Beyond the bell curve: Why Job Targets are the smarter way to hire

From school exams to team leaderboards, we’re used to seeing where we stand among the group. The idea of a percentile rank, knowing if you’re in the top 10% or somewhere in the middle, is intuitive. This comparison is often visualized with a bell curve: a statistical graph showing how scores are distributed across a population, with most results clustering around an average. So, when other cognitive tests provide these familiar percentile scores, it’s natural to ask, “Why doesn’t the PI Cognitive Assessment?”

The answer is simple: For hiring, there is a method that is more precise, more effective, and more fair. The PI Cognitive Assessment (CA) was built not as a general IQ test, but as a tool designed specifically for the workplace. Instead of comparing candidates to a generic population, we should compare them to the demands of the job.

It’s the difference between running a race and clearing a bar.

The race vs. the high jump: Two ways to measure performance

To understand why we prioritize a Job Target, we need to distinguish between two types of assessment scoring: norm-referenced and criterion-referenced.

Imagine a 100-meter dash. Your finishing time of 11.5 seconds is only meaningful when compared to the other runners. If you finish first, you’re the fastest in that group. This is norm-referenced scoring. It’s all about ranking you against a “norm group.” The bell curve and percentiles are the classic tools for this.

Now, picture the high jump. A bar is set at a specific height, let’s say 6 feet. This is the criterion. You either clear the bar or you don’t. Your success isn’t determined by whether other athletes cleared it; it’s measured against that pre-set standard. This is criterion-referenced scoring.

The PI Cognitive Assessment is designed as a high jump, not a race. It is a criterion-referenced tool, meaning scores are interpreted based on how a candidate scores in relation to a Job Target set by the hiring manager, not a bell curve. 

Four reasons to use a target, not a bell curve

Statistically, the bell curve represents a normal distribution, a probability distribution that is symmetric about the mean. This shape shows that data points near the average are far more common than data points at the extremes. It’s a powerful visual for norm-referencing because it instantly maps an individual’s score to a specific percentile rank within that group. Many assessments used around the world incorporate percentile rank in their analyses. And while it could be a great way to see how everyone leaves the starting blocks, it doesn’t tell you who is actually equipped for the hurdles ahead.

Relying solely on a bell curve or percentile to evaluate candidates isn’t just less effective; it can be misleading and risky. Here’s why the Job Target is the superior tool for hiring.

1. “Smartest” isn’t always “best fit.” 

Hiring the person with the 95th percentile score might seem like a win, but what if the job doesn’t require that level of cognitive complexity? The goal is not to find the “smartest” person in the pile; it’s to find the person with the right cognitive horsepower for the role’s challenges. The Job Target defines that “just right” fit. It’s also what separates PI with its focus on Head, Heart, Briefcase, looking at the entire individual instead of just a number that represents them. 

2. You’re comparing to the wrong crowd (like apples to oranges).

The PI CA norms are built from a massive Reference Group of over 288,000 global respondents. This group is intentionally diverse across industries, from finance to manufacturing. While this reference group is fantastic for establishing data driven benchmarks that serve as starting points in the PI Job Assessment, it’s the wrong group to compare your candidate against. The Job Target focuses the comparison on what matters: the cognitive demands of the specific role you’re hiring for.

3. It creates unnecessary legal risk. 

This is a critical point. The landmark 1971 Supreme Court case Griggs v. Duke Power Co. established a vital precedent: Any test or hiring requirement must be demonstrably related to job performance. A generic percentile rank from a broad population is difficult to prove as job-related.

A Job Target, however, is designed to be defensible. When set properly, using tools like the PI Job Assessment or a validity study, it establishes a clear, evidence-based link between the required score and the needs of the job. This aligns with professional standards from the EEOC, APA, and SIOP, ensuring a fair and legally sound process.

The PI approach: Hitting the target

The PI2 platform helps you create a defensible and realistic Job Target. This score represents the cognitive baseline needed for success in a role. It ensures you’re evaluating candidates against the job, not one another. The decision was made to remove the percentile comparison in our software to better align the platform with the CA’s design as a criterion-referenced assessment. This ensures the focus remains on a candidate’s fit for a role’s specific demands rather than on a normative comparison.

Remember: The CA is a powerful predictor of job performance, but it should always be used as just one data point in your hiring process, alongside the PI Behavioral Assessment and other relevant information like skills and experience. 

Hiring isn’t a simple 100-meter dash. It’s a decathlon, with multiple events contributing to the final score. For the cognitive event, you don’t need to know who ran the fastest time in history; you just need to know if your candidate can clear the bar for the job at hand.