Skills-First Resource Library

Every organization is at a different stage in their skills journey. Our shared skill taxonomies provide value regardless of maturity level, offering solutions tailored to each organization's current capabilities and challenges. This section outlines how our shared frameworks can accelerate progress across four common stages of organizational skill maturity – though in practice many organizations may fall in between or across multiple aspects of these stages.

Stage 1: Skills as a Buzzword - Organizations recognize that skills matter but haven't implemented any true skills-first practices. Discussions about skills remain largely conceptual, with limited application in talent processes.
Stage 2: Disjointed Skills Initiatives - Organizations have begun implementing skills-first approaches in multiple areas, but these efforts remain disconnected and inconsistent. Different functions develop their own skill frameworks and definitions, creating confusion and limiting scale.
Stage 3: Data Without Decisions - Organizations have implemented consistent skill frameworks and collected substantial skill data, but struggle to translate this information into strategic workforce decisions. They have the "what" but not the "so what" of skills intelligence.
Stage 4: Strategic Skills Management - Organizations fully integrate skills into strategic business planning and execution. Skills become the foundation for how work is organized, talent is deployed, and strategy is implemented.

Stage 1: Skills as Buzzword

Common characteristics:

Traditional job descriptions focused on years of experience and degrees
Performance management tied to broad competencies rather than specific skills
L&D offerings not clearly connected to skill development needs
Workforce planning and talent acquisition driven by titles rather than capabilities

How our shared taxonomy creates value:

Our employer-built taxonomy provides an immediate foundation for practical skill application without the time and expense of starting from scratch. For organizations just beginning their skills journey, focused pilots demonstrate value quickly:

Start with a business-critical talent challenge where skills could provide immediate value – for example, if your company struggles to identifying talent for cybersecurity roles, use this as an opportunity to fix that acute challenge and gain traction.
Run role-specific pilots using our pre-built skill libraries. Start with the skill profiles we’ve prepared for each role – they’ll save you 90% of the effort compared to starting from a blank sheet. From there you can customize toward exactly what your company needs.
Position our taxonomy as a risk-free way to test skills-based approaches. Skills rollout efforts can be time intensive and expensive efforts if everything is built from scratch – starting with these tools lowers the cost, and gives a faster path to showing value.

Unlike building a proprietary framework that might never reach implementation, these industry standard resources allow organizations to move directly to application.

Stage 2: Disjointed Skills Initiatives

At this stage, organizations have begun implementing skills-first approaches in multiple areas, but these efforts remain disconnected and inconsistent. Different functions or business units develop their own skill frameworks and definitions, creating confusion and limiting scale.

Common characteristics:

Multiple skill frameworks exist across talent functions
Inconsistent skill language between recruitment, L&D, and talent management
Siloed skill data that can't be easily aggregated or analyzed
Duplicated effort as each function develops its own definitions

How our shared taxonomy creates value:

Our standardized framework provides a common foundation to align disparate skill efforts, creating consistency without requiring teams to abandon their work:

Establish each skill taxonomy as the “source of truth” – while different tech platforms or teams may feature different default platforms, the team needs to decide on which skill profile for each role is the core definition used across teams.
Use these standard definitions to identify and eliminate redundancies – are there skills you are hiring, assessing, or training for that aren’t actually critical to the role? Are some of the skills your team is using – for example, “coaching” vs “mentorship”, so interconnected that it doesn’t make sense to assess them separately?
Create governance mechanisms that maintain alignment across functions – for example by setting up a “skills committee” responsible for alignment, updating, and driving consistency throughout the organization when it comes to skills.

Stage 3: Data Without Decisions

Organizations at this stage have implemented consistent skill frameworks and collected substantial skill data, but struggle to translate this information into strategic workforce decisions. They have the "what" but not the "so what" of skills intelligence.

Common characteristics:

Skill data exists but isn't connected to business strategy
Limited integration between internal skill information and external market insights
Skill data viewed as an HR asset rather than a strategic business capability
Workforce planning still driven primarily by headcount rather than capabilities

How our shared taxonomy creates value:

Our taxonomy's integration of market data enables meaningful insights about skill availability, growth rates, and where firms are willing to pay more for an emergent or specialized skill set.

Skills data also helps firms identify how people can move within an organization. Skill analyses can rely on this taxonomy's consistent structure to enable precise mapping of current skills against future needs – to inform hiring, training, and worker advancement.

How do I get skills data on my workforce?

When implementing skills-based talent practices, skills leaders face a critical decision point regarding how to gather data on their current workforce capabilities – how should they go about inventorying skills. Most employers go down one of the following paths:

Employee self-assessment: Requiring employees to fill out “skill profiles”, sometimes including assessment activities. This provides highly detailed information about workers’ self-declared capabilities when complete, but often suffers from inconsistent participation rates and potential biases in how people evaluate their own abilities.
Manager assessment: Looking to managers to validate or review skill profiles for their direct reports. This offers valuable perspective from those who observe performance directly but creates significant administrative burden and may introduce managerial biases or knowledge gaps about specialized skills. Organizations should secure Legal/Risk/Compliance approval before implementation and clearly communicate that skill data is intended for development planning and career pathing—not performance management or promotion decisions—to encourage honest self-assessment and manager feedback.
Role-based inference: Using market trend data, career history info, or simply the skills aligned in each role to infer workers’ capabilities. This benefits from minimal direct input required, but sacrifices precision and may miss capabilities developed outside of what the system is using to infer skills.

Some successful organizations ultimately adopt a hybrid approach, using role-based inference as a foundation, supplemented by either workers or managers adjusting the baseline inferred skills associated with each worker. There’s no universally right answer here – but the consistent message from major employers is that there is huge value from understanding the real skills across your workforce.

Stage 4: Strategic Capability Management

At the most advanced stage, organizations fully integrate skills into strategic business planning and execution. Skills become the foundation for how work is organized, talent is deployed, and strategy is implemented. There’s a clear platform to draw connections throughout the organization so that skills-focused efforts are coordinated with clear roles for all involved, rather than disparate efforts operating in silos.

Common characteristics:

Workforce planning driven by capabilities rather than headcount
Skills serve as common currency across organizational boundaries
Talent deployed dynamically based on capability needs rather than static roles
Strategic decisions consider skill implications alongside financial and operational factors

How our shared taxonomy creates value:

The standardized structure of our skill definitions enables precise matching between people and opportunities based on capabilities rather than just experience or titles. Because our framework serves as a common language across organizations, it enables connections to broader talent ecosystems and promotes cross-firm worker mobility; workers can take their skills to new firms and have them recognized, and recruiters can infer the same about candidates in the market.

For example, if your company is looking for network administrators, you don’t just need to know what skills to hire for – you need to know where to go looking for candidates those skills. If you know you can rely on a specific credential, or trust the experiences of similar workers at peer firms, you know where you can go recruit; both from existing network administrators in the market, or from occupations with highly overlapping skills, like IT support technicians.

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