UX Department Performance Indicators

Performance indicators for the UX department at GitLab

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Executive Summary

KPI	Health	Status
UX Team Member Retention	Unknown	Need to update the Tableau dashboard for UX-specific metrics.
UX Average Age of Open Positions	Attention	Consistently higher than the target. Making adjustments in our approach in FY25.
Total open UX bug issues by severity	Problem	UX bugs are introduced to the product faster than they are burned down and S3/S4 issues are not prioritized.
Average research projects per Product Designer	Attention	Below target for most of FY24.
Product Design MR review volume	Unknown	FY25-Q2 is the first full quarter we will track this indicator per Product Designer. Target is based on previous historical data by total volume per momth.
Technical Writer MR Rate	Attention	This target rate remains somewhat aspirational.

Key Performance Indicators

UX Team Member Retention

We need to be able to retain talented team members. Retention measures our ability to keep them sticking around at GitLab. Team Member Retention = (1-(Number of Team Members leaving GitLab/Average of the 12 month Total Team Member Headcount)) x 100. GitLab measures team member retention over a rolling 12 month period.

Target: at or above 84% This KPI cannot be public Unknown

Need to update the Tableau dashboard for UX-specific metrics.

UX Average Age of Open Positions

Measures the average time job openings take from open to close. This metric includes sourcing time of candidates compared to Time to Hire or Time to Offer Accept which only measures the time from when a candidate applies to when they accept.

Target: at or below 50 days Health:Attention

Consistently higher than the target. Making adjustments in our approach in FY25.

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Total open UX bug issues by severity

The purpose of this chart is to show the total volume of existing UX bug issues that impact our SUS score. We are tracking against the label “bug::ux.”

Target: 0 S1/S2 issues behind the SLA due date; reduction in total volume over time Health:Problem

UX bugs are introduced to the product faster than they are burned down and S3/S4 issues are not prioritized.

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Average research projects per Product Designer

Our goal is to use customer research to validate problems and solutions to ensure we are building the right things in the right way. We use many research methods, including interviews, surveys, usability studies, findability/navigation studies, and analytics. Hypothesis that there is a connection between this KPI and SUS KPI.

Target: At or greater than 2 validation issues per Product Designer per quarter Health:Attention

Below target for most of FY24.

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Product Design MR review volume

Our goal is to provide UX reviews for Merge Requests (MRs) that involve user-facing changes, including those impacting screen readers, to help improve the quality of our product and reduce the amount of Deferred UX. Product Designers follow our MR Review guidelines to conduct these reviews.

Target: At or greater than 7 MR Reviews per Product Designer per month. Unknown

FY25-Q2 is the first full quarter we will track this indicator per Product Designer. Target is based on previous historical data by total volume per momth.

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Technical Writer MR Rate

This PI tracks the number of MRs merged every month using the Technical Writing and UI text labels across all GitLab projects where the team works. Team performance has understandably changed throughout the years of this PI, based on changes to team organization and role requirements. May was a major release month. We are currently onboarding new team members. We continue to watch this metric.

Target: 55 MRs per technical writer per month Health:Attention

This target rate remains somewhat aspirational.

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Regular Performance Indicators

UX Department MR Rate

UX Department MR Rate is a performance indicator showing how many changes the UX team implements directly in the GitLab product. We currently count all members of the UX Department (Directors, Managers, ICs) in the denominator, because this is a team effort. The full definition of MR Rate is linked in the url section.

Target: Greater than TBD MRs per month Health:Attention

We don’t yet know what a good MR rate looks like for UX. Need accurate data to determine.
UX MR rate doesn’t accurately reflect all MRs to which UX contributes, because we often collaborate on MRs rather than opening them ouselves.

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URL(s):

UX Department Promotion Rate

The total number of promotions over a rolling 12 month period divided by the month end headcount. The target promotion rate is 12% of the population. This metric definition is taken from the People Success Team Member Promotion Rate PI.

Target: 12% Health:Okay

Metric is new and is being monitored

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UX Department Discretionary Bonus Rate

The number of discretionary bonuses given divided by the total number of team members, in a given period as defined. This metric definition is taken from the People Success Discretionary Bonuses KPI.

Target: at or above 10% Health:Attention

Metric is new and is being monitored

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System Usability Scale (SUS) score

The System Usability Scale (SUS) is an industry-standard survey that measures overall system usability based on 10 questions. Moving a SUS score upward even a couple of points on a large system is a significant change. The goal of this KPI is to understand how usability of the GitLab product rates against industry standards and then track trends over time. Even though UX will be responsible for this metric, they will need other departments such as PM and Development to positively affect change. See our grading scale for details on interpreting scores. SUS data is collected every other quarter.

Target: 73 by Q4-FY24, 77 by Q4-FY25, 82 by Q4-FY26 Health:Problem

Perceived usability rates as a C+. Overall, we have seen a declining trend in SUS with periods of stabilization.
FY22-Q1 focused on performance and visibility of system status.
FY22-Q2 focused on Merge Request improvements.
FY22-Q3 included 104 Pajamas migrations.
FY22-Q4 included 209 Pajamas migrations.
FY23-Q1 included 331 Pajamas migrations and burn down of 9 S1 SUS-Impacting issues.

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User Satisfaction (USAT) score

The User Satisfaction (USAT) is an industry-standard survey that measures user satisfaction based on a single question (How satisfied are you with GitLab (the product)?). The goal of this KPI is to understand how user satisfaction of the GitLab product rates against industry standards and then track trends over time. Even though UX will be responsible for this metric, they will need other departments such as PM and Development to positively affect change. USAT data is collected every quarter.

Target: 76% of survey respondents are Satisfied or Very Satisfied with GitLab (the product) Health:Okay

The USAT metric is new (as of Q2 FY25) and is being monitored to track performance over time

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Actionable insights

Actionable insights originate from user research. They always have the ‘Actionable Insight’ label applied to the resulting issue and a clear follow up that needs to take place as a result of the research observation or data. An actionable insight both defines the insight and clearly calls out the next step as a recommendation. The goal of this KPI is to ensure we’re documenting research insights that are actionable and tracking their closure rate.

Target: TBD Health:Okay

Q3 FY21 was spent establishing a baseline. Now that there’s ample data available, we’ll take two steps. Step 1 - investigate the oldest open actionable insights to understand why they have not been closed. Step 2 - track the average time for actionable insights to be closed.

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Usability benchmarking overall score by stage

This PI tracks the overall stage score for usability benchmarking studies performed across stage groups as they change over time. The tasks and workflows that comprise each benchmarking study are derived from JTBD for one or more target personas typical for the stage running the study. The overall score for each study takes into account the performance of each task that was tested, through metrics like completion rate, severity, and customer effort score (CES). The scale is 0-100, where 90-100 is ‘Great’, 80-89 is ‘Good’, 70-79 is ‘Fair’, 69 and below is ‘Poor’.

Target: 5% increase in overall score from previous benchmarking, maintaining an overall score above 84/100. Unknown

Not enough data. Only one benchmarking study has been performed so far.

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Experience baselines

This PI tracks the percent of supported groups that have determined their baseline experience scores using formative evaluation UX Scorecards of a main JTBD.

Target: 100% of supported groups have determined their experience baseline. Unknown

In FY25-Q1, we created a main JTBD for at least one category in each supported group.
Pending Tableau update.

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Experience baseline scores

This PI tracks the experience baseline scores of each group.

Target: 100% of supported groups have an experience baseline score of B or higher. Unknown

We first need to generate scores for all groups in order to understand which areas we need to prioritize to meet the goal of a B or greater.
Pending Tableau update.

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Deferred UX

Deferred UX means that for a given issue, we failed to meet defined standards for our Design system or for usability and feature viability standards as defined in agreed-upon design assets. When we fail to ship something according to defined standards, we track the resulting issues with a “Deferred UX” label. Even though UX will be responsible for this metric, they will need other departments such as PM and Development to positively affect change.

Target: Below 50 open “deferred UX” issues Health:Problem

Total amount of Deferred UX has increased in the last several months and is well above the target.
We are actively working with PMs to prioritize Deferred UX. Some stage groups are committing to resolving a minimum number of Deferred UX issues per milestone (generally, a commitment of no less than one issue). We will track this effort and make adjustments as we see the results.
The Deferred UX label has been inconsistently applied likely due to it deviating from the industry standard term. We are exploring alternatives to track Deferred UX in FY25 to increase accuracy.

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Open Deferred UX Age

Age of outstanding Deferred UX issues. Deferred UX means that for a given issue, we failed to meet defined standards. Age represented via median of days opened.

Target: At or below 150 days Health:Attention

Average days to close a “Deferred UX” issue is beginning to trend upward.
We will monitor to see if the trend continues.

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UX bug issues opened/closed each month

With SUS as a KPI, it’s important to ensure that we are closing UX bugs issues at an appropriate velocity. UX is responsible for ensuring that issues are opened when appropriate and advocating for their prioritization, while Product Management is the ultimate DRI for prioritization. We are tracking against the label “bug::ux.”

Target: TBD Unknown

We will be revising this PI in FY25 to give focus to a smaller number of labels.
Pending Tableau update.

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Pajamas component migrations

Integrating Pajamas components into GitLab contributes to a cohesive and consistent user experience, visually and functionally. This allows users to seemlessly transition throughout different stages of the DevOps lifecycle. With our adoption scanner, we are able to track percent adoption of existing Pajamas components per stage group. This PI does not yet track usage of components within the product that exist outside of Pajamas.

Target: 100% of groups are “On track” Health:Attention

81% of groups are “On track”
17% of groups “Need attention”
2% of groups are “At risk”

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Technical Writing collaboration on UI text

Historically, Technical Writers were not consistently included in the creation of UI text. Since UI text is critical to product usability, Technical Writing involvement can help improve the quality of our UI. This chart includes issues and MRs with the Technical Writing and UI text labels, because Technical Writing contributions happen in both places.

Target: TBD Unknown

We are watching this metric to determine a target, because historical data is inconsistent.

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Product Designer Gearing Ratio

Number of Product designers against the targeted gearing ratio

Target: At 72 product designers Health:Problem

At 47% of targeted gearing ratio, when including UX Engineers.
Some product groups have multiple designers and engineers supporting.
Chart no longer updated.

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Technical Writer Gearing Ratio

Number of Technical Writers against the targeted gearing ratio

Target: At 19 technical writers Health:Attention

At 63% of targeted gearing ratio

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UX Researcher Gearing Ratio

Number of researchers against the targeted gearing ratio

Target: At 11 researchers Health:Attention

At 72% of targeted gearing ratio

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Legends

Health

Value	Level	Meaning
3	Okay	The KPI is at an acceptable level compared to the threshold
2	Attention	This is a blip, or we’re going to watch it, or we just need to enact a proven intervention
1	Problem	We'll prioritize our efforts here
-1	Confidential	Metric & metric health are confidential
0	Unknown	Unknown

How pages like this work

Data

The heart of pages like this are Performance Indicators data files which are YAML files. Each - denotes a dictionary of values for a new (K)PI. The current elements (or data properties) are:

Property	Type	Description
`name`	Required	String value of the name of the (K)PI. For Product PIs, product hierarchy should be separate from name by " - " (Ex. {Stage Name}:{Group Name} - {PI Type} - {PI Name}
`base_path`	Required	Relative path to the performance indicator page that this (K)PI should live on
`definition`	Required	refer to Parts of a KPI
`parent`	Optional	should be used when a (K)PI is a subset of another PI. For example, we might care about Hiring vs Plan at the company level. The child would be the division and department levels, which would have the parent flag.
`target`	Required	The target or cap for the (K)PI. Please use `Unknown until we reach maturity level 2` if this is not yet defined. For GMAU, the target should be quarterly.
`org`	Required	the organizational grouping (Ex: Engineering Function or Development Department). For Product Sections, ensure you have the word section (Ex : Dev Section)
`section`	Optional	the product section (Ex: dev) as defined in sections.yml
`stage`	Optional	the product stage (Ex: release) as defined in stages.yml
`group`	Optional	the product group (Ex: progressive_delivery) as defined in stages.yml
`category`	Optional	the product group (Ex: feature_flags) as defined in categories.yml
`is_key`	Required	boolean value (true/false) that indicates if it is a (key) performance indicator
`health`	Required	indicates the (K)PI health and reasons as nested attributes. This should be updated monthly before Key Reviews by the DRI.
`health.level`	Optional	indicates a value between 0 and 3 (inclusive) to represent the health of the (K)PI. This should be updated monthly before Key Reviews by the DRI.
`health.reasons`	Optional	indicates the reasons behind the health level. This should be updated monthly before Key Reviews by the DRI. Should be an array (indented lines starting with dashes) even if you only have one reason.
`urls`	Optional	list of urls associated with the (K)PI. Should be an array (indented lines starting with dashes) even if you only have one url
`funnel`	Optional	indicates there is a handbook link for a description of the funnel for this PI. Should be a URL
`public`	Optional	boolean flag that can be set to `false` where a (K)PI does not meet the public guidelines.
`pi_type`	Optional	indicates the Product PI type (Ex: AMAU, GMAU, SMAU, Group PPI)
`product_analytics_type`	Optional	indicates if the metric is available on SaaS, SM (self-managed), or Both.
`is_primary`	Optional	boolean flag that indicates if this is the Primary PI for the Product Group.
`implementation`	Optional	indicates the implementation status and reasons as nested attributes. This should be updated monthly before Key Reviews by the DRI.
`implementation.status`	Optional	indicates the Implementation Status status. This should be updated monthly before Key Reviews by the DRI.
`implementation.reasons`	Optional	indicates the reasons behind the implementation status. This should be updated monthly before Key Reviews by the DRI. Should be an array (indented lines starting with dashes) even if you only have one reason.
`lessons`	Optional	indicates lessons learned from a K(PI) as a nested attribute. This should be updated monthly before Key Reviews by the DRI.
`lessons.learned`	Optional	`learned` is an attribute that can be nested under `lessons`and indicates lessons learned from a K(PI). This should be updated monthly before Key Reviews by the DRI. Should be an array (indented lines starting with dashes) even if you only have one lesson learned
`monthly_focus`	Optional	indicates monthly focus goals from a K(PI) as a nested attribute. This should be updated monthly before Key Reviews by the DRI.
`monthly_focus.goals`	Optional	indicates monthly focus goals from a K(PI). This should be updated monthly before Key Reviews by the DRI. Should be an array (indented lines starting with dashes) even if you only have one goal
`metric_name`	Optional	indicates the name of the metric in Self-Managed implemenation. The SaaS representation of the Self-Managed implementation should use the same name.

// want to edit? Go here –> https://gitlab.com/-/ide/project/gitlab-com/www-gitlab-com/edit/master/-/data/performance_indicators/ux_department.yml

System Usability Scale

The System Usability Scale (SUS) is a performance indicator we use to measure the long term usability of our product.

User Satisfaction (USAT) Survey

The User Satisfaction (USAT) survey is a performance indicator we use within the Product division to measure the end user satisfaction of our product.

Last modified May 15, 2024: Add note about Tableau sign-in (17ce7671)

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