Date of Award


Document Type


Degree Name

Master of Science (MS)


Mathematics and Systems Engineering

First Advisor

Juan C. Avendano Arbelaez

Second Advisor

Luis Daniel Otero

Third Advisor

Mary Ann Gaal

Fourth Advisor

Adrian M. Peter


Task Optimization via the use of automated process improvements is becoming more widespread as more industries lean into the concepts surrounding digital transformation. This shift also necessitates a complementary adaptation in project management methodologies to support the rapid and ever-changing environment, requirements, and innovations. This thesis examines the effectiveness of Agile methodology in managing digital automation projects, with a specific focus placed on process improvements with systems engineering. It accomplished this by contrasting the original model, designed and derived utilizing traditional project management techniques, with the proposed model which is a direct result of the application of Agile project practices. This comparative analysis aims to highlight the contributions of Agile methodologies in facilitating the digital transformation process. It examines a case study of the use of Agile methodology to manage the development and implementation of an internal process improvement via the use of scripted automation. The Product Management and Sustainment (PM&S) team has a monthly deliverable consisting of upwards of 150 discrete zip packages that must be delivered via a Customer Resource Management (CRM) System. The zip packages contain multiple workflow documents and asset inventory spreadsheets that are automatically updated for content. The current established process is to manually create each discrete zip package, as the content varies and is categorized by a customer identifier (referred to as a ‘node_ID’). Historical data analysis shows that creation of the zip packages takes approximately an hour or more of uninterrupted work depending on who is completing the task. Assigned day to day workload and tasking results in zip generation over the course of a week. This thesis presents a comparative analysis of the manual process versus the automated process, highlighting the impact on operational efficiency and error reduction.

Various applications domains exist that employ similar activities that could benefit from the use of automation. Examples of these use cases across these domains serve to demonstrate the potential scalability and adaptability of the developed utility across various industries with an emphasis on the broader implications of the proposed research. Some examples are:

  • Tax Firms - Zip up completed tax packages for customers by customerID
    • Ideally for larger firms that may work on multiple packages at once
    • Utility would allow for package generation of multiple customers at once as opposed to as they are worked on
  • Field Engineering team creates similar discrete packages for delivery to customers via the same CRM system
  • Education - Student assignments where there are multiple files per week (folders by week) and discrete zip packages are required on submission as opposed to a single zip containing multiple directories
  • Any need to create multiple zip packages
    • More than 3 zip packages on average to benefit from the time savings

The proposed solution involves the development of a PowerShell utility to automatically create the discrete zip packages. Ideally, the scripted solution will be generic enough for re-utilization on separate applications requiring similar capability. The development, implementation, and outcomes of this proposed utility are evaluated, providing insights into the broader application of digital transformation initiatives and tools in systems engineering. Creation and use of an automated utility significantly decreases user error in package generation and manual execution time, as well as removing the need for package validation. The research findings underscore the utility’s role in supporting the company’s digital transformation efforts while also contributing to the field of systems engineering.