PROCESS AUTOMATION CRITERIA IDENTIFICATION AND SELECTION: A CASE STUDY IN A PAYROLL COMPANY
Open Access
- Author:
- Yi, Fuyu
- Graduate Program:
- Industrial Relations and Human Resources
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- December 04, 2008
- Committee Members:
- Sumita Raghuram, Thesis Advisor/Co-Advisor
Sumita Raghuram, Thesis Advisor/Co-Advisor
Sandeep Purao, Thesis Advisor/Co-Advisor
Shawn Clark, Thesis Advisor/Co-Advisor
Paul Clark, Thesis Advisor/Co-Advisor - Keywords:
- Services
Process Automation
Case Study
Criteria - Abstract:
- This research is intended to provide insights to managers making decisions on automation. With the objective of investigating criteria for business process automation, the research question is defined as: “What are the criteria used by managers to select processes or part of a process for automation?” Although there is some development in the practice of selecting and prioritizing processes for automation, no academic research exists to validate those criteria used in the prioritization of automating processes. Due to the apparent lack of rigorous theories, our research utilized a case study strategy to investigate the criteria for business process automation, which can be helpful in selecting and prioritizing candidates for the automation process. This study will generate three major products: a series of process maps; process maps with varying automation levels; and a list of criteria for process automation. The first product, process maps, helps managers to better understand their business operation in order to discuss future improvement. The second product, automation level process maps, provides a discussion platform for managers to view technology distribution within the company and detect automation opportunities. The automation criteria, the primary product of this project, will provide new empirical evidence for critical factors for assessing process automation priorities, contributing to the efforts of building an automation decision model.