Workforce Planning Workforce Analytics Tool Kit draft Essential

Workforce Planning Workforce Analytics Tool Kit (draft)

Essential Elements of Strategic Workforce Planning 2

Managing WFP Risk Ø What are your Key Risk indicators § % of attrition by job § % eligible to retire § Ave age of employee § Ave years of service § Ave time to fill critical positions § Ave training lead times § % of empl completing training Ø What are your Business Drivers § Qualified workforce § Process efficiencies § Budget/Financial § Effectiveness use of talent § Organizational performance § Safety objectives § Leadership effectiveness Ø What are your Risk Events § Knowledge deficiencies § Insufficient skill sets § Equipment failures § Unplanned outages § Regulatory oversight Ø What are your Potential Impacts § Financial/Earnings § Safety § Staffing § Customer § Business Performance 3

Workforce Analytics– Assessing Readiness 1. Does the organization have a dashboard or information that focuses on projected attrition by organization and/or critical jobs? 2. Does your organization have a 5 year hiring plan? 3. Are the projected staffing needs instilled in the line organization? Does the line own the data? 4. Has the organization implemented a comprehensive knowledge risk assessment process and is it linked with their workforce planning analytics? 4

Overview of Attrition Model Current Staffing Levels _______ By type or classifications Sources of losses (outflows) Sources of additions (inflows) Employees Out Employees In • Transfers out (Migration out) • Attrition (HR Model) • Terminations • Retirements • Leaves (LTD) • Plan Org Change - Projected Outflows in a year Projected Staffing Level _____ By type or classifications • Transfers in (Migration in) • New Hires • Training Programs (Apprenticeship, Operations, Technicians, Engineering, etc) • Re-Hires + Projected Inflows in a year = Projected Staffing Level 5

WFP Analytics Process HR System Benefits Understand HR data elements and how the data is managed in the HR System. Know the organizations retirement criteria, including retiree health care impact. Data Segmentation Segment data into meaningful groups so that logical conclusions can be obtain. Workforce Planning Analystics • Development of a 5 to 10 year future workforce plan. • Meaningful historical data analysis for business decisions. • Linkage to other organizationals business plans. Data Analysis Perform data analysis (forecasting) based on historical trends and appropriate modeling.

HR Data Elements and Segmentation 7

Data Elements to Consider Demographics • Gender/Ethnicity/Age • Veteran status • Job code / Job title • Job family / feeder data • Union status / Seniority • Department ID or Name Outflows • Transfers out (Migration out) • Retirements (age, tenure) • Leaves (LTD) • Terminations - Date and type • For-cause • Voluntary/Involuntary • Reduction-in-force • Planned organizational changes Inflows • Transfers in (Migration in) • New hires - Date and type (Entry, Experienced) • Job change date/reason • Training Programs • Completion rates • Training timetables • Re-hires 8

Retirement Criteria Know your organizations retirement plan combinations This will be needed to help develop your retirement forecast • Rule of 80 (age plus tenure) • Age and Years of Service Combination • Health care plan impact • Social security impacts/off sets • Average age/service of retirement by job/department/company • Savings plans impact (e. g. 401 K) 9

Segment Data by Types The most common segmentation of historical data by type is: • Retirement • Voluntary Separation (non-retirement) • Involuntary Separations • Headcount This can be broken down by: • Total organization • Business unit/department • Job groups 10

Segment Data by Types The tables below are two different methods in illustrating data for: • Headcount with retirement eligibility by job title These methods are useful to show retirement eligibility impacts current staffing. By providing percent eligible for retirement the organization can clearly see the impact on pending retirements Headcount 11

Segment Data by Types Another common data segmentation are illustrations or tables showing • Years of Service or Tenure • Age of Population These can be displayed by either total company and/or organizational unit Years of Service Or Tenure AGE 12

Segment Data by Types A preferred method to illustrate Age and Years of Service is to create a table similar to the illustration above. In this illustration highlighted cells of the table show eligibility for pension with health care and that group without health care. The years of service and age cohorts are dependent on your organizations benefit plan. 13

Examples of Segment Data by Types History - Retirements History – Attrition (not retirement) History - Hires History – Hires by Job Title 14

Graphical Example of Age and Years of Service 15

CEWD WFP Metrics Data elements should link to the CEWD Key Performance Indicators (KPI) and Critical Success Factors (CSF). These metrics will support state consortia and national reporting by CEWD. Industry Education / Training Potential Applicants KPIs Planned and actual entry level hires Planned and actual experienced hires Attrition by tenure – retirement and other Number of students enrolled in pipeline programs Number of students completing pipeline programs Percentage passing each stage of screening CSFs Total number of employees over time Average of existing workforce over time Average length of tenure over time Total openings / demand Strength of HR Practices Types of Pipeline training programs Number of apprentices by year of program Length of apprenticeship programs Career awareness activities Number of candidates screened Pass rate by Source of hires 16

Additional Tables to Consider 1. 2. 3. 4. 5. 6. Table of Age and Years of Service Table of Average Age and YOS by Dept. and/or Job Family Table of Ethnicity and Gender (percent of total population/hires) Table of Veterans (percent of total population/hires) Table of Jobs Family and percent eligible to retire Table of historical hires by job family, department, company, or key organizational level 7. Table of historical terminations by job family, department, company, or key organizational level 8. Table of turnover for new hires (less than 1 or 2 years of service) 9. Table of entry level hires by total hires 10. Table of promotions by job family 11. Time to hire table for critical positions or job families 12. Table of completions for key training programs 13. Table of ready now candidates for key positions 14. Table of Span-of-control and levels of leaders 15. Table of actuals retirements to eligible retirements 17

Data Analysis and Forecasting 18

Attrition Forecast Model Current Staffing Levels _______ By type or classifications Sources of losses (outflows) Sources of additions (inflows) Employees Out Employees In • Transfers out (Migration out) • Attrition (HR Model) • Terminations • Retirements • Leaves (LTD) • Plan Org Change - Projected Outflows in a year Projected Staffing Level _____ By type or classifications • Transfers in (Migration in) • New Hires • Training Programs (Apprenticeship, Operations, Technicians, Engineering, etc) • Re-Hires + Projected Inflows in a year = Projected Staffing Level 19

Job Feeder Analysis Other Jobs In Org 25% Training Programs 50% Entry level jobs 2 & 4 Yr Colleges Tech Institutions In house apprenticeships Org changes impact Peer level jobs Electrical Tech Mid-career hires from within industry Hires from other industries Contractor hires Experienced Outside Hires 25% To understand the impacts of movement into and out of a job or job family, a job feeder analysis should be conducted. Consider the following model when performing this analysis. 20

Perform Data Analysis • Develop probability of terminations by type (see forecast model) • Retirements • Non-retirements • Other • Develop assumptions based on a 5 year historical view of attrition using data elements • Job type/Job family • Department/organization • Pension plan parameters • Forecast using a regression analysis or some type of probabilistic tool (e. g. SPSS or SAS) • Test forecast assumptions using historical data • Carry forecast out 5 to 10 years by key data elements such as job family, department company Goodor. NEWS!!!! There are Vendor Tools that can do this work!!!!! 21

Vendor Considerations 1. Do the vendor operations align with the organization’s business objectives? 2. Does the vendor have a robust query tool to provide ad hoc reporting? 3. Does the vendor have tools that will display organizational data elements in a format suitable to the business needs? 4. Does the vendor modeling tool properly reflect historical trends for headcount, retirement and non-retirements? 5. Does the vendor provide customer service levels as required by the business? 6. Do the vendor data security requirements meet organization’s business needs? 7. Does the vendor offer ability to project hires by the data elements needed by the organization (e. g. job title, department, organizational level)? 8. Does the vendor tool properly manage segment organizational data? 9. Does the vendor meet the long-term growth needs of the organization’s objectives? 10. Does the vendor have a good reputation for delivering the product in a timely matter? 22

Sample Tools 23

Workforce Planning Dashboard For illustration only 24

Forecast Workforce Requirements 25

Long-Lead Hiring Analysis The segments in the graph could represent job families or department level organizations depending what is being presented. 26

Future Talent Needs – 1 to 5 Years All other Prof, Admin, Evaluators, and Leadership Positions, 95 Operations Positions, 60 Engineering Positions, 80 Field, Maintenance, Craft and Tech Postions, 120 Engineering Positions Field, Maintenance, Craft and Tech Postions Operations Positions All other Prof, Admin, Evaluators, and Leadership Positions 27

Conclusions 28

Key Points to Consider 1. Any dashboard or reports must be relative to the organization’s business objectives. 2. All data must be clearly understood and help the organization understand data in a simplified format. 3. Data and results must be validated, using bad data or wrong data will impact the organization’s trust and creditability. 4. All data must tell a “story” or “paint” a picture of relative information. Do not over produce reports/tables/graphs that take away from the relative facts/findings being reported. 5. Test the reports and results/conclusions with peers before presenting to the organization. 6. Document the analysis, so that it can be replicated and provides sustainability to the process. 7. Let the Strategic Workforce Planning Model guide the reporting of data. 29

Essential Elements of Strategic Workforce Planning 30

Questions & Answer Session 31