Nowa strona 1 » How to Build a Skills Taxonomy Aligned with Your Operating Model

Subtitle: Structuring and managing skills for a future-ready workforce.

Introduction: The Importance of a Well-Structured Skills Taxonomy

As businesses evolve, so do the skills and capabilities required to succeed. Whether it's adapting to new technologies, entering new markets, or navigating changes in customer behavior, organizations must ensure their workforce is equipped with the right skills at the right time. A well-designed skills taxonomy is crucial for aligning learning and development initiatives with organizational needs, ensuring that employees develop the skills that support both the current and future direction of the company.

A skills taxonomy is more than just a list of competencies; it is a structured framework that classifies the various skills, capabilities, and competencies required for different roles within the organization. Aligning this taxonomy with the organization's operating model ensures that learning and development resources are strategically deployed to meet business objectives.

In this guide, we will walk through the process of building a skills taxonomy that not only categorizes and structures skills across functions and roles but also integrates with business needs and supports ongoing organizational change.

Step 1: Differentiating Between Skills, Capabilities, and Competencies

Before diving into taxonomy design, it’s essential to understand the nuanced differences between skills, capabilities, and competencies. While they are often used interchangeably, each term has its distinct meaning and role in talent management.

A. Defining Skills

Skills are specific, observable abilities that can be learned or developed through practice. They are typically task-oriented and can be technical (e.g., coding, data analysis) or soft skills (e.g., communication, problem-solving). Skills are usually specific to roles or functions.
Practical Example: In an IT department, a skill could be Python programming, while in a customer service role, a skill might be active listening.

B. Defining Capabilities

Capabilities are broader than skills and refer to a combination of knowledge, skills, and behaviors that enable individuals to perform at a higher level. They are often linked to a set of skills that work together to achieve organizational goals. Capabilities are typically linked to functional areas and can be cross-role.
Practical Example: The capability of data-driven decision-making involves a blend of analytical skills, technical skills, and the ability to interpret data in business contexts.

C. Defining Competencies

Competencies refer to the set of skills, knowledge, and behaviors that are necessary for an employee to succeed in their role. Competencies are often tied to the organizational culture, values, and the leadership behaviors needed at various levels.
Practical Example: Leadership as a competency would encompass skills such as decision-making, strategic thinking, and emotional intelligence, combined with behaviors that align with the organization’s leadership values.

By defining these terms clearly, you set the stage for a taxonomy that distinguishes between functional requirements (skills), business-critical strengths (capabilities), and broader performance expectations (competencies).

Step 2: Structuring Skill Libraries Across Functions and Levels

A skills taxonomy should be structured to cover all functional areas within the organization, ensuring that learning and development efforts address the skills and competencies required for both the present and future state of the business.

A. Organizing Skills by Function

Start by categorizing skills into broad functional areas (e.g., sales, IT, HR, marketing). Within each function, break down the skills into subcategories based on the tasks employees perform and the outcomes expected of them.

Practical Example: In a Sales function, skills might be categorized into areas such as customer relationship management, negotiation, and market research. Each of these categories can be further broken down into specific skills, such as cold calling, contract negotiation, and CRM software proficiency.

B. Classifying Skills by Role and Level

Once skills are categorized by function, it’s important to map them to the different levels of the organization. For instance, an entry-level employee may require foundational technical skills, while a senior leader may need advanced leadership capabilities and strategic thinking skills.

Practical Example: A skills taxonomy for a Finance function might look like:
- Entry-Level (Analyst): Basic skills in financial modeling, Excel proficiency, and budget tracking.
- Mid-Level (Manager): Advanced skills in financial forecasting, reporting, and project management.
- Senior-Level (Director/VP): Strategic capabilities in financial strategy, M&A experience, and investment analysis.

This hierarchical structure allows HR to ensure that learning content is targeted to the right level and provides a clear growth path for employees.

Step 3: Tagging Learning Assets to Skills and Roles

One of the key benefits of a skills taxonomy is its ability to help HR professionals and learning leaders tag learning assets (e.g., courses, workshops, on-the-job training) directly to specific skills and roles. This ensures that learning resources are relevant and accessible for employees, regardless of their level or functional area.

A. Mapping Learning Assets to Skills

For each skill identified in the taxonomy, ensure there is corresponding learning content that can help employees acquire or refine those skills. Learning content can range from formal courses, microlearning modules, and certifications to coaching, mentorship, and job rotations.

Practical Example: If a skill in the taxonomy is project management, tag learning content such as Project Management Professional (PMP) certification courses or Agile project management workshops.

B. Linking Learning Assets to Roles and Competencies

In addition to mapping learning to skills, it’s equally important to link content to roles and competencies. For instance, a leadership development program could be tagged to all leadership competencies, while specific technical training could be linked to roles that require those technical skills.

Practical Example: For roles such as data analyst or data scientist, tag learning content like SQL certification courses or data visualization workshops to ensure employees are equipped with the necessary tools for success in their roles.

Step 4: Maintaining Relevance as Roles Evolve

As organizations grow and adapt, the roles within them also evolve. New technologies, industry trends, and business strategies can shift the competencies required for specific functions. A well-maintained skills taxonomy should evolve alongside the business to ensure it remains relevant and forward-thinking.

A. Regularly Review and Update the Taxonomy

The world of work is evolving rapidly, and skills that were relevant a few years ago may no longer be sufficient. It’s essential to periodically review and update the skills taxonomy to ensure it reflects the latest business needs and emerging trends. Regular feedback from employees, managers, and business leaders will help keep the taxonomy aligned with the changing landscape.

Practical Example: A retail company that undergoes a digital transformation might find that e-commerce and digital marketing skills are now critical. In response, HR could update the taxonomy to include new skills related to SEO, digital advertising, and user experience (UX) design.

B. Adapt the Taxonomy to New Roles and Capabilities

As new roles are created or business strategies change, HR should be agile enough to update the taxonomy and map relevant skills to these new positions. The rise of automation, AI, and data analytics has created entirely new roles in many organizations, requiring a rapid response in terms of taxonomy updates.

Practical Example: With the introduction of machine learning engineers in a tech firm, HR would need to update the taxonomy to include advanced coding skills in Python or R, along with skills in machine learning algorithms, which are essential for the new roles.

Conclusion: Building a Taxonomy for Future-Proofing the Workforce

A well-structured skills taxonomy aligned with the operating model of an organization is the cornerstone of a future-ready workforce. By differentiating between skills, capabilities, and competencies, HR professionals can ensure they are categorizing and structuring the right elements of the workforce to meet current and future business needs. Moreover, tagging learning content to specific roles and continuously maintaining relevance ensures that the taxonomy adapts to both technological advancements and evolving organizational strategies.

Building and managing a skills taxonomy is not just a one-time project but an ongoing, dynamic process. It requires regular reviews, updates, and collaboration across departments to ensure the workforce remains equipped to meet strategic goals. When done right, a skills taxonomy not only enables more effective talent management but also fosters an adaptive, resilient, and high-performing culture that can thrive amid change.