Conducting a Needs Assessment to Determine Priorities for Retention of Direct Staff. Ellie Kazemi Cal State University, Northridge



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Transcription:

Conducting a Needs Assessment to Determine Priorities for Retention of Direct Staff Ellie Kazemi Cal State University, Northridge

My Staff are Leaving and I Wanna Know Why! Pertinent Factors that are In Fact Related to Turnover Alyssa Rylander, Amanda Valencia, Marnie Shapiro, Meline Pogosjana, and Ellie Kazemi California State University, Northridge

Impact of Turnover on Companies Hinders company s productivity Employees are less productive (health care employees; Arnold, 2005) Commitment and performance reported as less important Expensive to hire and train new employees (jail officers; Kiekbusch, Price & Theis, 2003) 150% of an employee s annual salary (organization employees; Ramlall, 2003) Hinders company s consistency Loss of knowledge that individual has developed (water management; Harris, 2005) Time spent training new individual (organization employees; Abassi & Holloman, 2000)

Previous Research Turnover intentions are associated to actual turnover Participants rate likelihood to leave on Likert scales 60% that report likelihood to leave actually leave within one year (Dollar & Broach, 2006; Lambert, 2006; Dupré & Day, 2007)

Let s do the numbers... 40 employees ($20,000) 10 report likelihood to leave (25%) 6 employees will actually leave **Cost of employee leaving is 150% of employees salary!!! Additional $30,000 per employee that leaves $180,000/year

Behavior Therapists Nature of recruitment for behavior therapists differs Agencies hired young people Job increases interest in field Objective of employee much more broad High demand for behavior therapist position As a result, we expect some percentage of turnover given the nature of the position and age of direct staff at recruitment.

Factors related to turnover (OBM/IO research) Dissatisfaction with job training (salespersons) Lack of supervisory support (military personnel) Job expectations not met (Navy recruits) Higher pay elsewhere (social workers) Length of time at job (correctional staff) Individual variables (welfare workers; special ed teachers) age, education, knowledge of concepts (Billingsley, 1993; Griffeth, Hom, & Gaertner 2000; Liu, 2006; Dupré & Day 2007)

Group Design

Participants 326 attempted survey 188 finished survey 58% response rate Previous research (mailed surveys) 68% response rate (Ramlall, 2003) 60% response rate (Harris, 2005)

Participants 43% 42% 13% 9% 4% 6% 4% 146 direct staff 19 agencies represented

Demographics Survey Item (n = 146) N % Gender Female 134 91.7 Male 12 8.3 Age 20-25 67 45.9 26-29 41 28.2 30-35 23 15.7 36+ 15 10.2 Number of Children 0 120 82.2 1-2 24 16.5 3+ 2 1.3

Demographics Survey Item (n = 146) N % Ethnicity African-American 9 6.1 Armenian-American 6 4.1 Asian-American 6 4.1 Euro-American/Caucasian 68 46.1 Chicano/Mexican-American 7 4.8 Filipino-American 5 3.4 Latino-American 17 11.5 Middle Eastern-American 6 4.1 Not Listed (Other) 12 9.5 Choose Not to Answer 10 6.3

Demographics (cont.) Survey Item (n = 146) N % Highest Level of Education 2 years 23 15.7 4 years 98 67.1 M.A./M.S. 22 15.1 Ph.D./Psy.D. 3 2.1 Obtained Certifications BCBA 3 2.1 BCABA 0 0 Planned Certifications BCBA 52 35.6 BCABA 22 15.1

Demographics (cont.) Survey Item N % Work Environment Home 69 56.6 School 16 13.1 Both 37 30.3 Mean Median SD Compensation Hourly Pay $19.21 $18.00 4.46

Our Survey

Procedure Recruited from various Southern CA agencies IRB approved On average,45 minute online survey Anonymous Choose not to answer option Ended with positively worded questions

Measures Measures adapted from previous research Held focus groups Interviewed individuals from field Conducted a pilot study

Measures in Survey Age, education, degree, years of service in the field Severity of cases, age of clients Context in which they provide therapy Training and supervision (Liu, 2006; Eisenberger, 2002) Satisfaction with infrastructure (e.g., promotions) Pay, insurance, reimbursements Hours worked per week Test of ABA Concepts (Furtkamp et. al, 1982) Knowledge of autism (Schwartz & Drager, 2008) Adherence to science and philosophy of BA Motivation to work and advance in field (Larkin et. al, 2007)

Turnover Item Turnover Intentions Scale: (α =.89) Taken directly from Dupré and Day (2007) Two items oppositely worded 5-point Likert scale measuring likelihood to leave current job. Example: I will leave my job if another job becomes available. 1 2 3 4 5 Highly Likely Highly Unlikely

Turnover Scale Items 1 2 1. I will STAY at my job my for as long as I can -.599** 2. I will LEAVE my job if another job becomes available.599** - **Correlation significant at 0.01 level (2-tailed) # of Participants 35 30 25 20 15 10 5 0 Highly Likely Likelihood to Leave (n = 118) 38% Leave Somewhat Likely 45% Stay Undecided Somewhat Unlikely Highly Unlikely

Likelihood to Stay in the Field # of Participants 40 35 30 25 20 15 10 5 0 Likely to Leave Job (n = 45); Mean = 3.3 33% 6 9 9 7 p <.001 47% 14 # of Participants Likely to Stay at Job (n = 53); Mean = 4.6 40 35 30 25 20 15 10 5 0 0 0 4 11 38

Individuals Who Switched Companies One Company (n = 67) More than one Company (n = 51) # of Participants 16 14 12 10 8 6 4 2 0 # of Participants 16 14 12 10 8 6 4 2 0

Correlates of Turnover Turnover Training Satisfaction.272** Supervision Satisfaction.279** Satisfaction with Pay.376**

Forward Sequential Regression Analysis Training 6% Training& Supervision 14% 22% Turnover Training, Supervision, & Pay

Regression Table Change Statistics Model R R Square Adjusted R Square Std. Error of the Estimate R Square Change F Change df1 df2 Sig. F Change 1.243 a.059.048 1.32588.059 5.633 1 90.020 2.372 b.138.119 1.27588.079 8.193 1 89.005 3.471 c.222.196 1.21892.084 9.513 1 88.003 1. Predictor: Initial Training Comp 2. Predictors: Initial Training Comp & Sup Comp 3. Predictors: Initial Training Comp, Sup Comp, & Pay Previous research can explain up to 6-26% of the variability in turnover. (Griffeth, Hom, & Gaertner, 2000; Lambert, 2006)

Factors Related to Turnover Predictor R 2 β Training.059.096 Supervision.138.230 Pay.222.305

References Abbasi, S., & Hollman, K. (2000). Turnover: The Real Bottom-line. Public Personnel Management, 29(3), 333-342. Arnold, E. (2005). Managing Human Resources to Improve Employee Retention. The Health Care Manager, 24(2), 132-140. Billingsley, B.S. (1993). Teacher Retention and Attrition in Special Education and General Education: A Critical Review of the Literature. The Journal of Special Education, 27(2), 137-134. Dollar, C. Broach, D. (2006). Comparison of Intent to Leave with Actual Turnover. Applied H.R.M Research, 16(1), 1-6. Dupre, K.E., & Day, A.L. (2007). The effects of supportive management and job quality on the turnover intentions and health of military personnel. Human Resource Management, 46(2), 185-201. Griffeth, R.W., Hom, P.W., Gaertner, S. (2000). A Meta-Analysis of Antecedents and Correlates of Employee Turnover: Update, Moderator Tests, and Research Implications for the Next Millennium. Journal of Management, 26(3), 463-488. Harris, K.J., Kacmar, K.M., & Witt, L.A. (2005). An examination of the curvilinear relationship between leader-member exchange and intent to turnover. Journal of Organizational Behavior, 26, 363-378. Kiekbusch, R., Price, W., & Theis, J. (2003). Turnover predictors: Causes of employee turnover in sheriff-operated jails. Criminal Justice Studies: A Critical Journal of Crime, Law, and Society, 16, 67-76. Lambert, E.G. (2006). I want to leave: A test of a model of turnover intent among correctional staff. Applied Psychology in Criminal Justice, 2(1), 57-83. Liu, C. (2006). The early employment influences of sales representatives on the development of organizational commitment. Employee Relations, 29(1), 5-15. Ramlall, S. (2003). Managing Employee Retention as a Strategy for Increasing Organizational Competitiveness. Applied H.R.M. Research, 8(2), 63-72.