Lecture 6 – Job Simulations: How to Assess Skills, Predict Performance & Hire with Confidence
Resumes and interviews only tell part of the story. Research consistently shows that job simulations are the most accurate predictor of future job performance, but how do you design assessments that are fair, effective, chat- proof, and truly reflective of the role?
In this session, we’ll explore how forward-thinking organizations are embracing skill-based hiring, moving beyond traditional credentials to focus on what candidates can actually do. You’ll learn how AI-powered job simulations and thoughtfully designed assessments are helping teams evaluate both technical and soft skills more objectively, and at scale, reducing their interview volumes, time to hire and employee turnover.
We’ll cover key considerations for building your assessment process, ensuring a positive candidate experience, and preventing cheating, while keeping fairness and performance prediction front and center.
What You’ll Learn:
- 🧭 Why skill-based hiring is gaining traction and how it creates more inclusive, effective hiring processes
- 🤖 How AI is transforming skill evaluation, from scalability to intelligent scoring
- 🎯 What matters most in designing assessments, including relevance, role alignment, and soft skill measurement
- 🛡️ Best practices to ensure integrity and prevent cheating, without compromising candidate trust
- 📈 How to interpret assessment insights to support confident, data-driven hiring decisions
About Canditech:
Canditech helps leading companies avoid expensive mis-hires, and make confident, fast and objective hiring decisions by automatically evaluating both technical and soft skills using job-simulation tests – the best predictor of future job performance.
Speaker Info: