becoming more fluid, employees are going beyond their original job descriptions and contributing formally or informally in new ways that puts skills, not jobs, in the driving seat. For the businesses that are embracing skills-powered models, skills most commonly come into play in career development, talent acquisition and performance management. Mercer’s Skills Snapshot Survey showed that almost one in two organizations have established a skills library and are making progress in mapping skills to jobs — showing an increase in skills data.

Action: Regularly assess and update people’s skills, define future critical skills for the business, and integrate these insights into performance reviews and learning programs. Consider technology that nudges managers to take action if employees are not building new skill sets or experiences within the company.

As uncertainty increases, so does the need for timely and more relevant talent insights. Organizations that seek new insights, rather than simply relying on traditional assessment tools and processes, will be better equipped to navigate the future. This is especially important in times of rapid change when agility and flexibility are essential.

Action: Develop a comprehensive talent insights strategy that includes predictive analytics to anticipate workforce needs and adapt to market shifts. Review your use of assessment tools to ensure they reflect modern demands around managing paradoxes, risk awareness, and leaders’ openness to managing across contractual and cultural boundaries.

Employees are increasingly seeking opportunities to grow their skills and advance their careers. However, only one in three companies currently ties skills development to performance and goal-setting. Companies must do more to encourage skill-building and career progression.

Action: Provide personalized skill development plans for employees, linking learning opportunities to business needs and individual career aspirations. Leverage large language models (LLMs) to offer individual development plans tailored to each worker, or use AI to offer career suggestions linked to the content in the LLM system. 

AI will heavily influence the future of talent management. However, many organizations are not yet prepared for this shift, especially when it comes to data fitness. Without solid data on people’s potential, aspirations and skills, the productivity promise of AI will be underutilized.

Action: Invest in upskilling leaders and managers to understand the impact of data on decision-making, and encourage a discipline around collecting good data and using more predictive tools. This will help managers to leverage AI’s potential in talent management.