Knowing exactly what skills your team holds can be a business superpower in the hands of the right leaders. However, as PWC discovered in a recent survey, many HR leaders face a significant challenge in identifying the emerging skills workers will need.
Imagine what you could do if you had a detailed breakdown of the skills needed for an employee to be successful in a specific role. This is known as a skills taxonomy, and it isn’t a buzzword—it’s the future of better HR and management.
Read on to learn more about what skills taxonomy is, why it’s more important than ever, and how you can implement it smartly.
A skills taxonomy is the practice of organizing skills into distinct categories or skill clusters. This process helps you identify, classify, and define the various skills needed to perform a job in an organization. You can use it to improve workforce planning, employee development initiatives, career pathing, recruitment processes, and performance management systems.
Having a well-defined skills taxonomy is important for human resources and management teams. This detailed list helps them take a skills-based approach and better understand their employees’ talents and where additional training or development is needed to bridge skill gaps and enhance overall performance.
As an added benefit, having an organized listing of skills makes it easier to prepare job listings and search for qualified candidates when it’s time to fill open positions.
Skills hierarchy refers to the arrangement of skills in a structured order based on their complexity, specialization, or importance. Skills are organized in a way that reflects their relationships and dependencies.
For instance, within the realm of programming, a skill hierarchy might start with basic coding skills and progress to more advanced concepts like algorithms and software architecture. This hierarchy helps employees and organizations understand the logical progression of skills and plan their learning or training accordingly.
Skills categorization involves grouping similar skills together based on their shared characteristics or functions. It helps in simplifying the understanding of skills by creating broader categories.
For example, programming languages, database management, and web development could be categories within the broader technical skills domain. Categorization makes it easier to assess and manage skills, especially when dealing with a wide range of competencies.
Skill descriptions provide detailed explanations of what each skill entails. They clarify the specific knowledge and abilities associated with a skill.
A skill description for "Data Analysis" might include proficiency in statistical software, the ability to interpret data trends, and the skill to communicate insights effectively. These descriptions ensure that everyone has a clear understanding of what they need to be proficient with under a particular skill, promoting better communication and expectations.
Skill mapping involves connecting skills to relevant roles, tasks, or responsibilities within an organization. It helps you identify where specific skills are needed and provides insights into potential skills gaps.
By mapping skills to job roles, businesses can make informed decisions about recruitment, training, and workforce planning. For example, a skill map might show that "Project Management" is crucial for roles like team leads or project managers.
These concepts work together to create a structured framework for understanding, organizing, and utilizing skills within individuals and organizations.
A skill hierarchy guides skill development, categorization simplifies the process, skill descriptions provide clarity, and skill mapping aligns skills with organizational needs.
Executive leaders must understand the importance of developing a comprehensive skills taxonomy. A well-defined skills taxonomy helps employers identify and develop the right talent they need in order to remain competitive.
In addition, new trends like remote work require a greater focus on soft skills such as communication, collaboration, problem-solving, and adaptability. As such, employers value employees who are able to effectively communicate and collaborate with their colleagues from different locations.
To stay ahead of the competition, enterprise businesses must also have employees with the capacity to think critically and process conceptual knowledge in order to solve complex problems. Employees must also possess the ability to quickly adapt and learn new technologies.
We’ve discussed why a skills taxonomy is important, but let’s talk about the many benefits of implementing it into your business.
Identifying gaps in employee skills and knowledge is key to providing adequate training. With the changing landscape of workplace demands, it can be difficult to determine where skill gaps exist.
Utilizing a skills taxonomy can help systematically clear this up by providing an organized way of structuring the needed skills and then cataloging and tracking employee skills and knowledge across various departments and job roles.
Of course, the step after identifying gaps is to improve them through training, but that can only be done effectively if you first define those skills clearly. This way, you can track employee progress against a specific set of skills that have already been defined by the skills taxonomy.
By knowing what skills an employee needs to improve on, you can then tailor training plans around them and provide them with the resources they need to succeed. This personalized approach maximizes employee engagement and facilitates continuous growth.
But even apart from the training aspect, employees can, by way of the skills taxonomy, have a clearer grasp of exactly the skills they need, their strengths and weaknesses, and the broader competency required in order to do well in their occupations.
Better performance and productivity come from a clear set of expectations and can be used as a catalyst to encourage employees to do their best work possible. Now that they know what skills are required for success, they can confidently do well in their role, leading to better outcomes for the company overall.
A skills taxonomy also helps HR teams to develop and streamline training and development programs because skill sets will be clearly defined, not left up to “the way we’ve always done it” or according to what new skills are trending at the moment. Roles with similar skills can be grouped together so that educational objectives and programs can be developed more effectively.
Speaking of streamlining the process, this is where AI can play an important role, especially with how quickly it has advanced both in capability and popularity recently.
AI-powered learning platforms can provide organizations with an invaluable resource in the creation and maintenance of their skills taxonomies. Since they can automatically analyze employee skills data, these platforms can identify skill gaps and deficiencies that might otherwise be overlooked in manual processes.
AI learning platforms can also make predictions about which critical skills should be prioritized in the future to ensure an organization maintains its competitive edge. Ultimately, they can be a powerful tool for helping organizations reach their goals and remain competitive in today’s market.
AI-powered upskilling platforms offer organizations a powerful and efficient solution for creating and managing their skills taxonomies. These platforms use AI algorithms to analyze data and identify skill gaps in real-time, ensuring an accurate view of the organization’s skill set.
Additionally, this process can be easily scaled across larger organizations, providing invaluable insight into the skill sets of various departments and teams. With such comprehensive solutions available, organizations can confidently build and maintain the right skill set for their organization.
Skills taxonomy requires a clear and consistent definition of skill categories that reflect the organization’s needs and goals. However, different stakeholders may have different perspectives and preferences on how to classify and label skills, which can lead to confusion and inconsistency. Moreover, skill categories may change over time as the organization evolves and adapts to the changing market conditions and customer demands.
Establishing a balance between the level of detail and the level of abstraction of skills is an integral part of skills taxonomy. Too much detail can make the taxonomy too complex and cumbersome to use, while too little detail can make the taxonomy too superficial and irrelevant to the specific roles and tasks. Finding the optimal level of granularity can be challenging, as it depends on various factors, such as the size and diversity of the organization, the nature and scope of the work, and the availability and quality of data.
A seamless integration with the existing systems and processes of the organization, such as learning management systems, talent management systems, performance management systems, and recruitment systems is also required. However, integrating skills taxonomy with these systems can be difficult, due to differences in data structures, formats, standards, and protocols. Moreover, integrating skills taxonomy with these systems may require significant changes in the workflows, policies, and practices of the organization.
Skills taxonomy requires a high level of user adoption and engagement from both employees and managers. However, users may resist or ignore skills taxonomy if they do not understand its benefits, value, and relevance to their work. Moreover, users may lack the motivation, confidence, or ability to use skills taxonomy effectively, especially if they do not receive adequate training, support, or feedback.
The first step in implementing a skills taxonomy is identifying the skills required by employees. This can be done by looking at the tasks the business needs to accomplish and identifying the skill set needed to perform those tasks.
It’s also possible to take a more data-driven approach by analyzing employee job descriptions and performance records. Creating a comprehensive list of required skills enables the business to create a roadmap for achieving its goals.
Once the skills have been identified, the next step is to create a standardized framework that can be used consistently throughout the organization. A standardized framework can help ensure that the skills taxonomy is in line with the organization’s goals and that everyone’s on the same page. It is important to try and keep this framework flexible to allow for future changes, as job roles, industry needs, and business goals can change over time.
After creating the framework, the next step is to roll it out to employees. This communication should be comprehensive, and employers should make sure that employees understand the purpose, benefits, and expectations of the skills taxonomy.
Employees should be informed about how their skills will be assessed and how that information will be used to guide their professional development. It’s crucial to take a collaborative approach, ensuring active participation by employees in shaping the skills taxonomy.
A skills taxonomy can only be effective if the business is monitoring and evaluating its implementation continuously. It is crucial to track progress regularly, assess employee performance data, and adjust the taxonomy to ensure it aligns with the business’s changing needs. This way, organizations will identify any skills gaps and formulate strategies to close them continually.
Implementing a skills taxonomy can be challenging for businesses, as it may be met with resistance or may be hard to measure training program effectiveness.
Transparency and effective communication are key to overcoming these challenges. Businesses can work towards implementing a skills taxonomy through a cultural change program that addresses the roles and responsibilities of all employees.
In 2024, there’s never been a better time to get ahead of the competition by creating and implementing a skills taxonomy in your business.
This will allow you to streamline the process of understanding employee skills and develop programs to meet their needs so that the organization benefits overall.
Doing so right now will pay dividends not just as soon as the programs are implemented, but for years to come. Plus, with the help of an AI-powered LXP, these developmental programs will be even easier to create, implement, and tweak, all thanks to data-driven processes that streamline your efforts.