The Employee Satisfaction Survey dataset is a comprehensive collection of information regarding employees within a company. It includes essential details such as employee identification numbers, self-reported satisfaction levels, performance evaluations, project involvement, work hours, tenure with the company, work accidents, promotions received in the last 5 years, departmental affiliations, and salary levels. This dataset offers valuable insights into the factors influencing employee satisfaction and can be used to analyze and understand various aspects of the workplace environment.

This dataset of 289,870 people sampled across TikTok, X, and Reddit reveals statistics of employee engagement in 2024 to find out whether employees consider themselves engaged, why they were engaged, what would make them more engaged, and to learn more about their demographics.

This dataset comes from the Biennial City of Tempe Employee Survey questions related to employee engagement. Survey respondents are asked to rate their level of agreement on a scale of 5 to 1, where 5 means "Strongly Agree" and 1 means "Strongly Disagree".This dataset includes responses to the following statements: Overall, I am satisfied with the level of employee engagement in my Department. I have been mentored at work. Overall, how satisfied are you with your current job? Participation in the survey is voluntary and confidential.This page provides data for the Employee Engagement performance measure. The performance measure dashboard is available at 2.13 Employee Engagement.Additional Information Source: Community Attitude Survey Contact:  Wydale Holmes Contact E-Mail:  wydale_holmes@tempe.govData Source Type:  ExcelPreparation Method:  Data received from vendor (Community Survey)Publish Frequency:  AnnualPublish Method:  ManualData Dictionary

Job Satisfaction: What Is It? Job Satisfaction Statistics: The term job "job contentment," also known as "employee satisfaction," is used in companies to understand the state of workers' unhappiness or happiness in their jobs. Organizations that want to have the best results can use job satisfaction statistics. They strongly correlate with staff output, retention, and overall happiness in the workplace. In addition, employers who wish to succeed with the best talent at their side need to comprehend the entire scope and importance of employee satisfaction stats. In this article, we will discuss the most important job satisfaction statistics. Job Satisfaction Statistics for 2023 (Editor's Choice) 77% of employees believe their coworkers remained very satisfied with overall job satisfaction. 55% of US workers are expected to search for new jobs within the next 12 months. 36% of employees globally claimed that they are in love with their current job. 75% of workers quit their jobs due to managerial conflicts. Remote work is preferred by 32% of respondents across the world. In the United States, 60% of workers are happy with their jobs in 2023. By the end of 2023, around 61% of American employees will leave their current jobs.

Introduction

Employee Feedback Statistics: Employee feedback forms an integral part of modern workplace management and gives organisations valuable insights into employee satisfaction, engagement, and well-being. Regularly seeking employee feedback helps an organisation improve its environment, uplift morale, and drive productivity.

As we approach 2025, the theme of employee feedback is even more vital than before. Organisations will realise the value of having productive relationships and creating a culture where employees feel supported.

This article examines some crucial employee feedback statistics in 2025, trends, challenges, and the overall implications of such feedback systems for organisations.

This dataset was created to explore the diverse factors impacting employee performance and satisfaction in a typical organization. It spans a variety of fields from personal demographics to performance metrics and job details, offering a comprehensive view into the dynamics of the workplace.

The inspiration behind the creation of this dataset is to provide an accessible resource for those interested in the field of HR analytics. It can be used to derive insights into employee performance, satisfaction, and overall engagement at work. This dataset is particularly useful for tasks such as predicting employee turnover, analyzing employee performance, and understanding the factors that influence job satisfaction.

As of 2023, impactful work was the most important organizational attribute for employees worldwide, with ** percent of respondents choosing that option. Career advancement opportunities and employer ethics and compensation were the other leading elements crucial for ensuring job satisfaction among employees.

The Employee Engagement Index (EEI) assesses the critical conditions conducive for employee engagement (e.g., effective leadership, work which provides meaning to employees). The index is comprised of three subfactors: Leaders Lead, Supervisors, and Intrinsic Work Experience.

Welcome to the 👨‍💼 👩‍💼 💼 Employee Data Analysis 📊 🔍 Database! 👋🏻

Our extensive collection of datasets provides a deep dive into different aspects of employee engagement and organizational dynamics.

Here's what you can expect to discover:

• General Employee Data: Explore essential workforce details such as demographics, job roles and tenure.

• Employee Survey Data: Access firsthand insights from employees through detailed surveys covering various aspects of their workplace experiences, satisfaction levels and engagement.

• Manager Survey Data: Gain valuable perspectives from managers' feedbacks, offering insights into leadership effectiveness and organizational culture.

With access to these datasets, you'll have the chance to analyze, model and discover actionable insights to improve organizational performance, elevate employee satisfaction, predict employee attrition and much more, all to inform strategic decision-making.

Reskilling and upskilling have become increasingly important in the workplace. Many companies have developed strategies to quench the need of continuously training their employees. According to a survey conducted in 2024 among employees in the United States, ** percent of respondents said that they were satisfied or very satisfied with their company's reskilling and upskilling training.

Employee engagement in the world increased from 2011 to 2020, but dropped slightly the next years. It stood at ** percent in 2022 and 2023. It was at its highest in 2020 when it reached ** percent.

This page provides information for the Employee Engagement performance measure.

Global employee engagement increased steadily from 2009 to 2023, but was still at only ** percent. A lack of involvement and enthusiasm of workers at their workplace can cost companies trillions of dollars in lost income.

This dataset contains detailed employee engagement survey responses collected voluntarily from employees of Pierce County Government in Washington State. The survey measures employees’ agreement levels on various workplace statements to assess overall engagement and satisfaction.

Key Features

• Survey Responses: Numeric values ranging from 0 to 4, where 0 means Not Applicable (N/A), 1 = Strongly Disagree, 2 = Disagree, 3 = Agree, and 4 = Strongly Agree. Each response reflects the employee’s sentiment toward a specific engagement question.
• Demographics & Hierarchy: Includes information on the employee’s role, department, and organizational structure with identifiers for director, manager, supervisor, lead, and staff.
• Survey Questions: Detailed statements about workplace environment and employee engagement, allowing deep analysis of opinions.
• Time Frame: Survey data covers responses collected in specific years (column Year).

Recommended Analyses

• Identify which questions employees most strongly agree or disagree with.
• Explore trends and differences in responses by department, role, or managerial hierarchy.
• Provide insights for management to improve employee satisfaction and engagement.

Source

The dataset was provided by Pierce County, WA. Licensed under Public Domain.

Employee Engagement Enterprise Performance Indicator Data

The 10,000 Worlds Employee Dataset is a comprehensive dataset designed for analyzing workforce trends, employee performance, and organizational dynamics within a large-scale company setting. This dataset contains information on 10,000 employees, spanning various departments, roles, and experience levels. It is ideal for research in human resource analytics, machine learning applications in employee retention, performance prediction, and diversity analysis.

Key Features of the Dataset: Employee Demographics:

Age, gender, ethnicity Education level, degree specialization Years of experience Employment Details:

Department (e.g., HR, Engineering, Marketing) Job title and seniority level Employment type (full-time, part-time, contract) Performance & Productivity Metrics:

Annual performance ratings Work hours, overtime details Training programs attended Compensation & Benefits:

Salary, bonuses, stock options Benefits (healthcare, pension plans, remote work options) Employee Engagement & Retention:

Job satisfaction scores Attrition and turnover rates Promotion history and career growth Workplace Environment Factors:

Team collaboration metrics Employee feedback and survey results Work-life balance indicators Use Cases: HR Analytics: Identifying patterns in employee satisfaction, retention, and performance. Predictive Modeling: Forecasting attrition risks and promotion likelihoods. Diversity & Inclusion Analysis: Understanding representation across departments. Compensation Benchmarking: Comparing salaries and benefits within and across industries. This dataset is highly valuable for data scientists, HR professionals, and business analysts looking to gain insights into workforce dynamics and improve organizational strategies.

Would you like any additional details or a sample schema for the dataset?

This dataset contains raw, unprocessed data files pertaining to the management tool group focused on 'Talent & Employee Engagement', including concepts like Employee Engagement Surveys/Systems and Corporate Codes of Ethics. The data originates from five distinct sources, each reflecting different facets of the tool's prominence and usage over time. Files preserve the original metrics and temporal granularity before any comparative normalization or harmonization. Data Sources & File Details: Google Trends File (Prefix: GT_): Metric: Relative Search Interest (RSI) Index (0-100 scale). Keywords Used: "corporate code of ethics" + "employee engagement" + "employee engagement management" Time Period: January 2004 - January 2025 (Native Monthly Resolution). Scope: Global Web Search, broad categorization. Extraction Date: Data extracted January 2025. Notes: Index relative to peak interest within the period for these terms. Reflects public/professional search interest trends. Based on probabilistic sampling. Source URL: Google Trends Query Google Books Ngram Viewer File (Prefix: GB_): Metric: Annual Relative Frequency (% of total n-grams in the corpus). Keywords Used: Corporate Code of Ethics+Employee Engagement Programs+Employee Engagement Surveys+Employee Engagement Time Period: 1950 - 2022 (Annual Resolution). Corpus: English. Parameters: Case Insensitive OFF, Smoothing 0. Extraction Date: Data extracted January 2025. Notes: Reflects term usage frequency in Google's digitized book corpus. Subject to corpus limitations (English bias, coverage). Source URL: Ngram Viewer Query Crossref.org File (Prefix: CR_): Metric: Absolute count of publications per month matching keywords. Keywords Used: ("corporate code of ethics" OR "employee engagement" OR "employee engagement programs" OR "employee engagement surveys") AND ("human resources" OR "management" OR "organizational" OR "culture" OR "development" OR "performance") Time Period: 1950 - 2025 (Queried for monthly counts based on publication date metadata). Search Fields: Title, Abstract. Extraction Date: Data extracted January 2025. Notes: Reflects volume of relevant academic publications indexed by Crossref. Deduplicated using DOIs; records without DOIs omitted. Source URL: Crossref Search Query Bain & Co. Survey - Usability File (Prefix: BU_): Metric: Original Percentage (%) of executives reporting tool usage. Tool Names/Years Included: Corporate Code of Ethics (2002); Employee Engagement Surveys (2012, 2014); Employee Engagement Systems (2017, 2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 2003, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 2002/708; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Bain & Co. Survey - Satisfaction File (Prefix: BS_): Metric: Original Average Satisfaction Score (Scale 0-5). Tool Names/Years Included: Corporate Code of Ethics (2002); Employee Engagement Surveys (2012, 2014); Employee Engagement Systems (2017, 2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 2003, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 2002/708; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Reflects subjective executive perception of utility. File Naming Convention: Files generally follow the pattern: PREFIX_Tool.csv, where the PREFIX indicates the data source: GT_: Google Trends GB_: Google Books Ngram CR_: Crossref.org (Count Data for this Raw Dataset) BU_: Bain & Company Survey (Usability) BS_: Bain & Company Survey (Satisfaction) The essential identification comes from the PREFIX and the Tool Name segment. This dataset resides within the 'Management Tool Source Data (Raw Extracts)' Dataverse.

Employee engagement data from an employee survey conducted by Pierce County and completed voluntarily by employees. Numeric responses correspond with the following answers: 0=N/A, 1=Strongly Disagree, 2=Disagree, 3=Agree, 4=Strongly Agree.

The 2020 Public Service Employee Survey (PSES) was administered by Advanis, on behalf of the Office of the Chief Human Resources Officer, Treasury Board of Canada. This comprehensive survey measured federal government employees’ opinions about their engagement, leadership, workforce, workplace, workplace well-being, compensation, diversity and inclusion, and the impacts of COVID-19. The 2020 Public Service Employee Survey was conducted from November 30, 2020 to January 29, 2021. A total of 188,786 employees in 87 federal departments and agencies responded to the 2020 Public Service Employee Survey, for a response rate of 61%. The 2020 Public Service Employee Survey datasets contain the results of the survey by year (2020, 2019 and 2018) for the Public Service and departments/agencies, and the results broken down by demographic characteristics (e.g., age, gender) and organizational units. Results for 2019 and 2018 are only provided for questions repeated in the 2020 Public Service Employee Survey.

Worldwide, employee satisfaction increases with company size, numbers from Glassdoor show. While employees working at companies with between *** and ** employees had average satisfaction levels of ***, they were *** point higher among employees working at companies with more than 10,000 employees.