Business Process Reengineering Using CRM Workflow Automation

  • Authors

    • Satyendra Kumar Vanapalli Consultant, Technical Solutions at Visa Inc, USA. Author

    DOI:

    https://doi.org/10.67228/30715725/IJIARE-2024PII2A3K

    Published 10-08-2024

  • Business Process Reengineering (BPR), CRM Workflow Automation, Digital Transformation, Process Optimization, Customer Experience, Automation Technologies, Enterprise Systems

    Issue

    Section

    Articles

    How to Cite

    [1]
    S. K. Vanapalli, “Business Process Reengineering Using CRM Workflow Automation”, IJIARE, vol. 7, no. 2, pp. 01–17, Oct. 2024, doi: 10.67228/30715725/IJIARE-2024PII2A3K.
  • Abstract

    Business Process Reengineering (BPR) was and still is considered by many as a very effective way of fundamentally rethinking and redesigning organizational processes so that dramatic improvements in performance, cost, quality, and service delivery are achieved. Nowadays, through the help of digital tools, the concept of Customer Relationship Management (CRM) workflow automation has greatly enhanced the capabilities of BPR by helping companies to better operate, minimizing the need for manual work and making customer-related decision-making more direct and less time-consuming. This paper investigates the role of CRM workflow automation in initiating change at the level of business processes that are not only agile but also ones that are run on data and can respond rapidly. The main goal of this paper is to assess how useful the CRM-enabled automation is in terms of reengineering the main business workflows, raising operational efficiency, and delivering superior customer experiences. As a way of reaching the goal, the study follows a mixed-method strategy by starting with a literature review, followed by conceptual modeling, and ending up with case-based analysis of the situations of CRM implementations in the enterprises that are the environments. The results point out that companies that make use of CRM workflow automation experience a great deal of process cycle time reductions, not only because their data is more accurate but also because of their better coordination among departments. At the same time, the number of customers who are happy has also increased. Besides, the paper discusses the ways in which automation makes it possible to provide up-to-the-minute analytics as well as continuous process improvements, which are the two factors necessary for staying ahead. In this study, a dual role has been assigned to the delivered outputs, firstly to the academia, such as the development of an explicit outline that merges the principles of BPR with those of the modern technologies of CRM and secondly to the practitioners.

  • References

    [1] Imediegwu, CHIKAOME CHIMARA, and O. K. E. O. G. H. E. N. E. Elebe. "Optimizing CRM-based sales pipelines: A business process reengineering model." IRE Journals, December 4.6 (2020).

    [2] Aversano, Lerina, et al. "Business process reengineering and workflow automation: a technology transfer experience." Journal of Systems and Software 63.1 (2002): 29-44.

    [3] Takkalapally, D. (2023). HoloSearchAI: AI-Driven Latency Optimization Framework for Distributed Search Systems. International Journal of Emerging Trends in Computer Science and Information Technology, 4(3), 217-227. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I3P122.

    [4] Yahaya, Jamaiah H., Syafrani Fithri, and Aziz Deraman. "An enhanced workflow reengineering methodology for SMEs." International Journal of Digital Information and Wireless Communications (IJDIWC) 2.1 (2012): 51-65.

    [5] Allenki, S. S. (2023). Reducing Security Vulnerabilities with Encryption, IAM, and Regular Audits. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 265-275. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P127.

    [6] Harmon, Paul. Business process change: a manager's guide to improving, redesigning, and automating processes. Morgan Kaufmann, 2003.

    [7] Topala, P., and V. Postolache. "Re-engineering of business processes as a bank efficiency method." IOP Conference Series: Materials Science and Engineering. Vol. 400. No. 6. IOP Publishing, 2018.

    [8] Srigadde BR. The Hidden Gem: Lightning Headless Component. IJETCSIT [Internet]. 2023 Mar. 30 [cited 2026 Aug. 7];4(1):244-5. Available from: https://ijetcsit.org/index.php/ijetcsit/article/view/731.

    9. Mohapatra, Sanjay. Business process reengineering: automation decision points in process reengineering. Springer Science & Business Media, 2012.

    [9] Kumar Doodala, A. N., Thatraju, S., & Kankanala, V. (2023). Post- Pandemic QA evolution in Healthcare IT. International Journal of Emerging Trends in Computer Science and Information Technology, 4(2), 223-232. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I2P122.

    [10] Shiramalla, R. (2022). Predictive Record Assignment Engine in Salesforce using LWC and Einstein AI. International Journal of AI, BigData, Computational and Management Studies, 3(3), 147-159. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I3P117.

    [11] Samaranayake, Premaratne. "Business process integration, automation, and optimization in ERP: Integrated approach using enhanced process models." Business Process Management Journal 15.4 (2009): 504-526.

    [12] Takkalapally, D., & Takkellapally, M. R. (2023). GC-TuneHFT: AI-Based Garbage Collection Optimization in High-Frequency Trading Environments. American International Journal of Computer Science and Technology, 5(6), 25-37. https://doi.org/10.63282/3117-5481/AIJCST-V5I6P103.

    [13] Muchairi, Alfred. Business process reengineering for process optimization: a case study. Diss. University of Johannesburg, 2022.

    [14] Muppaneni, R. K. (2023). Low-Code Revolution: How Power Platform Extends Dynamics 365 Capabilities. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(3), 162-171. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I3P119.

    [15] Srigadde, B. R. (2023). Creating Object Quick Actions with Lightning Web Components. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 167-180. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P118.

    [16] Bitzer, Sharon M. "Workflow Reengineering: A Methodology for Business Process Reengineering with Workflow Management Technology." (1995).

    [17] Allenki, S. S. (2023). Applying Cloud Security Best Practices in Regulated Environments. American International Journal of Computer Science and Technology, 5(3), 48-60. https://doi.org/10.63282/3117-5481/AIJCST-V5I3P105.

    [18] Parakala, A. (2023). Citizen-Facing Automation: Chatbots and Self-Service in Public Services. International Journal of AI, BigData, Computational and Management Studies, 4(4), 108-118. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I4P112.

    [19] Vppalapati, M., & Talasila, P. K. . (2023). Unobservable Performance: Storage Failures That Leave No Metrics Behind. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(4), 177-188. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P120.

    [20] Muppaneni, K., & Vejella, M. (2023). Security and Data Privacy in Redux Stores. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(4), 153-162. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P117.

    [21] Watson, Edward F., and Karyn Holmes. "Business process automation." Springer Handbook of Automation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. 1597-1612.

    [22] Shiramalla, R. (2023). Optimizing Cross-Platform Enterprise Integrations Using Workato: A Case Study of Salesforce and Oracle SaaS Applications. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 232-243. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P124.

    [23] Ezeh, Michael Osinakachukwu, Adindu Donatus Ogbu, and Augusta Heavens. "The role of business process analysis and re-engineering in enhancing energy sector efficiency." International Journal of Engineering Research and Development 20.8 (2023): 140-151.

    [24] Suryadevara, S. S. K., & Nakirikanti, S. (2024). Blockchain-Backed Content Authenticity Verification Framework. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(1), 242-252. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I1P125.

    [25] Bayomy, Noha Ahmed, Ayman E. Khedr, and Laila A. Abd-Elmegid. "Adaptive model to support business process reengineering." PeerJ Computer Science 7 (2021): e505.

    [26] Vppalapati, M. (2023). When Identity Decisions Throttle Data Movement. International Journal of Emerging Research in Engineering and Technology, 4(3), 160-170. https://doi.org/10.63282/3050-922X.IJERET-V4I3P117.

    [27] Gaddam, R. R. (2023). Progressive Delivery for Models with Quality KPIs. American International Journal of Computer Science and Technology, 5(4), 33-47. https://doi.org/10.63282/3117-5481/AIJCST-V5I4P104.

    [28] Stelling, Mark. "Automated Cost and Customer Based Business Process Reengineering in the Service Sector." (2008).

    [29] Parakala, A. (2023). Vendor Highlights – IoT, AI, and Process Mining. International Journal of Emerging Trends in Computer Science and Information Technology, 4(4), 135-146. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I4P115.

    [30] Elhag, Salma, Ebtehaj Alshahrani, and Zainab Alsharif. "An automated experience-based business process reengineer: case study bank call center." Int. J. Sci. Res.(IJSR) 8 (2018): 1868-1871.

    [31] Katangoori, S., & Katangoori, A. (2023). Intelligent ETL Orchestration with Reinforcement Learning and Bayesian Optimization. International Journal of Emerging Research in Engineering and Technology, 4(4), 208-219. https://doi.org/10.63282/3050-922X.IJERET-V4I4P123.

    [32] Melchert, Florian, Robert Winter, and Mario Klesse. "Aligning process automation and business intelligence to support corporate performance management." (2004).

    [33] Veershetty, G. (2023). Risk-adaptive transition and transformation (RATT): A predictive governance framework for SAP cloud migration programs. International Journal of Leading Research Publication, 4(12). https://doi.org/10.70528/IJLRP.v4.i12.2170

    [34] Taluri, R. (2022). Cloud Data Engineering Strategies for Large-Scale Financial Data Integration and Intelligent Corporate Performance Reporting. International Journal of Emerging Research in Engineering and Technology, 3(4), 176-188. https://doi.org/10.63282/3050-922X.IJERET-V3I4P119

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