Application of Change Theory in Software Application Delivery.

Theory of Change is a methodology for planning, participation, and evaluation. Can it apply to software application delivery? Understanding the current process and identifying what went wrong during the previous deliverable is one way to self-evaluate practices. Evaluation involves systematically appraising the status of all available indicators associated with organization and systems-level outputs and individual-level valued outcomes to come up with workable plan for the next execution (Shogren et al., 2018). The distinction between outputs and outcomes is based on the extensive literature regarding the use of logic models that facilitate the alignment of supports delivery development, implementation, and evaluation. Three step change model from the theoretical conceptual framework of Kurt Lewin’s (Lewin, 1947; Schein, 1996/1999) is used for this study. The whole system of structures and forces as well as the interdependencies within the system are examined. The three-step unfreezing, changing and freezing model is presented in the context of a field theory. In their critical analysis of change management framework, Rajan & Ganesan (2017) suggest, change management processes are sheer necessity for organizational emancipation, sustenance and growth and demonstrate the maturity level of an organization.

The dynamic nature of software requirement changes and subsequent deployment scheduling shift affects all stakeholders. One of the most challenging issues that software application development projects must address is the dynamic nature of change process requirements (Akbar et al., 2019). Customers may change requirements frequently, but the change process can be made predictable if the factors affecting the change process are identified. That is the reason the Kurt Lewin’s change model will be an ideal framework to use to determine the factors.

Software application development managers and stake holders should consider key factors that affect the successful implementation of continuous software deployment. Change leaders should apply change strategies throughout the three-step change process. Stojanov et al (2018) researched on the challenges of changing the approach that has been followed up for long time. The research acknowledged the difficulty to change especially software systems with layered architecture is particularly difficult since the complexity of software should be considered at several level since it can include many modules or packages. In data-driven software applications, it is important to examine all the methods and tools that can reduce the application complexity and simplify the management of changes during maintenance phase. Simpler systems will be easier to change and maintain.

Create the motivation for change (unfreezing) by making systems ready for change. This includes opening the software deployment change process for change instead of following existing policies and procedures. This allows the organization to reevaluate the change process and address issues that arose in the past to prevent from happening again. Once the unfreezing is done, the next step will be to ensure cognitive redefinition, restructuring and learning (changing) by involving all stake holders on timely basis. It is critical to have a clear and collaborative communication between the project team and all stakeholders to apply the change successfully. Once the change is tested and implemented, make the change permanent (freezing) by implementing a training, communication, and repeatable change process.

References

Akbar, M. A., Sang, J., Nasrullah, Khan, A. A., Mahmood, S., Qadri, S. F., Hu, H., & Xiang, H. (2019). Success factors influencing requirements change management process in global software development. Journal of Computer Languages, 51, 112–130. https://doi-org.ezproxy.umgc.edu/10.1016/j.cola.2018.12.005

Rajan, R., & Ganesan, R. (2017). A critical analysis of John P. Kotter's change management framework. Asian Journal of Research in Business Economics and Management, 7(7), 181-203.

Shogren, K. A., Schalock, R. L., & Luckasson, R. (2018). The Use of a Context‐Based Change Model to Unfreeze the Status Quo and Drive Valued Outcomes. Journal of Policy & Practice in Intellectual Disabilities, 15(2), 101–109. https://doi-org.ezproxy.umgc.edu/10.1111/jppi.12233

Stojanov, Z., Dobrilovic, D., & Stojanov, J. (2018). Extending data-driven model of software with software change request service. Enterprise Information Systems, 12(8/9), 982–1006. https://doi-org.ezproxy.umgc.edu/10.1080/17517575.2018.1445296