Turnover data by fiscal year for the City of Tempe compared to the seven market cities, which include Chandler, Gilbert, Glendale, Mesa, Phoenix, Peoria, and Scottsdale. There are two totals, one with and one without retirees.Please note that the Valley Benchmark Cities’ annual average is unavailable for FY 2020/2021 due to a gap in data collection during that year. Please note that corrections were made to the data, including historic data, due to additional review and research on the data on 10/2/2024.This page provides data for the Employee Turnover performance measure.The performance measure dashboard is available at 5.07 Employee Turnover.Data DictionaryAdditional InformationSource: Department ReportsContact: Lawrence La VictoireContact E-Mail: lawrence_lavictoire@tempe.govData Source Type: ExcelPreparation Method: Extracted from PeopleSoft, and requested data from other cities is entered manually into a spreadsheet, and calculations are conducted to determine the percent of turnover per fiscal yearPublish Frequency: AnnuallyPublish Method: Manual

Portobello Tech is an app innovator that has devised an intelligent way of predicting employee turnover within the company. It periodically evaluates employees' work details including the number of projects they worked upon, average monthly working hours, time spent in the company, promotions in the last 5 years, and salary level. Data from prior evaluations show the employee’s satisfaction at the workplace. The data could be used to identify patterns in work style and their interest to continue to work in the company. The HR Department owns the data and uses it to predict employee turnover. Employee turnover refers to the total number of workers who leave a company over a certain time period.

This table provides information on turnover developments. Turnover development is represented as the percentage of businesses which have generated a higher, the same or a lower turnover than in the same period one year previously. The figures are subdivided in sectors/branches according to the Standard Industrial Classification of all Economic Activities 2008 (SIC 2008) and in size classes based on the number of persons employed. Data available from: 2012. Status of the figures: Figures from the fourth quarter of 2021 are provisional, the others are final. Changes as of September 13, 2023: Figures of the second quarter 2023 have been added. When will new figures be published? New results are made available sixty calendar days after the period under review (quarter). After publication of the definite results, Statistics Netherlands will only make adjustments if major changes occur.

This dataset contains resources that present State of Oklahoma workforce data through the current fiscal year. The data can be used for workforce planning purposes.

Portugal - Turnover in services was -0.20 % year-on-year in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Portugal - Turnover in services - last updated from the EUROSTAT on August of 2025. Historically, Portugal - Turnover in services reached a record high of 31.60 % year-on-year in June of 2021 and a record low of -30.90 % year-on-year in June of 2020.

Hungary - Turnover in services was -5.20 % year-on-year in September of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Hungary - Turnover in services - last updated from the EUROSTAT on September of 2025. Historically, Hungary - Turnover in services reached a record high of 28.30 % year-on-year in June of 2022 and a record low of -10.60 % year-on-year in June of 2020.

Estimates of root turnover rates were calculated from measurements of live root standing crop and belowground net primary production (BNPP) compiled from the primary literature. Vegetation characteristics, soil properties, and climate conditions were associated with turnover rates to examine patterns and controls for biomes worldwide. Building on prior analyses (Jackson et al. 1996, 1997), data were compiled from approximately 190 papers from additional journals, book chapters, technical reports, and unpublished manuscripts that included information on live root standing crop and belowground BNPP. The papers described research on every continent except Antarctica, although the majority were from North America. In the database, the plant functional type and biome coverage were most abundant for grasslands and temperate zones.

We present a dataset created from merged secondary sources of ExecuComp and CompuStat and then augmented with manual data collection through searches of news stories related to CEO turnover.

We start dataset construction with the ExecuComp executive-level data for the period from 1992 through 2020. These data are merged with the CompuStat dataset of financial variables. As the dataset is intended for research on CEO turnover, we exclude observations in which the CEO at the start of the fiscal year is not well-defined; these are cases when there were co-CEOs and cases when the CEO was shared across different firms. The data set also excludes firm/year combinations that involve a restructuring of the firm – spinoff, buyout, merger, or bankruptcy.

We identify the CEO at the start of each year for each firm. This also helps identify the last year an individual served as CEO. In order to identify CEO turnover based on changes in the CEO from year to year, we require firm observations to extend over at least six contiguous years for the firm to remain in the sample. Cases involving the last year the firm is in the sample are excluded. We also exclude from the dataset cases when there was an interim CEO who stayed in the position for less than 2 years. This results in a sample of 3,100 firms reflecting 41,773 firm/year combinations.

For this sample, we examine news articles related to CEO turnover to confirm the reasons for each CEO departure case. We use the ProQuest full-text news database and search for the company name, the executive name, and the departure year. We identify news articles mentioning the turnover case and then classify the explanation of each CEO departure case into one of five categories of turnover. These categories represent CEOs who resigned, were fired, retired, left due to illness or death, and those who left the position but stayed with the firm in a change of duties, respectively.

The published data file does not include proprietary data from ExecuComp and CompuStat such as executive names and firm financial data. These data fields may be merged with the current data file using the provided ExecuComp and CompuStat identifiers.

The dataset consists of a single table containing the following fields: • gvkey – unique identifier for the firms retrieved from CompuStat database • firmid – unique firm identifier to distinguish distinct contiguous time periods created by breaks in a firm’s presence in the dataset • coname – company name as listed in the CompuStat database • execid – unique identifier for the executives retrieved from ExecuComp database • year – fiscal year • reason – reason for the eventual departure of the CEO executive from the firm, this field is blank for executives who did not leave the firm during the sample period • ceo_departure – dummy variable that equals 1 if the executive left the firm in the fiscal year, and 0 otherwise

Spain - Turnover in services was -0.80 % year-on-year in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Spain - Turnover in services - last updated from the EUROSTAT on September of 2025. Historically, Spain - Turnover in services reached a record high of 40.20 % year-on-year in June of 2021 and a record low of -33.40 % year-on-year in June of 2020.

United States Turnover: Daily Avg: CBOT: Financial Futures: US Treasury Notes: 5 Y data was reported at 827,590.000 Contract in Jun 2018. This records a decrease from the previous number of 1,657,021.230 Contract for May 2018. United States Turnover: Daily Avg: CBOT: Financial Futures: US Treasury Notes: 5 Y data is updated monthly, averaging 549,766.500 Contract from Jan 2001 (Median) to Jun 2018, with 210 observations. The data reached an all-time high of 1,862,559.630 Contract in Feb 2018 and a record low of 81,050.000 Contract in Jul 2001. United States Turnover: Daily Avg: CBOT: Financial Futures: US Treasury Notes: 5 Y data remains active status in CEIC and is reported by CME Group. The data is categorized under Global Database’s USA – Table US.Z021: CBOT: Futures: Turnover.

MB "12 data" financial data: profit, annual turnover, paid taxes, sales revenue, equity, assets (long-term and short-term), profitability indicators.

Greece - Turnover in services was -0.10 % year-on-year in September of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Greece - Turnover in services - last updated from the EUROSTAT on September of 2025. Historically, Greece - Turnover in services reached a record high of 34.70 % year-on-year in June of 2021 and a record low of -30.40 % year-on-year in June of 2020.

Monthly Business Survey services industries' total turnover in current price and non-seasonally adjusted, UK.

MB "Ex data" financial data: profit, annual turnover, paid taxes, sales revenue, equity, assets (long-term and short-term), profitability indicators.

UAB Linked Data financial data: profit, annual turnover, paid taxes, sales revenue, equity, assets (long-term and short-term), profitability indicators.

Stock market turnover ratio (%) in Hungary was reported at 40.41 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. Hungary - Stock market turnover ratio - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Stock market turnover ratio (%) in Ireland was reported at 29.13 % in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ireland - Stock market turnover ratio - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

JOLTS: Separation Rates: LD: sa: NF: PR: EH: Health & Social Assis data was reported at 0.600 % in Nov 2018. This stayed constant from the previous number of 0.600 % for Oct 2018. JOLTS: Separation Rates: LD: sa: NF: PR: EH: Health & Social Assis data is updated monthly, averaging 0.700 % from Jan 2008 (Median) to Nov 2018, with 131 observations. The data reached an all-time high of 1.100 % in Jul 2010 and a record low of 0.500 % in Aug 2018. JOLTS: Separation Rates: LD: sa: NF: PR: EH: Health & Social Assis data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G054: Job Openings and Labor Turnover Survey: Separation Rate.

Brazil Formal Employment: Turnover Rate: Metropolitan: São Paulo data was reported at 4.390 % in Apr 2019. This records an increase from the previous number of 4.150 % for Mar 2019. Brazil Formal Employment: Turnover Rate: Metropolitan: São Paulo data is updated monthly, averaging 3.630 % from Feb 2003 (Median) to Apr 2019, with 195 observations. The data reached an all-time high of 4.410 % in Mar 2016 and a record low of 2.010 % in Dec 2003. Brazil Formal Employment: Turnover Rate: Metropolitan: São Paulo data remains active status in CEIC and is reported by Ministry of Labor and Social Security. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBB093: Formal Employment: Turnover Rate: by Region and State.

Taiwan Labour Turnover: SP: Services data was reported at 2.990 % in Sep 2018. This records a decrease from the previous number of 3.030 % for Aug 2018. Taiwan Labour Turnover: SP: Services data is updated monthly, averaging 2.450 % from Jan 1980 (Median) to Sep 2018, with 465 observations. The data reached an all-time high of 7.360 % in Aug 1983 and a record low of 1.210 % in Jul 1987. Taiwan Labour Turnover: SP: Services data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G053: Labour Turnover: Separation Rate.