Weekly Aggregates
Weekly Aggregates Data
Filename
organizationName_ANONYMIZED_AGGREGATES_YYYYMMDDZ.extension
Variables:
organizationName: the slugified name of the organization
YYYYMMDD, the week this file contains data from. Week is in ISO format, meaning that Monday is considered the first day of the week.
extension, depending on the format and compression, see below:
Available formats
| Format | Compression | Extension |
|---|---|---|
NONE,GZIP | .csv[.gz] | |
NONE,GZIP | .json[.gz] | |
NONE,DEFLATE,SNAPPY | .avro | |
NONE,SNAPPY,GZIP,ZSTD | .parquet[.gz] |
File contents
This file contains data that Worklytics has preprocessed and aggregated at the week level. Depending on the metric in question, data is either inferred from connected customer data sources or calculated by Worklytics.
Sample row
NDJSON example (note examples are pretty printed for documentation purposes otherwise will be presented in one row each)
Weekly aggregates export schema
| Field | Type | Description |
|---|---|---|
employeeId | STRING | Pseudonymized ID of the employee whose work is summarized in the aggregate (ID may be un-pseudonymized for non-proxy users) |
week | DATE | ISOWEEK when that work occurred |
key | STRING | Metric name (see "Weekly aggregate definitions" below for details) |
value | FLOAT | Metric value |
Methodology notes
Key concepts
Metric Availability
Note that not all metrics in the table below will necessarily appear in your company’s export, as some require specific data connectors (e.g., if your company has not connected GitHub, you will not see any of the github: metrics). The list of metrics may change as aggregates are added over time.
Default Values & After-Hours Metrics
The default work week is Monday to Friday, and the default work day is 9:00 to 17:00. Unless you have made changes to the defaults for your company, after-hours metrics are calculated based on these values, combined with employee calendar data to take time zone into account (e.g., an email received at 19:00 local time is considered to be after-hours; a meeting on Saturday is considered weekend work).
Exclusive Time
Worklytics algorithmically estimates the time spent on each work activity to make apples-to-apples comparisons possible across tools, a process which can be relevant for measurement of tools like slack and email that don't automatically have an associated hourly cost like meetings do. For example, an instance of someone sending 10 rapid-fire slack messages might be estimated to take 2 minutes of time based on default values used for slack bounded by any activities that are happening before and after each message is sent.
Exclusive time calculations underlie metrics like focus time (used broadly) and can be seen directly in metrics following the TOOL:minutes:week format (typically used only for a few specific modeling use cases).
Meeting Time
For meetings specifically, Worklytics provides several layers of insight:
Meeting count: reports on the total number of meetings
Direct time: sum of all meeting hours, regardless of when they occur
Exclusive meeting time: de-dupes overlapping meetings from direct time
Exclusive time: subtracts time spent on other events that happen during meetings from meeting time
For example, consider a person who accepts the calendar invite for a team all-hands (10 people) from 10-11am on Tuesday and a 1:1 (2 people) at the same time and then sends slack messages for 5 total minutes of time during the 10-11am hour.
Meeting count: this person attended 2 meetings
Direct time: this person attended 2 hours of meetings
Exclusive meeting time: this person was in meetings for a total of 1 hour (because the meetings overlap fully)
Exclusive time: this person spent 55 minutes of time exclusively on meetings (because 5 mins of meeting time was actually spent on slack)
In most cases, we recommend measuring "Meeting count" or "Exclusive meeting time," though there are instances where "Exclusive time" makes more sense.
Focus Time
Worklytics has created a set of metrics intended to measure the amount of time in the day available for deep, focused work. In theory, the whole span of one’s workday could be used for this purpose, but in reality, this rarely is the case. Meetings, slack, and email can each break up blocks that could have been used for deep work — and this distraction is measurable.
This metric has several variations:
worklytics:hours:in:focus:blocks– daily time in blocks of 2+ hours free from meetings. Useful in determining whether meetings are disrupting deep work.worklytics:hours:in:focus:blocks:v2– daily time in blocks of 2+ hours free from meetings, slack, and email. Useful in investigating a wider set of possible disruptions to deep work.worklytics:hours:in:focus:blocks:v3:prep– daily time in blocks of 30+ minutes free from meetings, slack, and email. Useful as an analysis refinement for groups like sales and customer success that consider meetings a core work activity but still likely need some time to prepare for calls during the day.worklytics:hours:in:focus:blocks:v3:focus– daily time in blocks of 1+ hour free from meetings, slack, and email. Useful as an analysis refinement for groups like people managers and senior leaders that need to push forward larger projects despite a typically heavy meeting load.worklytics:hours:in:focus:blocks:v3:flow– daily time in blocks of 2+ hours free from meetings, slack, and email. Our current best metric for use in investigating a wider set of possible disruptions to deep work. This version is similar to v2, except with several algorithm refinements.
Zoom attendance
Note that Worklytics only considers call attendance for users who are logged in to Zoom. If individuals are not required to be logged in to join internal Zoom calls (by organizational policy), and they join any calls without logging in to Zoom, their attendance in these calls will not be attributed to them in Worklytics' data. Check with your organization's Zoom administrator to ensure that all users are required to log in to Zoom for internal calls.
In order to prevent outliers from skewing the data, Zoom calls longer than 7h are capped at 7h. Typically, these are the result of rare cases where calls are left open for an extended period of time.
Frequently asked questions
Q: What do the dates mean?
A: Worklytics data is grouped by week. We consider weeks in ISO format, so weeks start on Monday and comprise Monday to the following Sunday (inclusive).
Q: What is a GROUP_TYPE in the context of this document?
GROUP_TYPE is any of: cost center, business segment, business unit, cost center, department, level, other affiliations, region, territory, role or the special maingroup, which is equivalent to the primary group type chosen by the customer.
Q: What does CUSTOM_GROUP_X mean in the context of this document?
Custom groups represent any additional HR data fields provided by your company outside of the standard fields (e.g., department, level, role, etc.). These will vary by organization.
Q: What does cv12wk mean in the context of this document?
Values with the suffix "cv12wk" are the "coefficient of variation" for the underlying variable over the trailing 12 weeks. Coefficient of variation is the standard deviation of the variable divided by its mean. We use the coefficient of variation because, unlike standard deviation, it does not depend on the unit of the variable. Eg, you can sensibly compare cv12wk for a variable measured in minutes with one measured in hours. We colloquially describe this as "volatility" because the greater the typical change in the underlying variable from week-to-week, the higher this number will be. So if one variable has cv12wk of 1, and the other has cv12wk of 2, the other can be thought of as "twice as volatile".
Q: How are meeting time values expressed?
A: Meeting time is expressed as hours in decimal format (e.g. a value of 1.25 equates to 1 h 15 min). You can multiply by 60 to get the amount of time in minutes.
Q: Which version of focus time should I use?
A: In most cases, v3:flow, as this takes interruptions from meetings, email, and chat into account and reflects our most up-to-date methodologies (v3:flow is based on a 2-hour block).
Q: What is a collaborator? A strong collaborator?
A: A collaborator is anyone you’ve interacted with through email, slack, meetings, or other collaboration tools in a given week. A strong collaborator is the subset of these people with whom you’ve spent 2+ hours that week.
Q: Are there thresholds in place for what is considered “collaboration?” Are meetings above the threshold completely removed from the data set?
A: Unless your company has set a different threshold, events larger than 75 are excluded from collaboration-related calculations (e.g., we don't consider someone to have have 10,000 collaborators because they attended an all-hands meeting). However, that very large meeting would still appear as a meeting in the data set, given that it is an event that took up employee time.
Q: What is the difference between inter- and intra-department collaboration?
A: Inter-department meetings include at least one person from another team. Intra-department meetings are single-team. These metrics can be calculated at the team, department, or other level.
Q: Why are collaboration time aggregate values greater than the total time in a given week in some cases?
A: For collaboration time aggregates (E.g., GROUP_TYPE_individual_collaboration_interteam_hours), this can happen because these metrics are a sum of the total time spent collaborating with each individual associated with a particular work item. For instance, spending 1 hour in a meeting with 4 team members will be counted as 4 hours collaborating with your team.
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