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“Regression analysis is a very effective quantitative forecasting technique for short-, medium and long-range time horizons and can be easily updated.[i]” A simple linear regression model is a mathematical relationship between two quantitative variables, i.e. X and Y. Y is the variable we seek to predict based on the other variable X, for which we have information. Regression can predict Scanim’s personnel requirements for inbound operators at varying levels of Chrysler auto sales. In preparing a hypothetical regression analysis, I also assumed I had access to 5 years of historical data with respect to matching Chrysler auto sales to the number of inbound service and warranty claims operators. I also assumed that auto sales drive the number of warranty claims processed in our call center. A regression analysis could allow us to make the following hypothetical HR Demand forecast for Scanim: “For every $1 Million increase in sales (X) there is a predicted increase of 6 operators (Y) associated with that change.”
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The forecast time period is usually one year in length. To predict the number of employees who will remain in their positions at year’s end, the matrix should be multiplied by the number of employees in each job at the start of the year. The Markov Model below was created specifically for Scanim’s new warranty claims contract. I, as the Scanim HR Manager for Ontario, along with the ISWCT Management Team can rely on the model to predict the internal supply of our inbound operators into the future.
Markov Model
|Year 2014 |
Year 2013 |Initial Staffing Level |Manager |Coach/ Supervisor |Bilingual CSR |CSR |Exit | |Manager |1 |1 |- |- |- |- | |Coach Supervisor |4 | |2(.80) |1(.10) | |1(0.10) | |Bilingual …show more content…
The ISWCT’s 4 coach supervisors could benefit from mentoring prior to the start of our new contract. A mentor and/or coach could help our supervisors to better recruit, screen, and hire front line CSRs as well as teach supervisors how to mentor and coach front-line employees and assist with any other skill to ensure the success of the new contract.[ix] Furthermore, there is a positive correlation between the percent of time coaching CSRs and CSR retention.[x] Our 4 coaching supervisors should thus, coach and support our CSRs to boost their confidence and self esteem for higher productivity, greater customer satisfaction and problem resolution. The investment in mentoring and coaching outweigh the
The forecast time period is usually one year in length. To predict the number of employees who will remain in their positions at year’s end, the matrix should be multiplied by the number of employees in each job at the start of the year. The Markov Model below was created specifically for Scanim’s new warranty claims contract. I, as the Scanim HR Manager for Ontario, along with the ISWCT Management Team can rely on the model to predict the internal supply of our inbound operators into the future.
Markov Model
|Year 2014 |
Year 2013 |Initial Staffing Level |Manager |Coach/ Supervisor |Bilingual CSR |CSR |Exit | |Manager |1 |1 |- |- |- |- | |Coach Supervisor |4 | |2(.80) |1(.10) | |1(0.10) | |Bilingual …show more content…
The ISWCT’s 4 coach supervisors could benefit from mentoring prior to the start of our new contract. A mentor and/or coach could help our supervisors to better recruit, screen, and hire front line CSRs as well as teach supervisors how to mentor and coach front-line employees and assist with any other skill to ensure the success of the new contract.[ix] Furthermore, there is a positive correlation between the percent of time coaching CSRs and CSR retention.[x] Our 4 coaching supervisors should thus, coach and support our CSRs to boost their confidence and self esteem for higher productivity, greater customer satisfaction and problem resolution. The investment in mentoring and coaching outweigh the