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.

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 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

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.

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.

Of the G20 countries, employees in the ************* had the highest levels of engagement at work in 2023. Meanwhile, employees in ***** felt the lowest levels of workplace engagement. A lack of employee engagement can lead to companies worldwide losing trillions of dollars each year.

This page provides information for the Employee Engagement performance measure.

In 2022, employee engagement across all world regions dropped. Asia Pacific and Sub-Saharan Africa had the highest scores at ** percent, whereas Europe had the lowest at ** percent, with Middle East and North Africa following at ** percent.

Employee Engagement Enterprise Performance Indicator Data

This statistic shows the results of a survey, conducted annually from 2002 to 2012, among American employees regarding their engagement in the workplace. In 2012, 18 percent of respondents stated they were deliberately not engaged in their work, while 30 percent stated they were.

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.

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.

In 2021, almost ** percent of professionals worldwide revealed that employee in their organization are highly engaged in delivering customer experience (CX). During the survey, **** percent of customers rated organizations' CX capability seven out of ten (7/10).

This dataset provides processed and normalized/standardized indices for the management tool group focused on 'Talent & Employee Engagement', including concepts like Employee Engagement Surveys/Systems and Corporate Codes of Ethics. Derived from five distinct raw data sources, these indices are specifically designed for comparative longitudinal analysis, enabling the examination of trends and relationships across different empirical domains (web search, literature, academic publishing, and executive adoption). The data presented here represent transformed versions of the original source data, aimed at achieving metric comparability. Users requiring the unprocessed source data should consult the corresponding Talent/Engagement dataset in the Management Tool Source Data (Raw Extracts) Dataverse. Data Files and Processing Methodologies: Google Trends File (Prefix: GT_): Normalized Relative Search Interest (RSI) Input Data: Native monthly RSI values from Google Trends (Jan 2004 - Jan 2025) for the query "corporate code of ethics" + "employee engagement" + "employee engagement management". Processing: None. Utilizes the original base-100 normalized Google Trends index. Output Metric: Monthly Normalized RSI (Base 100). Frequency: Monthly. Google Books Ngram Viewer File (Prefix: GB_): Normalized Relative Frequency Input Data: Annual relative frequency values from Google Books Ngram Viewer (1950-2022, English corpus, no smoothing) for the query Corporate Code of Ethics+Employee Engagement Programs+Employee Engagement Surveys+Employee Engagement. Processing: Annual relative frequency series normalized (peak year = 100). Output Metric: Annual Normalized Relative Frequency Index (Base 100). Frequency: Annual. Crossref.org File (Prefix: CR_): Normalized Relative Publication Share Index Input Data: Absolute monthly publication counts matching Engagement/Ethics-related keywords [("corporate code of ethics" OR ...) AND (...) - see raw data for full query] in titles/abstracts (1950-2025), alongside total monthly Crossref publications. Deduplicated via DOIs. Processing: Monthly relative share calculated (Engage/Ethics Count / Total Count). Monthly relative share series normalized (peak month's share = 100). Output Metric: Monthly Normalized Relative Publication Share Index (Base 100). Frequency: Monthly. Bain & Co. Survey - Usability File (Prefix: BU_): Normalized Usability Index Input Data: Original usability percentages (%) from Bain surveys for specific years: Corporate Code of Ethics (2002); Employee Engagement Surveys (2012, 2014); Employee Engagement Systems (2017, 2022). Processing: Semantic Grouping: Data points across related names treated as a single conceptual series representing Talent/Engagement focus. Normalization: Combined series normalized relative to its historical peak (Max % = 100). Output Metric: Biennial Estimated Normalized Usability Index (Base 100 relative to historical peak). Frequency: Biennial (Approx.). Bain & Co. Survey - Satisfaction File (Prefix: BS_): Standardized Satisfaction Index Input Data: Original average satisfaction scores (1-5 scale) from Bain surveys for specific years (same names/years as Usability). Processing: Semantic Grouping: Data points treated as a single conceptual series. Standardization (Z-scores): Using Z = (X - 3.0) / 0.891609. Index Scale Transformation: Index = 50 + (Z * 22). Output Metric: Biennial Standardized Satisfaction Index (Center=50, Range?[1,100]). Frequency: Biennial (Approx.). File Naming Convention: Files generally follow the pattern: PREFIX_Tool_Processed.csv or similar, where the PREFIX indicates the data source (GT_, GB_, CR_, BU_, BS_). Consult the parent Dataverse description (Management Tool Comparative Indices) for general context and the methodological disclaimer. For original extraction details (specific keywords, URLs, etc.), refer to the corresponding Talent/Engagement dataset in the Raw Extracts Dataverse. Comprehensive project documentation provides full details on all processing steps.

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.

Structured data on optimal survey frequencies, question counts, and timing recommendations for different types of employee surveys including engagement surveys, pulse surveys, and specialized surveys.

This operations dashboard shows historic and current data related to this performance measure.The performance measure dashboard is available at 2.13 Employee Engagement. Data Dictionary

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.

This page provides data for the Employee Engagement performance measure. The performance measure dashboard is available at 2.13 Employee Engagement.Additional InformationSource: paper and digital survey submissionsContact: Aaron PetersonContact E-Mail: Aaron_Peterson@tempe.govData Source Type: ExcelPreparation Method: NAPublish Frequency: biennial

See "About" for field info. Dataset shows engagement level of city of Las Vegas employees based on questions from annual employee engagement survey.