Rating Scales for Employee Performance Reviews

July 23, 2019
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Rating scales are very common in employee reviews and performance checkins. They help us quantitatively measure employee performance. 

The benefits of employee rating questions are that they allow for simpler comparisons between employees and they can speed up the appraisal process. Faster appraisals can allow organizations to solicit feedback from more people in one review.

The downside of performance rating scales is that a lot of nuance is lost in a simple three, five or seven point scale. It can be hard to boil down all of a person’s strengths and weaknesses to one number. 

The other common issue with rating scales is that they are poorly constructed. This post is designed to help you create the scales for your performance management process. We also provide a ton of examples to borrow from at the bottom.

 

We built PerformYard to streamline and automate any organization's unique performance management strategy.

 

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Choosing the Right Rating Scales

There is literally a science to rating scales. Social scientists have been using questionnaires to collect real scientific data for many decades.

That means we don’t need to reinvent the wheel here, we should learn from our scientific colleagues.

Nominal vs Binary vs Ordinal Data

Stay with me, we should have a quick understanding of the types of data we’re collecting before diving deeper into rating scales. There are three types of data that are most often collected on employee appraisal forms - Nominal, Binary and Ordinal. Here is what they mean…

Nominal = Categories

Example: “Which of our six company values does this employee most live-up-to?”

When the answer options have no relationship to each other, in other words they aren’t ordered, or have any numeric relationship, you are asking a question that will generate nominal data. These are not technically rating scale questions, but are commonly found on review forms.

Binary = Yes or No (either or)

Example: “Is this employee ready for promotion?”

Binary data is always either or. The most common example being yes or no. Other examples are exists or doesn’t exist, is or is not, complete or incomplete. Deloitte collects binary data in 2 of the 4 questions on their review form. Google collects binary data on their upward reviews of managers.

Ordinal = Ordered List

Example: “Rate the employee for the following statements using a five point scale from Strongly Agree to Strongly Disagree”

Ordinal data is collected when we ask rating scale questions. The answers to a question will be a list of possibilities that have a clear order or ranking. As you move up the scale, options should clearly be better/more and as you move down the scale, the options are worse/less.

Numeric vs Descriptive Answers

There are two common ways to present rating scale answers, Numeric and Descriptiv. Here is what they mean…

Numeric - Just numbers (like 1-5)

Example: “Score the employee’s leadership ability between 1 and 5.” 

Numeric scales rightfully get a lot of pushback. It can be really hard for managers to understand what constitutes a 4 verse a 5 when it comes to subjective competencies like “assertiveness.” 

Descriptive - Ordered descriptions

Example: Everything from Agree to Disagree all the way to Behaviorally Anchored Rating Scales.

Descriptive rating scales include descriptions of what each step up on the scale looks like. This could be as simple as different levels of agreement or it could be as complex as a set of specific actions an employee should have taken to achieve each level.

Most Common Rating Scales - Likert vs Semantic vs Custom

Likert Scales

Likert scales are the most common scales and one we’ve all seen before. This scale measures our response to a statement, with the most common being…

Strongly Disagree - Disagree - Neither Agree nor Disagree - Agree - Strongly Agree. 

Well designed likert scales will be symmetrical, with an equal number of positive and negative responses. They will also be balanced with what feels like the same distance between each choice. 

Five choices is the most common, but any number is possible. One of the most important decisions to make is whether to give an odd or even number. An odd number of choices will mean the central option is neutral, neither positive or negative. An even number of options is sometimes called a “forced choice” does not give a neutral option and so the respondent has to pick a side.

Semantic Scales

Semantic scales are similar to likert scales but present just two extremes with unnamed options in between. For example you might ask an employee to rate a recent project between success and failure with 7 options in between.

Custom Scales

This is one of the most common choices on performance rating forms. We find that HR teams like to create their own scales to fit their needs. This is a bold move that could lead to unexpected distortions in your data. But! If you’re up for it we’ve provided many real life rating scale examples below.

Examples of Rating Scales in Action

UC Berkeley

The University of California, Berkeley human resources department currently conducts performance appraisals with a 5-level rating scale, ranging from Exceptional to Unsatisfactory. Supervisors that assign a Level 2 (Improvement Needed) or Level 1 (Unsatisfactory) rating to an employee must complete a Performance Improvement Plan for said employee. This plan is developed to improve or correct poor performance, containing timelines that are outlined and monitored to measure the employee’s progress. A Level 5 (Exceptional) rating is said to be achievable, but given fairly infrequently. High-performing employees often receive a Level 4 (Exceeds Expectations) or Level 3 (Meets Expectations) rating.

Huntington Ingalls

This company uses a rating system that is both numerical and alphabetical, focused on whether or not employees meet company goals. Their 5-point scale assigns abbreviations that coincide with each numerical ranking: 5 = FE (Far Exceeds), 4 = EX (Exceeds Expectations), 3 = ME (Meets Expectations), 2 = DR (Development Required), and 1 = IR (Improvement Required).

Harvard

Harvard makes use of multiple rating scales within their organization, including overall performance ratings of employees, goals, competencies, and direct report ratings. Overall performance ratings are given on a 5-point scale, observing employees with performances that are leading (5), strong (4), solid (3), building (2), and not meeting expectations (1).

Goals are also tracked using a 3-point rating scale that measures whether a goal or project was on time, on budget, and accomplished. A 3 ranking implies that a goal was met, a 2 ranking is given to partially met goals, and a 1 ranking is assigned to an unfinished goal where most or all dimensions were not achieved.

Competencies ratings are given to employees who demonstrate thorough to lacking knowledge of the organization’s core competencies. This 4-point scale ranges from Advanced, to Proficient, to Developing, and lastly, Does Not Demonstrate.

Direct report ratings are reserved for managers only, and determine whether the ratee’s capabilities are Highly Effective (3), Effective (2), or Needs Improvement (1).

Emory University

Emory University’s HR team operates an in-depth rating system that is similar to BARS. Each employee is rated against a long list of unique core competencies that the organization abides by. This checklist includes building trust, collaboration, communication, delivering results, problem solving, taking initiative, functional knowledge and skills, and service to others/customer focus.

Each of these categories deals with how well an employee displays honesty, respect, listening and sharing, productivity, decision making, and reasoning. The competencies are rated with a 3-point system ranging from Exceeds Expectations, Meets Expectations, and Unacceptable. All ratings apply to supervisors and managers, as well as non-managers.

More Examples

Unsatisfactory | Needs Improvement | Meets Expectations | Exceeds Expectations | Distinguished

Needs Improvement | Meets Expectations

Does Not Meet | Meets | Exceeds

Below Level | At Level | Above Level

Needs Attention | Satisfactory

Unacceptable | Needs Improvement | Acceptable | Good | Excellent

Did not meet expectations | Met some but not all expectations | Fully met expectations | Exceeded expectations | Significantly exceeded expectations

Area of Deficiency | Inconsistently Meets Standards | Meets Standards | Meets High Standards | Regularly Exceeds High Standards

Needs Improvement | Consistently Meets Expectations | Exceeds Expectations | Strongly Exceeds Expectations | Superb 

Unsatisfactory | Meets Most | Fully Meets and Sometimes Exceeds | Consistently Exceeds | Far Exceeds 

Never | Sometimes | Often | Always

Not Often Enough | From Time to Time | Most of the Time

Minor Contribution | Important Contribution | Critical Contribution

Low Performer | Developing Performer | Highly Valued Performer | Top Performer

Unacceptable Performance | Partially Successful | Fully Successful | Superior | Distinguished Performance

Poor | Below Average | Good | Very Good | Outstanding

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