Current Challenges in Skills Management and How to Navigate Them

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Workforce skills requirements are changing at a fast pace. It’s estimated that by 2027, half of the skill sets needed will be different from what they are today. This can make skills management challenging and calls for sophisticated strategies to ensure optimal alignment between employee skills, business goals, and market demands.

Current challenges in skills management

Rapid technological advancements

Technology is evolving at an unprecedented pace, and keeping employee skills up-to-date is a constant challenge. This raises concerns about the obsolescence of skills, considering that currently, the shelf life of skills can be as short as 2.5 years.

At the same time, the development of technologies like generative AI is expected to create millions of new job roles, from entry level to senior management. All this suggests that organizations will have to invest in extensive reskilling of the workforce.

Skills gaps and shortages

Although skills shortages vary based on industry and location, talent scarcity is a reality for HR professionals. In the United States, labor shortages stand at 70%, and globally the figures are even higher at 75%. Businesses that fail to address skill shortage and skills gaps will struggle to fill critical roles, becoming vulnerable to competitors due to decreased productivity.

Remote and hybrid work

Hybrid and remote work arrangements present another major challenge in employee skill development, especially where soft and interpersonal skills are concerned. The biggest skills gaps are in network leadership, executive presence, authenticity, alignment, and relationship building, which have become vital in a short period of time.

Measuring skills and performance

It can be very complex to measure skills in online environments, since traditional methods may fail to accurately capture an employee’s abilities in a variety of environments, from office settings to online meetings and distributed work environments.

Strategies for effective skills management

To overcome these challenges, each organization can leverage various tools and strategies:

Dynamic approach to skills management

Dynamic skills management can complement predictive and reactive approaches through the development of real-time monitoring of shifts in skills. This requires a more comprehensive and collaborative approach that goes beyond the HR department. People and systems must be aligned, and both managers and employees must be fully involved. This can be achieved by establishing a dialogue with staff and making them part of this dynamic process by requesting regular feedback about skill-related priorities.

Quantify the impact of new technologies

Recent research showed that barely 11% of the companies studied had carried out an impact analysis to determine which roles were more likely to be affected by new technologies. Performing this analysis should be a priority for HR professionals. The resulting information can be used to develop robust governance guidelines and to make strategic decisions on the IT and data investments needed to future-proof the company’s skills pool.

In addition, it’s important to quantify the positive impact of AI. Technologies like machine learning, wide language models, or natural language processing have applications in HR, like analyzing, mapping, workforce planning, and even establishing the different levels of impact on skills and suggesting strategies to mitigate it.

Refine measurement systems

Inaccurately measuring employee skills and performance can have a negative impact on employee engagement and retention, making them feel their efforts and strengths are not valued. To improve measurement systems, first it is vital to get more granular on what to measure. Incorporating skills ontologies into these systems can help, as ontologies offer a wide-ranging and relational view of relevant skills and their connections to each other.

The resulting framework or skills matrix can be useful to update performance reviews. Approximately 95% of managers find the annual system ineffective, so increasing the frequency and depth of performance assessments could be a good starting point, while taking into account ontology data to gradually expand employee skill sets.

AI and predictive analytics

AI can analyze vast amounts of data to predict skill gaps and future training needs, which is crucial for organizations that want to get a step ahead in the current climate of uncertainty. AI-powered skills management software solutions can quickly create and update extensive skills repositories and help plan your workforce development strategy along different time frames.

These solutions can also design personalized learning paths and tailored development experiences based on individual skill levels and career goals, ensuring employees receive the most relevant and effective training.

Conclusion

Overcoming skills management obstacles is vital to improve organizational well-being and to ensure a solid competitive advantage. Workforce skill requirements are changing rapidly, companies must update their strategies to manage skills accordingly. These strategies mentioned in this article can help organizations effectively address skills gaps, stay ahead of technological advancements, and encourage a collaborative culture of continuous learning and adaptability.