Decode the Resume Part 2: 3 Advanced Job Skills Assessment Techniques

In Part 1 of our series on job skills assessments, we explored 4 simple ways to verify skills as identified by RedThread Research. RedThread members may access the full report authored by Heather Gilmartin and Dani Johnson.

In Part 2, we delve into 3 sophisticated techniques that leverage both internal and external data to ensure a more accurate job skills assessment approach.

As the landscape of skills-based recruiting expands, it becomes evident that some roles and contexts demand more nuanced and data-intensive verification methods than others. 

1. Comparison to External Benchmarks

When verifying skills, it’s crucial to measure them against established external standards. Yet, according to RedThread, only 11% of organizations do so.

Benchmarking helps companies understand how their candidates' skills stack up against industry standards. In addition to providing a clear perspective on talent level relative to the broader market, it helps the organization future-proof their talent strategy and competitive edge. 

However, relying solely on external benchmarks may overlook unique aspects of a company’s culture or specific job roles that require customized skill sets. This approach also assumes that industry standards are up-to-date and sufficiently granular for an organization’s needs, which may not always be the case in fast-changing industries.

Effective benchmarking relies on advanced skills intelligence tools, thus requiring an investment in technology or access to benchmarking data. As with other verification methods, benchmarks are most effective when used in conjunction with internal assessments. These platforms can integrate with existing HR systems to provide deeper insights and real-time data that help refine benchmarking efforts against industry standards. 

2. Inference from HR Data

Skills prediction based on HR data involves analyzing information from HR technology systems to infer employee skills. AI models predict employees’ skills based on a range of data sources. It’s quick, effective, and doesn’t require much employee involvement, RedThread explains. They report that 13% of employers currently make use of this career skills assessment method. 

This method uses historical data, such as past job performances, training records, and employee interactions, to predict skill levels and identify potential gaps. As it continues to evolve, the accuracy of skill predictions generally increases with the number of data points processed by AI.

While powerful, this approach can be limited by the quality and completeness of the data collected. Biases in historical data can also lead to skewed predictions, making it essential to continuously update and review data inputs to ensure accuracy and fairness.

HR data on industry skills is typically purchased through Human Resource Information (HRIS), Learning Management (LMS), Talent Marketplaces, Applicant Tracking (ATS), and Performance Management systems. Such systems enhance the accuracy of skills predictions by utilizing machine learning models which improve as they process more diverse and comprehensive data sets. 

3. Inference from Work Data

Using work system data to measure skills involves analyzing real-time data from work processes and outputs. By evaluating the quality, efficiency, and creativity of the work produced, organizations can gain a precise understanding of an employee's practical skills.

This method requires sophisticated data analysis tools and expertise. It is also more complex than using HR data because it demands advanced technical integrations and substantial cross-functional collaboration to identify relevant metrics for specific skills. 

However, RedThread concludes that this is the only skills verification method that offers real-time insights into daily work and enables decisions at scale, based on performance data. This is where One Model shines, by seamlessly integrating with multiple data sources across the organization, enabling a more holistic and real-time assessment of employee skills based on actual work outputs.

How One Model Partnerships Elevate Job Skills Assessment with Advanced Data-Driven Approaches

Lightcast is a leading expert in the labor market. They collect and process a wide array of data, including job postings, resumes, and work history profiles. This data is aligned to job titles and skills classifications every two weeks.

By merging Lightcast's extensive knowledge of the external labor market with One Model's ability to unlock people data, organizations can gain business insights relative to industry-wide talent trends.

A One Model partnership empowers HR teams to: 

• Enhance the consistency of data in reporting by adding standardized titles to current roles 
• Analyze talent headcount, career paths, retention with accuracy
• Better align skills with job roles to enhance skills knowledge and plan for the future 

Ready to spend your time sharing insights, not integrating your people data?

Learn how One Model integrations can help you see the whole picture.

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