Explore demographic data on the Massachusetts executive branch workforce. Track our progress toward our goals to reflect the diversity of the people we serve, and to stand out as an employer of choice.

Hub page featuring Sioux Falls Dashboard - Economic Indicators - Employment Data.

Growth data for housing units and employment for the growth areas, urban centers and villages, for the City of Seattle Comprehensive Plan.Housing unit growth is reported quarterly from the city's permitting system while employment change is reported annually from the State of Washington QCEW data.

Socio-economic dashboard depicting Employment and Job Creation. Unemployment Rate (Province, Year, Qtr, Rate [percentage])Unemployment Rate by population group (Province, Year, Population Group, Rate [percentage])Unemployment Rate by gender (Province, Year, gender, Rate [percentage])Youth Unemployment Rate (Province, Year, Age cohorts, Rate [percentage])% Employment in formal and informal sectors (Province, Year, Sectors incl Agriculture, Sectors excl Agriculture, Private Households (domestic work), Rate [percentage])Labour particpation Rate (Province, Year, labour particpation Rate [percentage])Publication Date13 March 2022LineageData is sourced from Stats SA Quarterly Labour Force Surveys. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Six reports exist for this dashboard:Unemployment RateUnemployment Rate by population groupUnemployment Rate by genderYouth Unemployment Rate % Employment in formal and informal sectorsLabour particpation RateData SourceData from Stats SA; Labour force surveys and Quarterly Labour Force Surveys 2017 – 2021Dynamic dashboard reflecting the Outcome Indicator Release - Outcome Indicator: Unemployment rateUnemployment rate by population in WCUnemployment rate by gender in WCYouth unemployment ratePercentage of employed people working in the informal sector, including domestic work in WCLabour participation rate

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

This operations dashboard shows historic and current data related to this performance measure.

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

Employed persons are those who a) did any work at all at a job or business during the reference period, or b) had a job but were not at work due to a variety of personal or medically-related issues.

The Public Service Commission’s (PSC) Staffing Dashboard provides timely and relevant data on staffing activities and trends that will give deputy heads, hiring managers and human resources specialists a broader understanding of staffing within their organizations and the public service as a whole. The Staffing Dashboard is an integral feature of the PSC’s New Direction in Staffing (NDS), which includes the renewed Appointment Policy and delegation instrument, effective as of April 1, 2016. The Staffing Dashboard contains information on organizations subject to the Public Service Employment Act only. The purpose of the Staffing Dashboard is to share data available at the PSC with organizations. It is designed to allow organizations to have a snapshot of their staffing activities and to identify key data trends. It also provides the ability for organizations to compare their data with other organizations, including similar-sized or similarly mandated organizations, or to the public service as a whole The Staffing Dashboard is published on a quarterly basis. Data for a specific quarter may change over the course of the current fiscal year, as data are updated. The notes for each section will provide users with additional details. Please visit the Public Service Commission’s Staffing Dashboard to see the interactive visualisation tool that makes use of the datasets in this collection.

IBM HR Analytics Dashboard Using Excel

🌟 Project Overview This project features a dynamic HR analytics dashboard built using IBM's HR dataset and Excel. The dashboard provides insights into employee demographics, job satisfaction, work-life balance, and turnover rates, enabling data-driven decision-making in human resources management.

✨ Key Highlights

🎛️ Interactive Filters: Explore insights by gender, department, overtime status, job satisfaction, job involvement, and attrition. Dynamic slicers allow for filtering and drilling into specific subsets of data.

📊 Visualizations:

Bar Charts: Gender distribution, monthly income, and business travel patterns by department and job role. Pie Chart: Breakdown of employee job satisfaction levels. Radar Chart: Work-life balance analysis based on marital status. Line Graph: Training time by department.

📌 Top Metrics:

Total Employees: 1,470 (60% Male, 40% Female). Turnover Rate: 16% overall, with insights segmented by gender and department. Job Satisfaction: Visualized on a 4-point scale. Focus Areas: Employee attrition patterns by demographics and job roles. Departmental differences in income, training time, and job satisfaction. Work-life balance analysis based on marital status and job involvement.

🎯 Purpose

The dashboard serves as a tool for HR managers, analysts, and stakeholders to: - Understand key workforce trends. - Identify areas of improvement in job satisfaction and work-life balance. - Analyze factors influencing employee attrition.

💡 Why Excel?

This project demonstrates the power of Excel as a tool for creating interactive dashboards with rich visualizations, making it accessible to HR professionals without advanced technical skills.

💬 Let’s Discuss! I’d love to hear your feedback on this project! Share your thoughts, suggestions, or questions in the comments below. Let’s discuss ways to enhance the dashboard or dive deeper into HR analytics insights! 😊

It is important to identify any barriers in recruitment, hiring, and employee retention practices that might discourage any segment of our population from applying for positions or continuing employment at the City of Tempe. This information will provide better awareness for outreach efforts and other strategies to attract, hire, and retain a diverse workforce.This page provides data for the Employee Vertical Diversity performance measure.The performance measure dashboard is available at 2.20 Employee Vertical Diversity.Additional InformationSource:PeopleSoft HCM, Maricopa County Labor Market Census DataContact: Lawrence LaVictoireContact E-Mail: lawrence_lavicotoire@tempe.govData Source Type: Excel, PDFPreparation Method: PeopleSoft query and PDF are moved to a pre-formatted excel spreadsheet.Publish Frequency: Every six monthsPublish Method: ManualData Dictionary

The data for this report is derived from PeopleSoft Reporting, which includes the following fields, with one row per current active employee: Annual Rate Department ID Ethnic Group Full/Part Time Status Gender Job Title Reg/Temp Status Rehire Date

This operations dashboard shows historic and current data related to this performance measure. The performance measure dashboard is available at 5.02 New Jobs Created. Data Dictionary

Dashboard depicts count of employees by EEO Function for the County of Los Angeles

This dashboard displays longitudinal wage outcomes of Massachusetts students by district, including College and Career Outcomes, Average Annual Earnings by Student Group, and Average Annual Earnings by Industry.

Wage records are obtained from the Massachusetts Department of Unemployment Assistance (DUA) using a secure, anonymized matching process with limitations. For details on the process and suppression rules, please refer to the Employment and Earnings of High School Graduates dashboard itself.

The data in the dashboard is also published across three datasets in the E2C Hub: Average Earnings by Student Group Average Earnings by Industry College and Career Outcomes

Notes to consider when consuming this dataset:
1. Data is for working age adults (ages 18-64) enrolled in Consolidated, P/FDS, Community Living, or Adult Autism Waivers, base funded services, or Supports Coordination services only. 2. Data is a "point in time" as of December 31st of the reported calendar year, unless otherwise noted. 3. Living situations reported are those available in ODP's Employment Dashboard, which vary slightly from the EFOC request. Living situations reported are: 24-hour Residential; Lifesharing; On own or with relative/family; Supported Living; Unknown/other; and Unlicensed residential. 4. Pecenrages were determined using the statewide total number of enrolled individuals for each of the requested categories. 5. Reported numbers of 11 or under are suppressed for confidentiality purposes prior to any public release of the reported data.

This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html

The performance measure dashboard is available at 5.02 New Jobs Created. Data Dictionary

The Virginia Career Works Dashboard is an innovative data visualization tool that makes information about Virginia’s labor market and workforce system more accessible to workers, businesses, and policymakers.