How Technology Powers the Transition to a Skills-Based Organization (SBO)

My last article explored how transitioning to a Skills-Based Organization (SBO) requires a strategic realignment of people, processes, and mindset .?

Now, let’s explore technology's role in this transformation. As businesses embrace a skills-first approach, the right tools and platforms can make or break the success of your SBO. In this article, we’ll explore how technology—especially AI-driven solutions—can help build, sustain, and evolve your SBO, offering practical insights into how to structure your systems and data for long-term success.

Choosing the Right Tools to Build Your SBO

Establishing a "source of truth"—the system where your skills taxonomy lives and evolves—is the foundation of any effective skills-based strategy. Before you invest in tools, it’s essential to work backwards from your business objectives to identify the correct requirements for your system architecture.

One key lesson is that relying on a single monolithic system often doesn’t work. The best results usually come from integrating best-in-class systems that complement each other. For example, pairing Oracle Dynamic Skills with Cornerstone OnDemand as your Learning Management System (LMS) or Docebo to personalise learning journeys. Let’s look at some commonly used systems:

HR Systems: Platforms like 甲骨文 Dynamic Skills come with robust skills modules that can often serve as the source of truth. If your HRIS lacks these capabilities, you’ll need to establish the skills database elsewhere.

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Learning Systems (LMS/LXP): Systems like Docebo drive learning outcomes by leveraging AI to automate learning pathways based on a skills taxonomy. The system offers tailored learning experiences, making it easier for employees to upskill or reskill based on their needs.

Talent Marketplaces/Intelligence Platforms: Tools like Fuel50 link internal talent mobility to skill development, and platforms like Techwolf use AI to enhance skills systems, automatically identifying and updating skills across your workforce.

Proprietary Systems: In some cases, organisations rely on custom taxonomies stored outside traditional platforms, such as Excel. While niche, these setups work well when integrating custom skills into a broader system.

AI: The Accelerator for Building and Maintaining Your SBO

The sheer complexity of managing skills in a dynamic environment can be overwhelming. This is where AI steps in to become a game-changer. AI doesn’t just categorise and identify skills—it continuously captures emerging competencies and updates skill data based on real-time workforce changes. Systems like Eightfold.ai and TechWolf are leading in this space, using AI to map workforce skills with unprecedented accuracy.

AI provides immense value by creating a tailored and comprehensive skills framework. It gathers data from multiple sources—HR systems, project management tools like Asana , and learning platforms—to generate a dynamic, up-to-date view of your workforce’s capabilities. This ability to evolve with your business ensures you’re always aligned with current and future needs.

Managing Ever-Evolving Skills with AI

One of the significant challenges in any organisation is that skills are not static—they evolve constantly. Manually updating skills frameworks is tedious and time-consuming. AI automates this process by continuously capturing emerging skills, ensuring that your HR and leadership teams always have the latest information.

AI goes beyond simply cataloguing skills. It can also infer hidden competencies, such as soft skills acquired through project completion, and offer development recommendations for employees to build on their strengths. When paired with public labour data, AI provides a 360-degree view of your workforce's skillsets, further enriching your skills ecosystem.

The Importance of High-Quality Data

The effectiveness of AI-driven skills management hinges on the quality of your data. Incomplete or biased data can distort AI-driven insights, amplifying issues rather than solving them. That’s why it’s crucial to thoroughly audit your data before integrating AI into your skills framework. You set the stage for accurate, meaningful results by ensuring data integrity from the start.

Trust in data is paramount. A recent 麦肯锡 survey reveals that 32% of business leaders need more confidence in understanding employees' technical skills, while 52% struggle with soft skills assessments. AI’s decisions must be explainable and data sources transparent. Trust is critical to ensuring adoption across the organisation and driving continuous improvement.

Balancing People, Process, and Technology for a Successful SBO Transformation

Successfully transitioning to an SBO involves aligning three core elements: people, process, and technology. Let’s break them down:

People: Transformation must be a collaborative effort. While HR leads the charge, managers and employees must be actively involved. Early team engagement ensures a more comprehensive and effective approach to skills management.

Process: Transitioning to an SBO is an iterative journey. Perfection is not required from the outset; instead, focus on learning and adapting. This continuous improvement model allows for refining processes and strategies, ensuring long-term success.

Technology: The right tech stack is essential. Skills management software helps you identify, track, and develop skills at scale. Investing in these tools optimises talent decisions—whether it’s for succession planning, learning programs, or internal mobility.

Mapping Skills and Structuring Data: The Key to Success

The next critical step in transitioning to an SBO is to define your skills taxonomy—a structured catalogue that categorises skills and establishes relationships between them. This taxonomy becomes the standard language for your workforce, allowing you to map skills to employees, projects, training programs, and career paths.

Once you’ve built your taxonomy, continuously update and iterate on it to reflect new skills that emerge over time. This flexibility ensures your organisation remains agile and ready to respond to technological advancements and market shifts.

Creating a Methodology for Skill Measurement

Building a skills-based organisation means more than just identifying skills—it means measuring them effectively. Striking a balance between objective assessments (like technical certifications) and subjective evaluations (such as manager feedback) offers a structured, reliable way to assess workforce competencies.

This balanced approach ensures that you capture the complexities of skill development while maintaining consistency across your evaluations. With these insights, you can guide career development, allocate resources more strategically, and make smarter workforce decisions.

Leveraging Skill Insights for Strategic Workforce Decisions

The ultimate goal of building an SBO is to leverage real-time skill insights for critical workforce decisions. Whether you’re planning future talent needs, optimising learning and development budgets, or driving internal mobility, skill data becomes your most valuable asset. With AI-powered insights, businesses can make informed, strategic decisions that drive success.

What’s Next?

As we've seen, technology is a powerful enabler in building a Skills-Based Organization. Today's tools can reshape how businesses approach skills management, from AI-powered platforms to integrated talent marketplaces. However, while technology is crucial, the roles within HR and beyond will also evolve to support this transformation. In the following article, we’ll explore the emerging and future HR roles designed to lead the charge in this new era of skills-based work. Stay tuned as we dive into the roles that will define the future of HR in an AI-driven world!