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Behaviorally Anchored Rating Scales (BARS): A Practical Guide

Behaviorally Anchored Rating Scales (BARS): A Practical Guide

Author
Nischal V Chadaga
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December 3, 2024
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5 min read
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Many companies across the globe still rely on outdated performance rating scales that offer vague and unhelpful feedback while failing to capture the true essence of employee performance. This is where Behaviorally Anchored Rating Scales (BARS) can help. BARS allows leaders to link noteworthy workplace behaviours to ratings, facilitating a fair evaluation of performance, and making it objective and actionable.

However, BARS isn’t ideal.  Like any other performance measurement system, it has its demerits. While it helps managers evaluate employees more objectively, there are challenges—from implementation issues to scalability in dynamic work environments. In this article, we look at the advantages and disadvantages of the BARS system and offer ideas on how leaders can effectively implement BARS despite its limitations, and ways to modify it for modern teams.

What Is BARS, and Why Should Leaders Care?

BARS is a structured performance evaluation method that links numerical ratings to more specific workplace behaviours that can be used to assess the temperament of employees at work. Instead of broad subjective ratings (e.g., "Meets Expectations"), it allows leaders to evaluate different employee performance levels based on specific behaviour patterns. BARS provides a holistic view of employee performance and humanizes how leaders communicate feedback to employees, encouraging them to work on their drawbacks, resulting in highly-driven teams that work together to achieve professional excellence.

Example: "Collaboration" Evaluation in a Workplace Setting

Rating Behavioural Indicators
5 (Exceptional) Consistently promotes a highly motivated, collectively united and growth-driven work environment. Regularly shares knowledge, mentors peers, and resolves conflicts effectively.
4 (Above Expectations) Works well in teams, encourages constructive discussions, and contributes positively to team projects. Occasionally shares insights and best practices.
3 (Meets Expectations) Participates in teamwork but may need occasional guidance in conflict resolution and group communication.
2 (Needs Improvement) Collaborates reluctantly, may struggle with team communication or fail to engage proactively in discussions.
1 (Unsatisfactory) Is resistant to collaborating with team members, breaking unity and hesitates to work with others, showing poor team spirit and limiting professional growth.

Why BARS Works for Organizations

Hiring talent is costly. Organizations cannot afford to evaluate their employees based on vague pointers that leave no scope for improvement. With its unique feature of linking behaviours to performance rating parameters, BARS helps retain talented employees and motivates them to improve their outputs, driving tremendous results that contribute to the bigger picture. Here are the benefits of using BARS for employee performance evaluation.

Reduces subjectivity – Anchors performance to observable behaviours, making reviews fairer and holistic. 

Improves feedback quality – Employees are more receptive to feedback, as the system allows them to assess where they fall short, instead of vague evaluations. 

Enhances development plans – Motivates employees to take note of the organization’s goals and align their actions accordingly, resulting in a more understanding workforce ethos. 

Standardized performance benchmarks – Aligns expectations across teams and levels.

Ensures employee satisfaction – The BARS framework builds a holistic view of performance review sessions, providing definitive and actionable feedback. This enhances employee satisfaction.

BARS provides employees with a clear understanding of the problem areas and encourages them to act on the feedback provided during review meetings. High employee satisfaction indicates that the organization is taking its review sessions seriously driving fruitful outcomes.

Successful Implementation Of Bars: Real-Life Examples

A few conglomerates have successfully implemented and benefited from BARS. Here are a few real-life examples.

IBM Improved Diversity Sourcing And Garnered Improved Manager-Recruiter Relationships

IBM wanted to structure it’s hiring process and fine-tune talent acquisition. So they implemented BARS as part of their talent acquisition function to rate recruiters and hiring managers on the following criteria:

  1. Accuracy of job-analysis.
  2. Communicating with candidates.
  3. Diversity sourcing efforts.

To understand how much efforts were taken by members of their TA team to recruit from different sources, the experts at IBM linked the following behaviours with the respective ratings:

1 (Low) : No diversity efforts beyond general platforms.

3(Mid): Occasionally sources from diverse platforms.

5(High): Regularly reaches out to diverse talent communities and tracks the outcomes.

This exercise not only caused an increase in candidate diversity but also improved recruiter accountability and enhanced hiring manager-recruiter relationships.

Deloitte Enhances Leadership Skills

Deloitte used BARS in its global leadership development programs to assess employee progress for:

  1. Strategic thinking.
  2. Communication.
  3. Emotional Intelligence.

To assess their employees’ progress on strategic thinking, Deloitte implemented BARS and used the following behavioural benchmarks.

1: Focuses only on short-term tasks.

3: Considers medium-term objectives.

5: Align strategies with long-term goals.

By implementing BARS, Deloitte was able to identify potential leaders and extract desired outcomes from their L&D efforts.

Challenges of BARS (And How to Fix Them)

1. Difficult to Implement from Scratch

  • Problem: Developing behavioural anchors requires a deep job analysis, which can be time-consuming.
  • Solution: Start small. Instead of building and implementing a full-fledged framework immediately:
    • Pick 3–5 key competencies (e.g., Collaboration, Problem-Solving, Customer Service).
    • Use team feedback and past reviews to draft realistic behavioural parameters.

2. Not Easily Scalable for Large Teams

  • Problem: Work environments evolve quickly, giving people less time to adapt and scale.
  • Solution: Implement BARS with flexibility:
    • Allow self-assessment and peer feedback to complement manager evaluations.
    • Use AI-driven assessment tools to adapt BARS dynamically.
    • Keep behavioural anchors updated with evolving workplace expectations.

3. Can Miss Broader Aspects of Performance

  • Problem: BARS focuses on specific behaviours, which may ignore growth potential, leadership, and innovation.
  • Solution: Combine BARS with continuous feedback models, such as:
    • 360-degree feedback to assess teamwork and leadership.
    • OKRs (Objectives & Key Results) for goal alignment.
    • Project-based evaluations to capture real-world contributions.

How to Implement BARS in Your Organization

Step 1: Identify Key Competencies

Focus on 3–5 critical skills for your team, such as:

  • Collaboration (Teamwork, Communication, Conflict Resolution)
  • Problem-Solving (Creativity, Critical Thinking, Decision-Making)
  • Critical Thinking (Frequent evaluation of work strategies, experimenting with varying frameworks to drive growth and conducting feedback sessions for better productivity)
  • Customer Service (Responsiveness, Empathy, Effectiveness)
  • Ownership & Initiative (Taking on New Challenges, Leadership)
  • Adaptability (Handling Change, Resilience, Learning Agility)

Step 2: Define Behavioral Anchors

Use team input, past reviews, and industry benchmarks to define a list of specific behaviours based on which performance levels are assessed.

Step 3: Train Managers and Employees

  • Conduct training sessions on how to use BARS effectively.
  • Ensure consistency in evaluations by discussing real-world examples.

Step 4: Integrate with Your Performance Management System

Use HR tech tools, and performance dashboards, and implement AI-powered assessments as the one by HackerEarth to streamline and expedite evaluations.

Step 5: Continuously Improve

  • Collect feedback from managers and employees. Conduct regular feedback sessions to assess the general temperament of your employees and introduce strategies that work for the employees and the overall health of the team.
  • Process behavioural indicators annually to match evolving workplace standards.

How BARS Can Benefit In The Long Run?

One of the highlights of the BARS framework is that it is agile and adaptable. It converts review meetings into insightful sessions where employees are given a platform to understand their shortcomings and work on them, motivating them to understand and align their workplace practices with the organization’s goals. BARS paves the way for a more holistic approach, helping organizations retain talent.

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Author
Nischal V Chadaga
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December 3, 2024
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5 min read
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A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing c

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.​

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.​
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.​

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

Guide to Conducting Successful System Design Interviews in 2025

What is Systems Design?Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.Systems Design, in its...

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

  • Develop an understanding of basics of system design and architecture
  • Familiarize yourself with commonly asked systems design interview questions
  • Read about system design case studies for popular applications
  • Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

  • Plan the extent of the topics and scope of discussion in advance
  • Clearly define the evaluation criteria and communicate expectations
  • Quantify constraints, inputs, boundaries and assumptions
  • Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

  • Ask follow-up questions to challenge a solution
  • Probe candidates to gauge real-time logical reasoning skills
  • Make it a conversation and take notes of important pointers and outcomes
  • Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

  • Encourage candidates to explore and consider alternative solutions
  • Work with the candidate to drill the problem into smaller tasks
  • Provide context and supporting details to help candidates stay on track
  • Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.

How Candidates Use Technology to Cheat in Online Technical Assessments

Impact of Online Assessments in Technical Hiring In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers. The ease and...

Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.
  • Secure, sealed-off testing environment
  • AI-enabled live test monitoring
  • Enterprise-grade, industry leading compliance
  • Built-in features to track, detect and flag cheating attempts
Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.
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