HR Committee Dashboard Discussion HR Committee Board of Trustees - - PowerPoint PPT Presentation

HR Committee Dashboard Discussion

HR Committee – Board of Trustees Meeting January 8th 2020

Tony Redmond–CHRO

HR Dashboard

Description Previous Qtr/FY Q1 FY20 (July 1 to Sept 30 2019) Current Qtr/FY Q2 FY20 (Oct 1 to Dec 31 2019) Benchmark / Source Target goal Strategic Alignment Details Days it takes to fill a position after an

• pening has been

posted 49.46 days 58.53 days 51 days 51 days Workforce Sustainability Time to fill impacted by 10 specific positions: AHD Certified Nursing Assistant - 357 days to fill AHD Registered Nurse - Park Bridge - 231 days to fill Clinical Nurse Il (five positions): 271, 356, 367, 232 and 220 days to fill Clinical Nurse Iv (two positions): 219 and 234 days to fill Psychiatrist II Board Certified: 434 days to fill Excluding these positions, Time to Fill would be 48.19 days. Days from offer accepted to first day at work 21.56 days 31.66 days 19 days Workforce Sustainability Q2 - 261 new hires to onboard Q1 - 299 new hires to onboard (including 50 new residents) Percent of external applicants, new hires, and current employees that reside in Alameda County 2,557 of 4,573 (56%) ______________________ 134 of 226 (59%) ______________________ 3,190 of 4962 (64%) 1,965 of 3,574 (55%) _____________________ 101 of 161 (62%) _____________________ 3,146 of 4,894 (64%) Workforce Sustainability Created partnerships with local community organizations. Formed partnership with the EDD. Working with niche job posting sites to increase employment of local community residents at AHS.

HR Dashboard

Description Previous Qtr/FY Q1 FY20 (July 1 to Sept 30 2019) Current Qtr/FY Q2 FY20 (Oct 1 to Dec 31 2019) Benchmark / Source Target goal Strategic Alignment Details Days employees are unable to work due to a work related injury 3.19 avg days per fte TBD 1.83 avg days per fte 1.83 avg days per fte Workforce Sustainability Total productive hours dropped from 2,002,558 in the 4th quarter to 1,657,482 in the 1st. This is the primary factor in the increase in average loss days from 2.56 to 3.19. Number of Workers Compensation Injuries 65 66 50 50 Workforce Sustainability Injury and Illness Prevention Plan approved by BOT 1/24/19; On-going preventative ergonomics program - 385 evaluations completed in 2018. Focus

• n reduction of Safe Patient Handling

injuries.

HR Dashboard

Dashboard Item Description Previous Qtr/FY Q1 FY20 (July 1 to Sept 30 2019) Current Qtr/FY Q2 FY20 (Oct 1 to Dec 31 2019) Benchmark / Source Target goal Strategic Alignment Details Annual Turnover - System Overall - Annualized/Qtrly

_____________________

First Year - Annualized/Qtrly

_____________________

Second Year - Annualized/Qtrly Number of separations divided by Number of Employees Annualized - 15.53% Quarterly - 3.88%

term count = 188 ______________________

Annualized - 27.80% Quarterly - 6.95%

term count = 44 ______________________

Annualized - 28.96% Quarterly - 7.24%

term count = 37

Annualized - 15.01% Quarterly - 3.75%

term count = 181 _____________________

Annualized - 29.08% Quarterly - 7.27%

term count = 49 _____________________

Annualized - 25.43% Quarterly - 6.36%

term count = 26

16.70% 11.09% Workforce Sustainability Reviewing data on top voluntary term reasons (from exit interview data) Launched 30, 60, 90 day reminder process in Passport to Performance for Leadership to continue to "onboard" new employees within their departments Top Term Reasons: Resignation (84); Resignation – Non Compliance (19) Retirement (16) Annual Turnover - Nursing Overall - Annualized/Qtrly

_____________________

First Year - Annualized/Qtrly

_____________________

Second Year - Annualized/Qtrly Number of Nursing separations divided by Number of Nursing Employees Annualized - 23.77% Quarterly - 5.94%

term count = 88 ______________________

Annualized - 51.69% Quarterly - 12.92%

term count = 23 ______________________

Annualized - 54.96% Quarterly - 13.74%

term count = 18

Annualized - 15.17% Quarterly - 3.79%

term count = 56 _____________________

Annualized - 32.16% Quarterly - 8.04%

term count = 16 _____________________

Annualized - 35.16% Quarterly - 8.79%

term count = 8

14.70% 11.09% Financial benefit

• save cost of

hiring,

• nboarding new

employees / Workforce - maintaining quality of care through consitent workforce Reviewing data on top voluntary term reasons (from exit interview data) Launched 30, 60, 90 day reminder process in Passport to Performance for Leadership to continue to "onboard" new employees within their departments Top Term Reasons: Resignation (84); Resignation-Non Compliance (19) Retirement (16)

Exit Interview Data – Top Reasons for Leaving

VOLUNTARY TERMS VOLUNTARY TERMS VOLUNTARY TERMS REASON FOR LEAVING FY 2018 REASON FOR LEAVING FY 2019 REASON FOR LEAVING FY 2020 YTD Time - Shift/Schedule 30 Retirement - Retirement 39 Retirement - Retirement 8 Retirement - Retirement 24 Time - Shift/Schedule 22 Career - Different Type of Work 4 Relocation - Employee Inititated 23 Relocation - Employee Inititated 17 Time - Shift/Schedule 4 Time - Commute 14 Career - Different Type of Work 15 Management - Other 3 Career - Developmental/Growth Opportunity 11 Total Rewards - Base Pay 12 Total Rewards - Base Pay 3 Other Reasons 123 Other Reasons 311 Other Reasons 14 No Response 236 No Response 300 No Response 98 Total 461 Total 519 Total 134 INVOLUNTARY TERMS INVOLUNTARY TERMS INVOLUNTARY TERMS REASON FOR LEAVING FY 2018 REASON FOR LEAVING FY 2019 REASON FOR LEAVING FY 2020 YTD Involuntary - Fired 13 Involuntary - Laid Off/Job Elimination 14 Involuntary - Laid Off/Job Elimination 4 Involuntary - Unsatisfactory Performance 5 Involuntary - Fired 10 Involuntary - Fired 2 Involuntary - Laid Off/Job Elimination 4 Involuntary - Unsatisfactory Performance 6 Involuntary - Violation of Company Policy 2 Involuntary - Other 4 Involuntary - Other 5 Involuntary - Other 2 Management - Unprofessional Behavior 3 Involuntary - Violation of Company Policy 3 Other Reasons 7 Other Reasons 12 No Response 51 No Response 91 No Response 43 Total 91 Total 143 Total 53

Top Voluntary Reasons for Leaving – FY 2019 By Gender and Ethnicity

10 20 30 40

Career - Different Type of Work Relocation - Employee Inititated Retirement - Retirement Time - Shift/Schedule Total Rewards - Base Pay

FY 2019 - Female

Female Asian Female Black or African American Female Hispanic or Latino Female Two or More Races Female Unspecificed Female White

5 10

Career - Different Type of Work Relocation - Employee Inititated Retirement - Retirement Time - Shift/Schedule Total Rewards - Base Pay

FY 2019 - Male

Male Asian Male Black or African American Male Hispanic or Latino Male White

Top Involuntary Reasons for Leaving – FY 2019 By Gender and Ethnicity

5 10

Involuntary - Fired Involuntary - Laid Off/Job Elimination Involuntary - Other Involuntary - Unsatisfactory Performance Involuntary - Violation of Company Policy

Fy 2019 Female

Female Asian Female Black or African American Female Hispanic or Latino Female Two or More Races Female White 2 4 6 8

Involuntary - Fired Involuntary - Laid Off/Job Elimination Involuntary - Other Involuntary - Unsatisfactory Performance Involuntary - Violation of Company Policy

FY 2019 Male

Male Asian Male Black or African American Male Two or More Races Male White

Top Voluntary Reasons for Leaving – FY 2018 By Gender and Ethnicity

10 20 30

Career - Developmental/Growth Opportunity Relocation - Employee Inititated Retirement - Retirement Time - Commute Time - Shift/Schedule

FY 2018 Females

Female Asian Female Black or African American Female Hispanic or Latino Female Two or More Races Female White

5 10 15

Career - Developmental/Growth Opportunity Relocation - Employee Inititated Retirement - Retirement Time - Commute Time - Shift/Schedule

FY 2018 Males

Male Asian Male Black or African American Male Hispanic or Latino Male Two or More Races Male White

Top Involuntary Reasons for Leaving – FY 2018 By Gender and Ethnicity

5 10

Involuntary - Fired Involuntary - Laid Off/Job Elimination Involuntary - Other Involuntary - Unsatisfactory Performance Management - Unprofessional Behavior

FY 2018 Female

Female Asian Female Black or African American Female Hispanic or Latino Female Two or More Races Female White 2 4 6

Involuntary - Fired Involuntary - Laid Off/Job Elimination Involuntary - Other Involuntary - Unsatisfactory Performance Management - Unprofessional Behavior

FY 2018 Male

Male Asian Male Black or African American Male Hispanic or Latino Male Hawaiian or Pacific Islander Male Two or More Races Male White

Top Voluntary Reasons for Leaving – FY 2017 By Gender and Ethnicity

5 10 15 20

Career - Developmental/Growth Opportunity Relocation - Employee Inititated Retirement - Retirement Time - Commute Time - Shift/Schedule

FY 2017 Female

Female Asian Female Black or African American Female Hispanic or Latino Female Hawaiian or Pacific Islander Female Two or More Races Female White 2 4 6 8

Career - Developmental/Growth Opportunity Relocation - Employee Inititated Retirement - Retirement Time - Commute Time - Shift/Schedule

FY 2017 Male

Male Asian Male Black or African American Male Hispanic or Latino Male Two or More Races Male White

Top Involuntary Reasons for Leaving – FY 2017 By Gender and Ethnicity

5 10

Involuntary - Fired Involuntary - Laid Off/Job Elimination Involuntary - Other Involuntary - Unsatisfactory Performance Management - Unprofessional Behavior

FY 2017 Female

Female Asian Female Black or African American Female Hispanic or Latino Female Two or More Races Female White 2 4 6 8

Involuntary - Fired Involuntary - Unsatisfactory Performance

FY 2017 Male

Male Asian Male Black or Africah American Male White

EEO1 Data – Current Employees

500 1000 1500 2000 2500 EXEC/SENIOR MGRS FIRST/MID-LVL MGRS PROFESSIONALS TECHNICIANS ADMIN SUPPORT CRAFT WORKERS SERVICE WORKERS

EEO1 Data 2019 - Females

Hispanic Whire Black Hawaiian or Pacific Islander Asian Native American 100 200 300 400 500 600 700 800 EXEC/SENIOR MGRS FIRST/MID-LVL MGRS PROFESSIONALS TECHNICIANS ADMIN SUPPORT CRAFT WORKERS SERVICE WORKERS

EE01 Data 2019 - Males

Hispanic White Black Hawaiian or Pacific Islander Asian Native American Two or More Races 500 1000 1500 2000 EXEC/SENIOR MGRS FIRST/MID-LVL MGRS PROFESSIONALS TECHNICIANS ADMIN SUPPORT CRAFT WORKERS SERVICE WORKERS

EEO1 Data 2018 - Females

Hispanic White Black Hawaiian or Pacific Islander Asian Native American Two or More Races 100 200 300 400 500 600 700 EXEC/SENIOR MGRS FIRST/MID-LVL MGRS PROFESSIONALS TECHNICIANS ADMIN SUPPORT CRAFT WORKERS SERVICE WORKERS

EEO1 DATA 2018 - Males

Hispanic White Black Hawaiian or Pacific Islander Asian Native American Two or More Races