---
title: How to Objectively Compare IT Candidates
description: "How to objectively compare IT candidates: a common baseline, a per-skill rubric, a reference level, and concrete evidence."
image: https://blog.scalyz.com/hubfs/Comment%20comparer%20objectivement%20les%20r%C3%A9sultats%20des%20candidats%20IT%20%3F.jpg
---

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# How to Objectively Compare IT Candidates

![How to Objectively Compare IT Candidates](https://blog.scalyz.com/hubfs/Comment%20comparer%20objectivement%20les%20r%C3%A9sultats%20des%20candidats%20IT%20%3F.jpg)

- October 12, 2026

![Amine Ben Asker](https://app.hubspot.com/settings/avatar/634e39b7d35f4374d4633a6d3ad2f5d6)

[Amine Ben Asker](https://blog.scalyz.com/en/author/amine-ben-asker)

Three candidates, three results, and a decision to make. But are those results really comparable? **Objectively comparing candidates** is harder than it looks: without precautions, you compare noise and decide with a false sense of objectivity.

The problem is that a seemingly identical number can hide very different realities. Unequal scenarios, implicit criteria, order or similarity bias: all of these distort the comparison without you noticing. This article details the conditions for a truly objective comparison between IT candidates, and the biases to neutralize so the decision rests on the candidates, not on how they were evaluated.

 

**Table of contents**

[1. Why Comparing Candidates Is So Tricky](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num1)  
[2. The Prerequisite: A Common Baseline](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num2)  
[3. Compare by Skill, Not on a Global Score](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num3)  
[4. Anchor Each Score to a Reference Level](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num4)  
[5. Neutralize Bias in the Comparison](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num5)  
[6. Evidence in Service of the Comparison](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num6)  
[7. FAQ: Objectively Comparing Candidates](https://blog.scalyz.com/en/objectively-compare-it-candidates#Num7)  
[Conclusion](https://blog.scalyz.com/en/objectively-compare-it-candidates#Conclusion)

## 1. Why Comparing Candidates Is So Tricky

Comparing requires a common scale. Yet in many processes, each candidate is evaluated under slightly different conditions, which makes the scores incomparable without anyone noticing.

The most common traps:

- scenarios or exercises of unequal difficulty from one candidate to the next
- implicit criteria that shift from one interview to another
- order and similarity bias: the candidate seen right after a weak one looks better, the one who resembles you inspires confidence

The problem is that an unfair comparison doesn't show in the numbers. Two "7 out of 10" can have nothing in common. Comparability is built upstream. It can't be improvised at the end.

 

## 2. The Prerequisite: A Common Baseline

Before any comparison, you need an identical baseline for everyone. It's the condition without which no number has a relative meaning.

The three pillars of a common baseline:

- the same scenario, or scenarios of strictly equivalent difficulty
- the same conditions: duration, allowed resources, environment
- the same criteria, defined before evaluating the first candidate

That last point is decisive: defining your criteria before even looking at the applications prevents you from unconsciously adjusting them to your preferences. Set the rubric first, evaluate second. [The IT hiring decision tree formalizes exactly this comparison on a common baseline.](https://blog.scalyz.com/en/it-hiring-decision-tree-bias-free-5-steps?hsLang=en)

 

## 3. Compare by Skill, Not on a Global Score

A global score is the worst comparison tool. Two candidates at 7 out of 10 can be radically different: one strong in diagnosis and weak in security, the other the reverse. The single number erases that information.

A reliable comparison rests on a broken-down rubric:

- each skill is scored separately
- each criterion is weighted by its real importance for the role
- each score is justified by a factual observation

This way, you don't compare two averages, but two profiles, criterion by criterion. An essential skill weighs more than a secondary one, and a good score on a minor criterion doesn't offset a gap on a critical one.

![What Does a Score of 70100 Hide?](https://blog.scalyz.com/hs-fs/hubfs/What%20Does%20a%20Score%20of%2070100%20Hide%3F.png?width=650&height=277&name=What%20Does%20a%20Score%20of%2070100%20Hide%3F.png)

 

## 4. Anchor Each Score to a Reference Level

A score only becomes comparable when anchored to a benchmark. 7 out of 10 only means something if you know what was expected for the role. Without a reference level, comparing amounts to ranking numbers out of context.

The benchmarks to set:

- the expected level per criterion for the role, defined upfront
- an explicit pass threshold, distinct from simple ranking
- the candidates' relative performance on the same scale

What matters isn't crowning "the best in the absolute," but the one closest to the required level on the criteria that count. A candidate can dominate the comparison while staying below the expected threshold on a critical skill.

 

## 5. Neutralize Bias in the Comparison

Let's be honest: a rubric doesn't remove all bias on its own. It can creep into the choice of criteria, the wording of questions, or the way you score. But a few reflexes strongly reduce its influence.

The practices that make the comparison reliable:

- have each evaluator score individually before any group discussion, to avoid the bandwagon effect
- calibrate evaluators on scored examples, to align their reading of the criteria
- stay alert to order and similarity bias throughout the process
- handle culture fit later, after the comparison on objective criteria

Platforms like [Scalyz](https://scalyz.com) make this comparison more reliable by design: same scenario, same rubric, broken-down scores for every candidate. The structure does the heavy lifting; the evaluator keeps the final judgment.

 

## 6. Evidence in Service of the Comparison

With [Scalyz](https://scalyz.com), the objective comparison of IT candidates rests on concrete, verifiable evidence. Two features let recruiters evaluate each candidate's results on observed facts rather than impressions.

The first is the detailed report. For each candidate, it shows precisely the correct and incorrect answers. Beyond that correction, an advanced AI report provides a clear view of their approach, their reasoning, and their ability to handle technical challenges independently. You no longer compare impressions, but structured analyses and clear scores, directly comparable from one candidate to the next.

The second is the recorded session. Candidates work live in a real terminal. When they finish, the full record of their actions is available for verification. Where a score alone isn't enough to understand the work done, the session provides concrete proof: every action is traceable.

Together, these two Scalyz features let you:

- **limit bias**, by grounding the comparison in observed facts
- **strengthen the reliability of the evaluation**, with evidence verifiable after the fact
- **compare results more easily**, with clear and detailed scores from one candidate to the next

The comparison thus rests on what candidates actually did, their reasoning, and the skills they demonstrated, for more objective IT hiring decisions.

 

## 7. FAQ: Objectively Comparing Candidates

#### Why aren't two candidates with the same score comparable?

Because a global score erases the approach and the per-skill detail. Two "7 out of 10" can hide opposite strengths and weaknesses. Only a broken-down rubric allows a real comparison.

#### How do you make candidates' results comparable?

By giving them the same scenario, under the same conditions, with the same criteria defined before the evaluation. Without that common baseline, no comparison is reliable.

#### Is a scoring rubric enough to eliminate bias?

No. It strongly reduces subjectivity, but bias can lodge in the criteria and the scoring. Complement it with individual scoring, evaluator calibration, and vigilance on order and similarity bias.

#### Should you compare on a global score or by skill?

By skill, always. A global score hides the essential. Compare criterion by criterion, weighting by the real importance for the role.

 

## Conclusion :

**Objectively comparing candidates** isn't about lining up scores, but about guaranteeing they rest on the same basis: same scenario, same criteria, same reference level, and bias actively neutralized. Without that, the comparison is an illusion of objectivity.

The right question isn't "who has the best score?" but "do these scores really measure the same thing, under the same conditions?" The answer to that question is what makes a hiring decision defensible.

[Want to compare your IT candidates on a truly common, reliable baseline? Book a Scalyz demo.](https://go.scalyz.com/eng/book-your-demo?hsLang=en)

 

 

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