This section provides practical guidance for embedding standardized skills data into your HR ecosystem, recognizing that most organizations will need to work within their current technology constraints rather than implementing new purpose-built solutions.

Current State Assessment

Before diving into technology implementation, assess your current systems landscape to understand integration possibilities and limitations:

Evaluate your existing HR tech infrastructure for skills-readiness:

• Which systems currently store or use skill information?
• What skill frameworks, if any, are already in use?
• Where are the most critical integration points for skills data?

• Identify which systems serve as "source of truth" for different data elements

Create a systems map of skill data flow:

• Document where skill data needs to be created, stored, updated, and consumed
• Map current and desired data flows between systems
• Identify gaps in existing architecture that might hinder implementation

This assessment provides the foundation for a technology roadmap that supports your skills strategy while working within practical constraints. Most organizations adopt a phased approach that strategically integrates skills where they deliver the most immediate value.

Core Systems Integration Strategies

Different HR systems play different roles in a skills ecosystem. Here's how to approach integration of shared taxonomies with key system types, working within existing technological constraints:

HRIS Systems: 

Most HRIS platforms now have some skills functionality, but capabilities vary widely. Options for integration include:

• Using native skills modules where they exist, adapting the shared taxonomy to fit available structures
• Creating custom fields to track critical skills when native support is limited

• Consider where skills relate to other HR data (e.g., positions, training records)

Applicant Tracking Systems:

Connecting shared taxonomies to job requisitions and candidate assessments:

• Tag job postings with standardized skills from the shared taxonomy
• Create structured candidate assessments aligned to required skills
• Enable skill-based searching and matching of candidates where possible

Learning Management Systems:

Aligning learning content with shared skill taxonomies:

• Tag courses and resources with relevant skills and levels
• Create learning paths based on skill progression
• Enable skill gap-based recommendations where possible

Talent Management Platforms:

Incorporating shared taxonomies into performance management and succession planning:

• Base performance criteria on standardized skill definitions
• Track skill acquisition and development in review processes
• Include skill considerations in succession planning and readiness assessments

Data Integration Challenges and Solutions

Skills data often exists in multiple systems with different structures and terminology. Here's how to address common challenges within existing technology constraints:

Handling inconsistent skill terminology across legacy systems:

• Start with high-value use cases rather than attempting complete integration – getting buy-in on priority roles to gain early traction
• Focus on standardizing terminology for new implementations while gradually aligning legacy systems
• Create simple reference guides that help translate between different terms

Approaches for mapping proprietary skill frameworks to shared taxonomies:

• Identify conceptual matches rather than forcing perfect one-to-one mappings
• Focus on equivalence of meaning rather than exact terminology
• Start with the most frequently used skills to deliver quick value

The journey to skills-first talent practices doesn't require replacing your HR technology. By taking a pragmatic approach that works within existing constraints while strategically implementing shared taxonomies where they add most value, organizations can make meaningful progress toward skills-based talent management regardless of their current technology landscape.