Performance-Based By Design

  • Candidates must engage, persist, and complete hands-on challenges—revealing real ability rather than stated experience.
  • ERA cannot be completed by résumé-generation tools or automated responses; success requires human reasoning and follow-through.
  • The core traits measured—problem-solving, attention to detail, adaptability, perseverance, and abstract reasoning—predict success in nearly every occupation.
  • No math prerequisites and minimal technical requirements ensure broad access while maintaining a high performance bar.
  • Acquire soft skills that will serve you well throughout your work life.
  • Individuals who successfully complete ERA consistently demonstrate the capacity to succeed in training and on the job.

Overview

The Employment Readiness Assessment (ERA) introduces a fundamentally new approach to identifying high-potential candidates in today’s hiring environment.

Traditional screening tools—résumés, questionnaires, and even AI-assisted applicant filters—are increasingly ineffective in distinguishing truly capable candidates from those who simply sound qualified. With the widespread use of AI-generated résumés, nearly every applicant can appear polished, articulate, and well-matched on paper.

The ERA addresses this challenge by supplementing existing screening methods with a hands-on, performance-oriented assessment that evaluates what candidates can actually do—not how well they can describe themselves.

Simply put, the ERA measures what matters most—and because it is not AI-solvable, success depends totally on the participant’s own effort.

Why ERA Is Different

The ERA is designed to evaluate core performance traits that predict real-world success across roles, industries, and training pathways. These attributes include:

  • Attention to detail

  • Problem-solving ability

  • Adaptability

  • Perseverance

  • Abstract reasoning

These are the traits shared by high performers—and they are not reliably captured by résumés, questionnaires, interviews, or automated keyword screening.

The ERA is especially effective at screening AI-generated applications, identifying candidates who can genuinely perform rather than merely present well.

A Closer Look at ERA Results

Each ERA produces a clear, actionable report that includes:

  • Assessment completion
    Confirms the candidate’s ability to engage, persist, and finish a structured task.

  • Key performance indicators (KPIs)
    Measures the traits most closely associated with workplace and training success.

  • Time to completion
    Provides insight into focus and efficiency.

Together, these indicators give employers and program administrators a reliable, performance-based signal of candidate readiness.

How the Assessment Works

The ERA is built around hands-on, interactive challenges that require candidates to actively engage, think, and perform.

Key characteristics include:

  • Learning by doing
    Candidates complete practical, task-based challenges, minimizing cultural/language bias.

  • Role-agnostic by design
    The assessment is applicable to all entry to mid-level job openings because the attributes measured are universal to success in all roles.

  • No math dependency
    The ERA does not evaluate math skills, removing a common barrier when it is unrelated to job performance.

  • Minimal prerequisites
    Candidates only need:

    • Basic English or Spanish comprehension

    • Keyboard and mouse skills

This makes the ERA broadly accessible while maintaining a high standard for performance.

The Bottom Line

In an era where AI can generate impressive résumés in seconds, the ERA restores meaning to candidate evaluation.

It does not replace existing screening tools—it strengthens them, ensuring that the individuals who advance are those with proven ability, motivation, and readiness to succeed.

ERA finds the candidates who can actually perform.

To talk with one our product specialists about what NCLab can do for your enterprise, schedule a call below or fill in the Get-In-Touch form below.

 

 

 

 

 

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