Enterprise Architecture and Project Management Synergy: Optimizing Post-M&A Integration for Large-Scale Enterprises

Enterprise Architecture and Project Management Synergy: Optimizing Post-M&A Integration for Large-Scale Enterprises

Authors

  • Mahadu Vinayak Kurkute Stanley Black & Decker Inc, USA
  • Deepak Venkatachalam CVS Health, USA
  • Priya Ranjan Parida Universal Music Group, USA

Downloads

Keywords:

Enterprise Architecture, EA Frameworks

Abstract

The integration of enterprise architecture (EA) and project management (PM) methodologies is critical for the successful execution of post-merger and acquisition (M&A) integration projects, particularly within large-scale enterprises. This paper investigates the synergy between EA and PM, focusing on their combined impact on optimizing post-M&A integration processes. Given the complexity and scale of M&A integrations, the alignment of EA principles with PM practices is pivotal in mitigating risks, reducing integration complexity, and enhancing overall efficiency.

Enterprise architecture provides a structured framework for aligning business strategies with IT infrastructure, offering a holistic view of an organization's processes, information systems, and technologies. By leveraging EA principles, organizations can establish a coherent integration strategy that ensures consistency across diverse business units and technology platforms. This integration framework facilitates a comprehensive understanding of existing systems, enabling the identification of redundancies and inefficiencies that may arise during the integration process.

On the other hand, project management methodologies offer systematic approaches to planning, executing, and controlling integration projects. The application of PM principles ensures that integration activities are conducted within predefined timelines, budgets, and scopes. Effective project management is essential for coordinating cross-functional teams, managing stakeholder expectations, and addressing unforeseen challenges that may impact the integration process.

This paper delineates the intersections between EA and PM in the context of post-M&A integration, emphasizing how their synergy can drive successful outcomes. The research employs a multi-dimensional analysis to explore how EA frameworks can be integrated into PM processes to streamline project execution and optimize resource allocation. Key areas of focus include the alignment of EA models with project management plans, the utilization of EA tools to support project tracking and reporting, and the role of EA in defining integration goals and milestones.

In particular, the study examines various EA methodologies, such as the Zachman Framework, The Open Group Architecture Framework (TOGAF), and the Business Process Framework (eTOM), and their relevance to post-M&A integration. The research also evaluates project management approaches, including Agile, Waterfall, and Hybrid methodologies, assessing their compatibility with EA principles in facilitating integration activities.

Case studies of large enterprises that have successfully implemented EA and PM integration strategies are presented to illustrate practical applications and outcomes. These case studies highlight best practices, common challenges, and solutions that have emerged from real-world scenarios. The analysis provides insights into how organizations can leverage EA and PM to achieve seamless integration, improve operational efficiencies, and realize strategic objectives post-M&A.

Furthermore, the paper addresses the challenges associated with integrating EA and PM practices, including issues related to organizational culture, stakeholder engagement, and the management of integration risks. It explores strategies for overcoming these challenges, such as the adoption of change management techniques, the establishment of clear governance structures, and the development of robust communication plans.

The findings of this research contribute to a deeper understanding of how the synergy between enterprise architecture and project management can enhance the effectiveness of post-M&A integration efforts. By providing a comprehensive framework for aligning EA and PM, the paper offers practical guidance for large enterprises seeking to optimize their integration processes and achieve long-term success in the aftermath of mergers and acquisitions.

Downloads

Download data is not yet available.

References

J. A. Zachman, "A Framework for Information Systems Architecture," IBM Systems Journal, vol. 26, no. 3, pp. 276-292, 1987.

M. Themistocleous, J. P. Mayer, and C. P. M. C. Lu, "Enterprise Architecture and Project Management: Insights from the TOGAF Framework," International Journal of Information Management, vol. 30, no. 3, pp. 215-225, 2010.

Pelluru, Karthik. "Prospects and Challenges of Big Data Analytics in Medical Science." Journal of Innovative Technologies 3.1 (2020): 1-18.

Rachakatla, Sareen Kumar, Prabu Ravichandran, and Jeshwanth Reddy Machireddy. "Building Intelligent Data Warehouses: AI and Machine Learning Techniques for Enhanced Data Management and Analytics." Journal of AI in Healthcare and Medicine 2.2 (2022): 142-167.

Machireddy, Jeshwanth Reddy, Sareen Kumar Rachakatla, and Prabu Ravichandran. "Cloud-Native Data Warehousing: Implementing AI and Machine Learning for Scalable Business Analytics." Journal of AI in Healthcare and Medicine 2.1 (2022): 144-169.

Ravichandran, Prabu, Jeshwanth Reddy Machireddy, and Sareen Kumar Rachakatla. "Generative AI in Data Science: Applications in Automated Data Cleaning and Preprocessing for Machine Learning Models." Journal of Bioinformatics and Artificial Intelligence 2.1 (2022): 129-152.

Potla, Ravi Teja. "Scalable Machine Learning Algorithms for Big Data Analytics: Challenges and Opportunities." Journal of Artificial Intelligence Research 2.2 (2022): 124-141.

Singh, Puneet. "AI-Powered IVR and Chat: A New Era in Telecom Troubleshooting." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 143-185.

Devapatla, Harini, and Jeshwanth Reddy Machireddy. "Architecting Intelligent Data Pipelines: Utilizing Cloud-Native RPA and AI for Automated Data Warehousing and Advanced Analytics." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 127-152.

Machireddy, Jeshwanth Reddy, and Harini Devapatla. "Leveraging Robotic Process Automation (RPA) with AI and Machine Learning for Scalable Data Science Workflows in Cloud-Based Data Warehousing Environments." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 234-261.

J. P. Williams, "The Role of Enterprise Architecture in M&A Integration," Journal of Enterprise Architecture, vol. 8, no. 4, pp. 24-32, 2012.

G. Gable, "Evaluating the Effectiveness of Enterprise Architecture Frameworks in Project Management," Information Systems Journal, vol. 18, no. 1, pp. 31-45, 2008.

D. G. Nicolescu and L. M. Tomescu, "Enterprise Architecture and Agile Project Management Integration: A Case Study," Journal of Systems and Software, vol. 83, no. 11, pp. 2130-2141, 2010.

S. G. Hartmann and M. J. Behrendt, "Agile Methods in Enterprise Architecture: Managing Complexity in M&A Integration," Information and Software Technology, vol. 54, no. 4, pp. 409-421, 2012.

H. A. Rezaie and F. S. Klein, "TOGAF-Based Enterprise Architecture for Post-M&A Integration," Journal of Strategic Information Systems, vol. 22, no. 2, pp. 144-158, 2013.

C. C. Chan, "Project Management and Enterprise Architecture: A Combined Approach to M&A Integration," Project Management Journal, vol. 45, no. 1, pp. 25-38, 2014.

M. B. Jones and A. H. Smith, "Frameworks for Enterprise Architecture: The Role of Zachman and TOGAF," Information Systems Management, vol. 27, no. 3, pp. 211-220, 2010.

T. K. Smith and J. T. Green, "Enterprise Architecture and Its Impact on Project Management Efficiency," Journal of Enterprise Information Management, vol. 29, no. 4, pp. 511-528, 2016.

A. K. Gupta and R. S. Verma, "Integration of Enterprise Architecture and Project Management for M&A Success," International Journal of Project Management, vol. 33, no. 2, pp. 375-387, 2015.

R. L. Johnson and D. E. Baker, "M&A Integration Challenges: The Role of EA in Addressing Common Issues," European Journal of Information Systems, vol. 24, no. 1, pp. 1-15, 2015.

P. S. Yadav and M. K. Patel, "Best Practices in EA and PM for Successful M&A Integration," Journal of Information Technology Management, vol. 29, no. 3, pp. 22-34, 2017.

E. J. Stone and B. C. Turner, "Strategic Alignment of EA and PM in the Context of M&A," Journal of Business Research, vol. 69, no. 10, pp. 4021-4032, 2016.

L. F. Anderson and R. J. Wright, "Post-M&A Integration: Leveraging Enterprise Architecture for Success," Management Decision, vol. 52, no. 6, pp. 1156-1172, 2014.

A. L. Moore and K. A. Johnson, "Enhancing M&A Integration through EA and PM Synergy," Information Systems Frontiers, vol. 17, no. 2, pp. 237-250, 2015.

N. J. Robinson and L. M. Davis, "Case Studies in EA and PM Integration for M&A Projects," Journal of Strategic Management, vol. 36, no. 5, pp. 725-740, 2017.

B. T. Lee and C. E. Campbell, "Leveraging EA for Project Management in Complex M&A Scenarios," Journal of Information Technology, vol. 33, no. 4, pp. 563-578, 2014.

M. T. Evans and P. M. King, "Enterprise Architecture and Project Management: Challenges and Solutions in M&A Integration," International Journal of Information Systems, vol. 16, no. 1, pp. 55-68, 2013.

J. M. Baker and S. E. Murphy, "Strategic Use of EA and PM for Effective M&A Integration," Journal of Organizational Change Management, vol. 29, no. 7, pp. 1156-1173, 2016.

Downloads

Published

15-03-2022

How to Cite

Mahadu Vinayak Kurkute, Deepak Venkatachalam, and Priya Ranjan Parida. “Enterprise Architecture and Project Management Synergy: Optimizing Post-M&A Integration for Large-Scale Enterprises”. Journal of Science & Technology, vol. 3, no. 2, Mar. 2022, pp. 141-82, https://thesciencebrigade.com/jst/article/view/377.
PlumX Metrics

Plaudit

License Terms

Ownership and Licensing:

Authors of this research paper submitted to the Journal of Science & Technology retain the copyright of their work while granting the journal certain rights. Authors maintain ownership of the copyright and have granted the journal a right of first publication. Simultaneously, authors agreed to license their research papers under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.

License Permissions:

Under the CC BY-NC-SA 4.0 License, others are permitted to share and adapt the work, as long as proper attribution is given to the authors and acknowledgement is made of the initial publication in the Journal of Science & Technology. This license allows for the broad dissemination and utilization of research papers.

Additional Distribution Arrangements:

Authors are free to enter into separate contractual arrangements for the non-exclusive distribution of the journal's published version of the work. This may include posting the work to institutional repositories, publishing it in journals or books, or other forms of dissemination. In such cases, authors are requested to acknowledge the initial publication of the work in the Journal of Science & Technology.

Online Posting:

Authors are encouraged to share their work online, including in institutional repositories, disciplinary repositories, or on their personal websites. This permission applies both prior to and during the submission process to the Journal of Science & Technology. Online sharing enhances the visibility and accessibility of the research papers.

Responsibility and Liability:

Authors are responsible for ensuring that their research papers do not infringe upon the copyright, privacy, or other rights of any third party. The Journal of Science & Technology and The Science Brigade Publishers disclaim any liability or responsibility for any copyright infringement or violation of third-party rights in the research papers.

Loading...