The Compensation Calculator

Introduction

On this page, we explain the different factors that make up our Compensation Calculator and its alignment to GitLab’s values and Compensation Principles.

Use the calculator

We source some of the information the calculator is based upon, including the San Francisco benchmark and location factors, from 3rd party, non-public sources. As a result, the full compensation calculator application itself cannot be made completely public.

Instead, consistent with our value of transparency but in line with our agreements regarding how we use data we have sourced, we provide information regarding the type of data we use to build the calculator and how that information helps us build as complete and accurate of a calculator as possible.

Team members can access the calculator at any time with their GitLab credentials. Applicants will be issued credentials and have access to the calculator during the interview process. The information from the calculator should only be shared with those who have access (GitLab team members and candidates).

You can use the calculator to determine the overall Total Rewards Package Offered by GitLab (Cash + Equity + Benefits). Internal team members can also use the following spreadsheet by making a copy and adding in your specific information to calculate the GitLab Total Rewards annual amount.

Contact Total Rewards

For any questions relating to the compensation calculator, reach out to Total Rewards.

The Compensation Calculator

As a natural extension of the Compensation Principles and our commitment to transparency, sharing, efficiency, directness, and boring solutions (see our values) we developed a Compensation Calculator. The compensation of executives and anyone on a quota is not set with the calculator. We use a Compensation Calculator because it helps us align compensation to our values:

1. Transparency - The calculator is open to GitLab team members and candidates in the pipeline. This means that at the time of hiring, candidates don’t have to blindly negotiate compensation. They simply need to enter the individual inputs on the Compensation Calculator and it comes up with a band consistent with the individual’s circumstance - where they live, level, currency, etc. When team members move across levels, departments and locations during their time at GitLab, they’ll also be able to see the appropriate band for the change.
2. Efficient - There’s no need to have multiple back-and-forth conversations between team members, managers, recruiters and the Total Rewards team. For hiring managers and recruiters, they simply use the Compensation Calculator for the roles they’re hiring for rather than having multiple approval levels and conversations. Similar with promotions and any other changes with locations, benchmarks, levels, team members and managers can discuss compensation according to the inputs on the Compensation Calculator rather than having negotiations.
3. Diversity, Inclusion & Belonging - People with the same attributes should earn the same. The Compensation Calculator reduces unconscious bias or giving higher pay to individuals who can negotiate better. The Compensation Calculator allows us to take a data-driven approach to compensation where there’s fairness across all teams, levels and countries.
4. Collaboration - Allows for team members to review the Compensation Calculator and have the Total Rewards team iterate based on the data and feedback we get from the team.
5. Iteration - The Compensation Calculator gets reviewed when feedback is received and all inputs are reviewed during the Annual Compensation Review.
6. Results - The Compensation Calculator helps us focus on our outputs rather than spending unnecessary time talking about and negotiating money. It shifts conversations and focus from ‘I want X money’ to looking at the training and mentorship necessary for our team members to increase within the range based on performance.

Goals of the Compensation Calculator

The goals of the calculator are:

1. Calculate compensation for 200+ regions all over the world.
2. Based on a simple formula.
3. People with the same attributes should earn the same.
4. The adjustment for paying local rates should be the same if you are in the same location.
5. You should be able to calculate your compensation in case you know or made an assumption about your level.
6. That it is as close to a competitive rate as possible given the other constraints.
7. Be able to calculate compensation for most of our offers without involving a compensation specialist.

The Compensation Calculator Formula

Your compensation = SF benchmark x Location Factor x Level Factor x Exchange Rate

The calculator will output the amount as base + variable = total target cash (TTC)

Your options can be found on stock options and benefits can be found on relevant entity specific benefits pages.

The compensation calculator is updated in December and June with the proper exchange rate, keeping compensation levels in line with local purchasing power.

Disclaimer

The compensation calculator is a tool to assist the Total Rewards team in determining a compensation package for new and existing team members. The results of the calculator are not binding. Written correspondence through a contract or job change letter specify all official compensation changes. We reserve the right to change the calculator at any point in time.

Reporting a Discrepancy

As with all things at GitLab, the compensation calculator is a constant work in progress. There are a few options for reporting a discrepancy if you find the calculator isn’t outputting data that is true to market.

If you are an internal GitLab team member or external to GitLab:

• Create an issue utilizing the issue templates.
  • Requesting a review of a new location factor.
  • Requesting a review of an existing location factor.
  • Requesting a review of a benchmark.
• Email total-rewards@domain for more personal inquiries.

If you prefer to remain anonymous:

• You can use the Reporting a Compensation Discrepancy Form.
  • Providing an email is optional, but we will only reach out directly with any updates if an email is provided.

Rounding Best Practice

Previously, our compensation calculator and processes (percentage changes from compensation review, relocations, currency fluctuations, etc.) produced numbers that were exact, sometimes down to the dollar and cents. To make the numbers more digestible, we are implementing a practice to round up compensation in the local currency to the nearest hundreds. This rounding practice applies to future compensation changes from July 2020 onwards.

SF Benchmark

Introduction

SF benchmark is the team member compensation at a compa ratio of 1.0 at or above market for the role in San Francisco, which we determine using various sources of survey data: Radford, Comptryx.

Benchmark Evaluation

Benchmark Types

Benchmarks are determined based on the following types: Individual Contributor (IC), Manager, Director, Senior Director. The Total Rewards team will add an entry for each type listed within the job family. For example:

  ic_ttc:
    compensation: 100000
    percentage_variable: 0
    from_base: true
  manager_ttc:
    compensation: 140000
    percentage_variable: 0
    from_base: true
  director_ttc:
    compensation: 180000
    percentage_variable: 0.15
    from_base: true
  senior_director_ttc:
    compensation: 220000
    percentage_variable: 0.15
    from_base: true

Note: Where there is no variable component offered (ICs and Managers) GitLab runs the benchmark evaluation off of base salary only. Where there is a variable component offered, GitLab runs the benchmark evaluation off of Total Target Case (TTC).

Benchmark Evaluation for Existing Roles

Benchmarks are evaluated annually as part of the Annual Compensation Review process. Benchmarks can also be adjusted as needed throughout the year.

To analyze benchmarks:

1. Use the job code as the unique identifier to match all data.
2. Outline whether the role is Base or TTC (Total Target Cash) to pull data accordingly.
3. Add in the Radford and Comptryx Job Code.
4. Generate a formula to look up the proper survey data from both Radford and Comptryx at the 50th and 75th percentile.
5. Propose an updated benchmark taking the maximum of the 50th percentile median or the current benchmark.
6. Evaluate the percent change.
7. Generate a merge request to update the benchmark in the relevant data file and assign to the executive of the group for approval.
8. Evaluate any impact to the current team if this benchmark change is done outside of annual compensation review.

New Benchmark

Whenever a new role is established, a new benchmark must also be determined. The Total Rewards team is pinged on the merge request for a compensation review to start the process. The Total Rewards team should ensure that the request is not for a role that already exists and has a benchmark.

Compensation Benchmarking is the process of using internal job descriptions to match salary survey jobs in order to identify the external survey data for each benchmark positions. Compensation data can fluctuate from very high salary data to very low salary data for roles that have the same or similar job titles. Example would be Field Marketing Manager. A Field Marketing Manager at GitLab or another SaaS or Technology company salary benchmarks would and can be included with Field Marketing Manager for other Non Technology companies, as an example RedBull. Though they have the same “title” the role, scope and salaries for these roles are very different. Based on these variants in comp data we will look at the relevant comp data for each role and use the median for the benchmark.

Each new job family will be assigned a job code and evaluated through the same process as for existing role.

To review the Compensation Benchmark process please refer to the New Roles Creation.

Benchmark Adjustment

As stated in competitive rate we want to recruit and retain people who meet our requirements. If any one, or a combination of, the following statistics is met, a benchmark review can be requested to address any concerns around the benchmark:

• An open role is open for longer than 100 days
• A minimum of 4 qualified candidates reject an offer extended by GitLab, or withdraw from the hiring process, due to a reason of compensation for an open requisition
  • Non qualified candidates who do not move forward in the hiring process, would not count towards this minimum as this would not be a reason of compensation, but more about competency or other qualifying reasons. We would still want to collect this data as an input for a compensation analysis on candidate expectations.
• The Recruitment Declines and Withdrawals template is compiled with at least 10 rows of significant/qualified candidate data, including equity information.
  • It is important to ensure when we discuss compensation we have an idea of the candidate’s expectations of total rewards which is inclusive of cash and equity for compensation.
• A voluntary departure rate of 12% or more by current GitLab team members in any given department due to the reason of compensation.
• Evidence of leading indicators of increased compensation, for example:
  • Increased recruiter reachouts to a specific department or role.
  • Government policy announcements related to a specific business sector.
  • Engagement Survey Results.

Timing of requests for benchmark adjustments:

Requests to review a benchmark adjustment can be requested between Feb 1 and Oct 1 of the fiscal year, with the latest effective date of the potential benchmark update being Nov 1. There will not be any benchmark adjustment reviews in Q4 due to the timing of the annual review of benchmarks in Q4.

Summary of the process:

Once data has been collected, the Total Rewards team will review the compensation expectations. During this review, we will look at survey data and candidate expectations (specifically declines due to compensation) to recommend an adjustment to our SF benchmark and target percentile for the role. Total Rewards will coordinate with FP&A and the department leader to draft a business case to be presented to the e-group leader. The business case would include:

• A google sheet with market data, candidate expectations, and impact to the current team.
• A google doc outlining the problem statement, what the department has already tried, and an overall proposal which clarifies the budgetary impact.

Please see the following for a full summary of the benchmark review process:

1. The recruitment team member should compile significant data in the Recruitment Declines and Withdrawals Template for a specific job and conclude that a benchmark review is needed due to recruiting challenges related to compensation reasons/expectations. Significant data is defined as 10 rows of qualified candidates.
2. The recruitment team member should discuss challenges and concerns with the hiring team and/or manager and agree that a benchmark review is necessary.
3. The hiring manager/team should include the PBP and Department Head (Director/VP), and other People Group team members as appropriate, in a discussion to obtain initial approval by Department Head for benchmark review to ensure a willingness to make budget trade offs if a benchmark review results in a recommendation for a higher adjustment.
4. After receiving Department Head approval, the hiring manager should send an email to the Total Rewards team (total-rewards@gitlab.com) and copy the PBP, with the Recruitment Declines and Withdrawals file, along with the business case, confirmation of Department Head approval, and proposal or expectations of adjustment.
5. The Total Rewards team will review the email and perform an analysis of the benchmark in question if it is agreed that a review is warranted. If it is not warranted, the Total Rewards team will go back to the hiring manager and PBP to discuss further.
6. The Total Rewards team will summarize and review the results of the benchmark review with the hiring manager and PBP, and propose a recommendation and next steps for the benchmark adjustment, including reaching out to Finance for budgetary impact.
7. The Hiring Manager should discuss the results to the Department Head, ensuring approval to move forward with the final recommendation.
8. Once the Department Head has approved, the FP&A team will review and approve and discuss any tradeoffs needed for the department.
9. The Department Head would escalate the business case for approval to the e-group Leader after approval from the Total Rewards and FP&A team.
10. After approval from the e-group Leader, the Department Head and PBP review and prepare adjustments and communications.
11. The Total Rewards team will update the Compensation Calculator and all other appropriate documentation
12. If applicable, team members are notified of a pay adjustment and related information.

Job Codes

To automate the process of pulling survey data from Comptryx and Radford to review benchmarks, GitLab has mapped each job title with a corresponding job code. As a first iteration GitLab will use the job codes Radford has outlined. Each job family and level must have a unique job code. The following structure is used:

• Radford Code to be used as job code.
• If there is a duplicate Radford code, the job code in Workday will have a letter behind to differentiate (A, B, C, etc).
• If there is no job code, GitLab will generate a four digit unique job code starting with “N”.

For example: Backend Engineer = 5163 Senior Backend Engineer = 5164 Distribution Engineer = 5163A Senior Distribution Engineer = 5164A

All current job codes can be found by the Total Rewards team in the “Job Codes” google sheet on the Final Job Code Tab.

Location factor

Introduction

Location Factor is calculated using multiple data sources to conduct a market analysis of compensation rates globally: Economic Research Institute (ERI), Comptryx, Radford. This is not a cost of living analysis, but instead a cost of labor market evaluation compared to San Francisco. The Total Rewards team will use their best judgement in determining the input per location based on our Compensation Principles.

Geographical Areas

The location factor depends on your geographical area. To determine geographical areas as it relates to compensation, we looked at what the United Nations outlines globally:

• Americas/LATAM:
  • US: Central
  • US: Mid Atlantic
  • US: South Atlantic
  • US: Mountain
  • US: New England
  • US: Pacific
  • Canada
  • Central America
  • South America
  • Caribbean
• EMEA:
  • Eastern Europe
  • United Kingdom
  • Northern Europe
  • Southern Europe
  • Western Europe
  • Middle Africa
  • Northern Africa
  • Eastern Africa
  • Southern Africa
  • Western Africa
• APAC:
  • Central Asia
  • Eastern Asia
  • Northwestern Asia
  • South-eastern Asia
  • Southern Asia
  • Southwestern Asia
  • New Zealand
  • Australia

To determine your area:

1. Select the country you live in. This filters out all areas outside of your country.

2. Select your Province or State (if applicable).

3. Select your Metro Area if you live within a commutable one hour and forty-five minutes of a city listed.

   If you are within a commutable one hour and forty-five minutes of more than one city, use the city with the shortest commute as your location. If not, select “Not Applicable.”

   If there are no additional boxes for State/Province and/or Metro Area for the country you select, this country has the same location factor regardless of the city you live in. Similarly, if there is no additional box for Metro Area after selecting a State/Province, this state or province has the same location factor regardless of the city you live in.

4. If your country is not listed, reach out to total-rewards@domain to gather relevant data.

5. When you move, you have to inform People Ops and Total Rewards, per the Relocation process and your compensation may be adjusted up or down. Refer to Total Rewards team or the Compensation Calculator to see what the likely impact will be.

If the location of a metropolitan area is higher than the regional minimum, the metropolitan area’s location factor is used for the calculation.

Calculating Location Factors

GitLab will gather and analyze the data for each location factor annually as part of annual compensation review. We will also iterate on location factors as needed throughout the year.

1. Data Gathering
   • ERI: Review the Cost of Labor Market Analysis of each Geo Area to San Francisco at the 100,000, 150,000, and 200,000 salary rate. Take the average of all three data points.
   • Comptryx: Pull a report from Comptryx with all job families in SF as well as each location available in Comptryx to evaluate the differential.
   • Radford: Pull a report from Radford with all job families in SF as well as each location available in Radford to evaluate the differential.
   • In reviewing the data set, determine if a new geo area needs to be added to the list.
2. Data Analysis
   • For geographical areas:
     • Take the average of all non-metro data to determine the location factor for the geographical area. If insufficient non-metro data is available, use all available data and deflate for metros.
   • For metro areas, take the maximum of:
     • the average of all data sources rounded up to the nearest 0.05 OR
     • the current location factor or geographic area (so as to not reduce location factors).
     • If the location factor for the metro area is higher than for the geographical area, pull this out as its own location factor.
     • Analyze the output based on geo areas to adjust location factors where needed. Add a comment with the rationale for the adjustment.
   • Reasons why the formula may be adjusted:
     • Not enough number of data points for the output to be statistically relevant
     • Adjusted to align with other metros in geo
   • When analyzing: Focus on where we are having troubles talent acquisition, retaining, or have a smaller population of team members as these can be indicators of a misalignment in the region.

Level Factor

Level Factor is currently defined as:

• Junior: 0.8 x ic_ttc
• Intermediate: 1.0 x ic_ttc
• Senior: 1.2 x ic_ttc
• Staff/Manager: 1.0 x manager_ttc
• Senior Manager: 1.2 x manager_ttc
• Director: 1.0 x director_ttc
• Senior Director: 1.0 x seniordirector_ttc

The nomenclature can be adjusted for each job family to ensure the appropriate level to select is clear.

GitLab Job Grades

GitLab job grades aid in mapping a role for internal equity with respect to cash and equity. For example, if there is a stock option update, this mapping can act as a reference to update the compensation calculator for the various roles to ensure alignment. Job Grades can also provide an alternative path to finding the current number of options offered without having to fill out the compensation calculator.

Job Grades

Note: This table excludes Enterprise Sales, Commercial Sales, Channel Sales, and Sales Development. Grading can be seen in the table below.

Dual career tracks can be added to each job family (regardless of division) when supported by data. Each individual contributor level above senior (grade 7) will have links to market examples of that level in the relevant section of the job family.

Sales/Sales Development

Customer Success

Compa Ratio

Compa Ratio is a term used internally in the Total Rewards team to evaluate Pay Equality.

The Compa Ratio where within the range spread a team member falls in the calculator. Specifically, the GitLab compensation calculator has a 40% spread (+/- 20% from the median). It is common to see range spreads up to 50%.

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