Hybrid Work Compliance Tracker
This dataset provides detailed tracking of employee adherence to hybrid work schedules, including scheduled and actual remote/in-office days, policy violations, and compliance scores. It enables HR and operations teams to monitor compliance, optimize workforce distribution, and support digital transformation initiatives in hybrid work environments. The dataset is ideal for compliance reporting, productivity analysis, and strategic workforce planning.
Sample rows
preview · 8 of 120 rows · all 19 columns| employee_idstring | work_modestring | scheduled_remote_days_per_weekinteger | policy_violationboolean | manager_idstring | employee_namestring | departmentstring | scheduled_in_office_days_per_weekinteger | actual_in_office_days_per_weekinteger | actual_remote_days_per_weekinteger | violation_typestring | violation_countinteger | reporting_period_startdate | reporting_period_enddate | location_citystring | location_statestring | location_countrystring | compliance_scorefloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| E1001 | hybrid | 3 | true | E1012 | Sophia Chen | Engineering | 3 | 2 | 4 | exceeded_remote_days | 1 | 2024-05-01 | 2024-05-31 | San Francisco | CA | USA | 0.67 | Employee worked one extra remote day than scheduled. |
| E1002 | in-office | 0 | false | E1005 | Aditya Kumar | Finance | 5 | 5 | 0 | none | 0 | 2024-05-06 | 2024-05-31 | Mumbai | Maharashtra | India | 1 | Perfect in-office attendance throughout reporting period. |
| E1003 | remote | 6 | false | E1021 | Lucas Svensson | Engineering | 0 | 0 | 6 | none | 0 | 2024-05-01 | 2024-05-31 | Stockholm | Stockholm | Sweden | 1 | Fully remote employee; no schedule deviations. |
| E1004 | in-office | 0 | true | blank | Isabella Silva | Sales | 7 | 6 | 1 | missed_in_office_days | 1 | 2024-05-01 | 2024-05-07 | Sao Paulo | SP | Brazil | 0.86 | Missed one scheduled in-office day due to illness. |
| E1005 | hybrid | 2 | false | E1029 | Ahmed El-Sayed | Finance | 4 | 4 | 2 | none | 0 | 2024-05-01 | 2024-05-31 | Cairo | Cairo | Egypt | 1 | Employee followed hybrid schedule exactly. |
| E1006 | remote | 5 | true | E1009 | Maria Garcia | Marketing | 0 | 0 | 6 | exceeded_remote_days | 1 | 2024-05-15 | 2024-05-31 | Barcelona | Catalonia | Spain | 0.8 | Worked an extra remote day to meet project deadline. |
| E1007 | hybrid | 3 | false | blank | Chloe Dubois | Legal | 2 | 2 | 3 | none | 0 | 2024-04-01 | 2024-04-30 | Paris | Ile-de-France | France | 1 | Employee adhered to hybrid schedule for the entire month. |
| E1008 | hybrid | 3 | true | E1027 | Kwame Mensah | Human Resources | 3 | 2 | 4 | exceeded_remote_days | 1 | 2024-05-01 | 2024-05-31 | Accra | Greater Accra | Ghana | 0.67 | Remote day exceeded due to regional training event. |
| E1009 | in-office | 0 | false | E1025 | Oliver Evans | Marketing | 6 | 6 | 0 | none | 0 | 2024-05-01 | 2024-05-31 | London | England | UK | 1 | Attended all scheduled in-office days. |
| E1010 | remote | 7 | true | E1007 | Elena Rossi | Legal | 0 | 1 | 6 | other | 1 | 2024-03-01 | 2024-03-31 | Rome | Lazio | Italy | 0.86 | Employee attended office for one day unexpectedly. |
| E1011 | hybrid | 2 | false | blank | Daniel Lee | Engineering | 5 | 5 | 2 | none | 0 | 2024-05-01 | 2024-05-31 | Seattle | WA | USA | 1 | Adhered to hybrid schedule; department head. |
| E1012 | hybrid | 3 | true | E1002 | Zara Patel | Finance | 3 | 2 | 4 | exceeded_remote_days | 1 | 2024-05-08 | 2024-05-15 | Delhi | Delhi | India | 0.67 | Worked one extra remote day during partial month. |
| E1013 | in-office | 0 | false | E1004 | Gabriel Costa | Sales | 7 | 7 | 0 | none | 0 | 2024-05-01 | 2024-05-31 | Rio de Janeiro | RJ | Brazil | 1 | Excellent attendance, no remote work. |
| E1014 | hybrid | 3 | true | E1010 | Katarzyna Nowak | Legal | 2 | 1 | 4 | missed_in_office_days | 1 | 2024-04-08 | 2024-04-14 | Warsaw | Mazovia | Poland | 0.5 | Missed one office day; made up with remote work. |
| E1015 | remote | 7 | false | blank | Jack Thompson | Marketing | 0 | 0 | 7 | none | 0 | 2024-05-01 | 2024-05-31 | Sydney | NSW | Australia | 1 | Fully remote, no deviations. |
| E1016 | hybrid | 3 | true | E1011 | Mei Lin | Engineering | 3 | 2 | 4 | exceeded_remote_days | 1 | 2024-05-01 | 2024-05-31 | Shanghai | Shanghai | China | 0.67 | Exceeded remote days due to public holiday. |
| E1017 | hybrid | 3 | false | E1011 | William Smith | Engineering | 4 | 4 | 3 | none | 0 | 2024-05-01 | 2024-05-31 | Chicago | IL | USA | 1 | No schedule deviations; hybrid model works well. |
| E1018 | hybrid | 4 | false | blank | Fatima Al-Farsi | Finance | 2 | 2 | 4 | none | 0 | 2024-05-01 | 2024-05-31 | Dubai | Dubai | UAE | 1 | Department head; schedule strictly followed. |
| E1019 | remote | 5 | true | E1014 | Anton Baranov | Legal | 0 | 0 | 6 | exceeded_remote_days | 1 | 2024-05-01 | 2024-05-07 | Moscow | Moscow | Russia | 0.8 | Extra remote day logged for urgent legal review. |
| E1020 | in-office | 0 | true | blank | Linda Johansson | Human Resources | 5 | 4 | 1 | missed_in_office_days | 1 | 2024-05-01 | 2024-05-07 | Gothenburg | Vastra Gotaland | Sweden | 0.8 | Missed one office day due to medical appointment. |
What the 120 rows show
from the 120-row sampleRemote (work mode) stands out: mean scheduled_
- 49%policy_
violation = true - 3median scheduled_
remote_ days_ per_ week - 4violation types
- 6departments
- 34location countries
- 3median scheduled_
in_ office_ days_ per_ week
Median 3, from 0 to 7.
- string 10
- integer 5
- float 1
- date 2
- boolean 1
Columns
19 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 10 columns | |||
employee_id | string | Unique identifier for each employeeunique | E1001 |
employee_name | string | Full name of the employee | Sophia Chen |
department | string | Department where the employee works6 departments | Engineering |
manager_id | string | Unique identifier for the employee's manageroptional | E1012 |
work_mode | string | Scheduled work mode for the employee (remote, in-office, hybrid)remote · in-office · hybrid | hybrid |
violation_type | string | Type of policy violation (if any)4 values · optional | exceeded_remote_days |
location_city | string | City of the employee's designated office locationoptional | San Francisco |
location_state | string | State of the employee's designated office locationoptional | CA |
location_country | string | Country of the employee's designated office locationoptional | USA |
notes | string | Additional notes or comments related to the employee's compliance or scheduleoptional | No schedule deviations. |
| Numbers 6 columns | |||
scheduled_in_office_days_per_week | integer | Number of days per week the employee is scheduled to work in the office0 to 7 | 3 |
actual_in_office_days_per_week | integer | Number of days per week the employee actually worked in the office0 to 7 | 2 |
scheduled_remote_days_per_week | integer | Number of days per week the employee is scheduled to work remotely0 to 7 | 3 |
actual_remote_days_per_week | integer | Number of days per week the employee actually worked remotely0 to 7 | 4 |
violation_count | integer | Number of policy violations recorded for the employee in the reporting period0 or more · optional | 1 |
compliance_score | float | Calculated compliance score for the employee during the reporting period (0-1 scale)0 to 1 · optional | 0.67 |
| Dates and times 2 columns | |||
reporting_period_start | date | Start date of the reporting period | 2024-05-01 |
reporting_period_end | date | End date of the reporting period | 2024-05-31 |
| True or false 1 column | |||
policy_violation | boolean | Indicates if the employee violated the hybrid work policy during the reporting period | true |
Use it for
A human resources dashboard
The policy_
violation rate, scheduled_ remote_ days_ per_ week by work_ mode and a breakdown of manager_ id. Excel, Power BI or Tableau. Why do the 23 remote rows have a mean scheduled_
remote_ days_ per_ week of 6.0? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Employees120E10013hybridE10020in-officeE10040in-office
A software demo
Believable employees with employee_
name, department and manager_ id to fill a screen in front of a buyer.
This dataset120 rows19 columns
Yours1,000 rows19 columnslocation_city: UK only
blueprint · hybrid-work-compliance-tracker
Behind this dataset
Same schema. As many rows as you need.
These 120 rows came out of a blueprint — 19 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- Each row represents an individual employee’s weekly schedule compliance status.
- Includes fields for scheduled remote, scheduled onsite, actual remote, and actual onsite days.
- Flags any deviations from approved schedule and records reason codes.
- Calculates percentage of compliance for performance analytics.
- Requires unique employee code and department identifier in each row.
Open the blueprint in Data Factory
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- hybrid-work-compliance-tracker