Event Title

Using Demographical Information to Predict Work Performance Among Shiftgig, Inc. Employees: A Case Study of Temporary On-Demand Staffing

Session Number

D01

Advisor(s)

Jade Martin, Shift Gig Inc

Location

A-135

Start Date

28-4-2016 1:10 PM

End Date

28-4-2016 1:35 PM

Abstract

Shiftgig, Inc., a technology company founded in 2012, has created a mobile platform to remedy the high turnover experienced in the service industry by acquiring a workforce that is deployable at moment’s notice. The platform acts as a medium between the workforce and the employer. The greatest challenge Shiftgig experiences is achieving a balance between these two users. This case study addressed this issue by breaking it into two parts: quantifying market demand and the availability of the targeted supply. Prior to this study, a survey was conducted to understand the varying interests among Shiftgig’s demographical workforce. This study used the survey results to understand how Shiftgig can estimate the size of the workforce needed to optimize the shift fill rate. The survey suggests that there are significant differences in job preferences among genders and age groups. Preliminary data also shows that Shiftgig would need to spend approximately $1.38 million to recruit a workforce capable of generating the revenue necessary to meet its 2016 goals. An outcome of this investigation is the potential to create forecasting models which could show the anticipated workforce population for 2016 by using data from 2015.


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Apr 28th, 1:10 PM Apr 28th, 1:35 PM

Using Demographical Information to Predict Work Performance Among Shiftgig, Inc. Employees: A Case Study of Temporary On-Demand Staffing

A-135

Shiftgig, Inc., a technology company founded in 2012, has created a mobile platform to remedy the high turnover experienced in the service industry by acquiring a workforce that is deployable at moment’s notice. The platform acts as a medium between the workforce and the employer. The greatest challenge Shiftgig experiences is achieving a balance between these two users. This case study addressed this issue by breaking it into two parts: quantifying market demand and the availability of the targeted supply. Prior to this study, a survey was conducted to understand the varying interests among Shiftgig’s demographical workforce. This study used the survey results to understand how Shiftgig can estimate the size of the workforce needed to optimize the shift fill rate. The survey suggests that there are significant differences in job preferences among genders and age groups. Preliminary data also shows that Shiftgig would need to spend approximately $1.38 million to recruit a workforce capable of generating the revenue necessary to meet its 2016 goals. An outcome of this investigation is the potential to create forecasting models which could show the anticipated workforce population for 2016 by using data from 2015.