Human Resources
17 columns
200 rows
8 formats

Employee Promotion Eligibility Signals

This dataset provides a detailed view of employee promotion eligibility signals, including performance scores, tenure, training completion, and succession planning status. Designed for HR analytics, it enables organizations to identify high-potential employees, optimize promotion decisions, and support strategic workforce planning.

last updated 5 Sept 2025
by GoMask

The brief that made it

Identifying and prioritizing employees for promotion

Sample rows

preview · 8 of 200 rows · all 17 columns

employee_idstring	promotion_recommendationstring	promotion_readiness_scorefloat	promotion_eligibleboolean	departmentstring	first_namestring	last_namestring	job_titlestring	manager_idstring	hire_datedate	tenure_yearsfloat	last_promotion_datedate	performance_scorefloat	succession_plan_flagboolean	critical_role_flagboolean	training_completedboolean	last_performance_review_datedate
A00001	Recommended	0.98	true	Finance	Emily	Watson	Senior Financial Analyst	A00003	2010-08-15	13.9	2022-07-01	95.3	true	true	true	2024-03-10
B00002	Recommended	0.94	true	Engineering	Carlos	Nguyen	Lead Software Engineer	B00010	2012-03-01	12.3	2023-02-20	92.8	true	true	true	2024-05-15
C00003	Under Review	0.83	true	HR	Monica	Lee	HR Business Partner	C00004	2015-09-20	8.7	2021-06-11	87.1	false	false	true	2024-02-19
D00004	Recommended	0.89	true	Marketing	Michael	Brown	Marketing Strategist	D00018	2018-05-10	6.1	2022-09-30	90.5	false	false	true	2024-04-07
E00005	Under Review	0.79	true	Sales	Liam	Patel	Account Manager	E00040	2019-11-25	4.6	2021-12-15	84.7	false	false	true	2024-01-22
F00006	Under Review	0.75	true	IT	Sophia	Kim	IT Systems Administrator	F00009	2020-02-14	4.1	2023-03-01	79.3	false	false	true	2024-05-19
G00007	Recommended	0.99	true	Legal	Daniel	Hernandez	Corporate Counsel	G00015	2008-07-21	15.9	2021-08-28	97.1	true	true	true	2024-06-03
H00008	Recommended	0.92	true	Operations	Ava	Singh	Operations Supervisor	H00014	2016-04-30	8.1	2022-04-12	93.2	true	true	true	2024-02-04
I00009	Under Review	0.62	true	Procurement	Lucas	Garcia	Procurement Specialist	I00019	2022-01-11	2.4	blank	72.9	false	false	true	2024-05-21
J00010	Recommended	0.86	true	Customer Service	Olivia	Carter	Customer Success Lead	J00016	2017-10-03	6.7	2022-12-10	88.6	false	false	true	2024-04-27
A00011	Not Recommended	0.33	false	Finance	Ethan	Miller	Junior Accountant	A00001	2023-08-12	0.8	blank	68.4	false	false	false	2024-02-10
B00012	Under Review	0.68	true	Engineering	Grace	Turner	Software Engineer	B00002	2021-04-23	2.1	blank	77.5	false	false	true	2024-05-19
C00013	Under Review	0.74	true	HR	Benjamin	Reed	Recruiter	C00003	2019-07-10	4.9	blank	81.6	false	false	true	2024-03-15
D00014	Not Recommended	0.38	false	Marketing	Jack	Evans	Marketing Coordinator	D00004	2022-04-02	2.2	blank	66.7	false	false	false	2024-04-22
E00015	Under Review	0.57	true	Sales	Zoe	Hill	Sales Associate	E00005	2023-01-15	1.4	blank	70.9	false	false	true	2024-04-26
F00016	Under Review	0.66	true	IT	Henry	Moore	Help Desk Specialist	F00006	2020-11-08	3.6	blank	73.4	false	false	true	2024-02-18
G00017	Not Recommended	0.41	false	Legal	Natalie	Ramirez	Paralegal	G00007	2022-08-19	1.8	blank	65.2	false	false	false	2024-03-12
H00018	Under Review	0.65	true	Operations	Chloe	Baker	Operations Analyst	H00008	2021-10-22	2.6	blank	74.1	false	false	true	2024-05-09
I00019	Under Review	0.77	true	Procurement	Ryan	Gonzalez	Procurement Coordinator	I00009	2018-09-15	5.7	2020-08-19	82.3	false	false	true	2024-04-10
J00020	Not Recommended	0.19	false	Customer Service	Ella	Murphy	Customer Service Rep	J00010	2023-12-01	0.4	blank	59.5	false	false	false	blank

What the 200 rows show

from the 200-row sample

Not Recommended (promotion recommendation) stands out: mean promotion_readiness_score is 0.42, against 0.81 for the rest.

72%promotion_eligible = true
0.80median promotion_readiness_score
5.0median tenure_years
84.3median performance_score

Mean promotion_readiness_score by promotion_recommendation200 rows

promotion_readiness_score200 rows, in bands of 0.1

Median 0.80, from 0.19 to 1.0.

department200 rows · top 10 of 13 values

Finance20
Engineering20
Marketing20
Sales20
IT20
Legal20
Operations20
Customer Service20
HR10
Procurement10

17 columns by typefrom the column list below

string 7
float 3
date 3
boolean 4

Columns

17 columns in four groups

blueprint · 17 columns
column	type	description	example
Text 7 columns
`employee_id`	string	Unique identifier for each employeeunique	A00001
`first_name`	string	Employee's first name	Emily
`last_name`	string	Employee's last name	Watson
`department`	string	Department where the employee works	Finance
`job_title`	string	Current job title of the employee	Senior Financial Analyst
`manager_id`	string	Unique identifier of the employee's direct manageroptional	A00003
`promotion_recommendation`	string	Recommendation status for promotion (e.g., 'Recommended', 'Not Recommended', 'Under Review')Recommended · Not Recommended · Under Review · Pending · optional	Recommended
Numbers 3 columns
`tenure_years`	float	Number of years the employee has been with the company0 or more	13.9
`performance_score`	float	Latest performance evaluation score (0-100)0 to 100	95.3
`promotion_readiness_score`	float	Composite score reflecting readiness for promotion (0-1 scale)0 to 1 · optional	0.98
Dates and times 3 columns
`hire_date`	date	Date when the employee was hired	2010-08-15
`last_promotion_date`	date	Date of the employee's most recent promotionoptional	2022-07-01
`last_performance_review_date`	date	Date of the most recent performance reviewoptional	2024-03-10
True or false 4 columns
`promotion_eligible`	boolean	Indicates if the employee is currently eligible for promotion	true
`succession_plan_flag`	boolean	Indicates if the employee is included in a succession planoptional	true
`critical_role_flag`	boolean	Indicates if the employee holds a critical role in the organizationoptional	true
`training_completed`	boolean	Indicates if the employee has completed all required training for promotionoptional	true

Use it for

A human resources dashboard
The promotion_eligible rate, promotion_readiness_score by promotion_recommendation and a breakdown of department. Excel, Power BI or Tableau.
Why do the 42 Not Recommended rows have a mean promotion_readiness_score of 0.42?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Employees200
A000010.98Recommen…
B000020.94Recommen…
A000110.33Not Reco…
A software demo
Believable employees with first_name, last_name and department to fill a screen in front of a buyer.

This dataset200 rows17 columns

Yours1,000 rows17 columns

blueprint · employee-promotion-eligibility-signals

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 17 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

Log performance ratings and review dates
Include tenure and training completion
Flag eligible and ineligible candidates
Exclude employee identifiers
Group by department

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: employee-promotion-eligibility-signals

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A human resources dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Human Resources

What should your data show?