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Optimizing CRM-Based Sales Pipelines: A Business Process Reengineering Model
Subject area: Science,Engineering and Technology · Area of research: CRM-Based Sales Pipelines
Abstract
In today?s hypercompetitive business environment, organizations are increasingly turning to Customer Relationship Management (CRM) systems to streamline and enhance their sales processes. However, many CRM implementations fail to deliver expected results due to fragmented workflows and legacy process constraints. This paper presents a comprehensive review of CRM-enabled sales pipeline optimization through the lens of Business Process Reengineering (BPR). By synthesizing findings from academic literature, industry reports, and case studies, the paper proposes a BPR-driven model that restructures key sales pipeline stages?from lead generation to customer retention?for greater agility, visibility, and performance. Emphasis is placed on eliminating redundancy, automating decision-making, integrating real-time analytics, and aligning CRM workflows with business objectives. The paper also explores critical success factors, challenges, and digital enablers such as AI, predictive analytics, and cloud-based CRM platforms. The review concludes by offering a strategic framework to guide organizations in redesigning their CRM-based sales pipelines to improve revenue conversion and customer engagement in a data-driven economy.
Keywords
Customer Relationship Management (CRM), Business Process Reengineering (BPR), Sales Pipeline Optimization, Workflow Automation, Digital Transformation, Customer Lifecycle Management.
References
[1] Abiola Olayinka Adams, Nwani, S., Abiola-Adams, O., Otokiti, B.O. & Ogeawuchi, J.C., 2020.Building Operational Readiness Assessment Models for Micro, Small, and Medium Enterprises Seeking Government-Backed Financing. Journal of Frontiers in Multidisciplinary Research, 1(1), pp.38-43. DOI: 10.54660/IJFMR.2020.1.1.38-43.
[2] Adenuga, T., Ayobami, A.T. & Okolo, F.C., 2019. Laying the Groundwork for Predictive Workforce Planning Through Strategic Data Analytics and Talent Modeling. IRE Journals, 3(3), pp.159–161. ISSN: 2456-8880.
[3] Adenuga, T., Ayobami, A.T. & Okolo, F.C., 2020. AI-Driven Workforce Forecasting for Peak Planning and Disruption Resilience in Global Logistics and Supply Networks. International Journal of Multidisciplinary Research and Growth Evaluation, 2(2), pp.71–87. Available at: https://doi.org/10.54660/.IJMRGE.2020.1.2.71-87.
[4] Adewoyin, M.A., Ogunnowo, E.O., Fiemotongha, J.E., Igunma, T.O. & Adeleke, A.K., 2020.A Conceptual Framework for Dynamic Mechanical Analysis in High-Performance Material Selection. IRE Journals, 4(5), pp.137–144.
[5] Adewoyin, M.A., Ogunnowo, E.O., Fiemotongha, J.E., Igunma, T.O. & Adeleke, A.K., 2020.Advances in Thermofluid Simulation for Heat Transfer Optimization in Compact Mechanical Devices. IRE Journals, 4(6), pp.116–124.
[6] Adewuyi, A., Oladuji, T.J., Ajuwon, A. & Nwangele, C.R. (2020) ‘A Conceptual Framework for Financial Inclusion in Emerging Economies: Leveraging AI to Expand Access to Credit’, IRE Journals, 4(1), pp. 222–236. ISSN: 2456-8880.
[7] Ajuwon, A., Onifade, O., Oladuji, T.J. & Akintobi, A.O. (2020) ‘Blockchain-Based Models for Credit and Loan System Automation in Financial Institutions’, IRE Journals, 3(10), pp. 364–381. ISSN: 2456-8880.
[8] Akinbola, O. A., Otokiti, B. O., Akinbola, O. S., & Sanni, S. A. (2020). Nexus of Born Global Entrepreneurship Firms and Economic Development in Nigeria. Ekonomicko-manazerske spektrum, 14(1), 52-64.
[9] Akpe, O. E. E., Mgbame, A. C., Ogbuefi, E., Abayomi, A. A., & Adeyelu, O. O. (2020). Bridging the business intelligence gap in small enterprises: A conceptual framework for scalable adoption. IRE Journals, 4(2), 159–161.
[10] Akpe, O.E., Mgbame, A.C., Ogbuefi, E., Abayomi, A.A. & Adeyelu, O.O., 2020.Barriers and Enablers of BI Tool Implementation in Underserved SME Communities. IRE Journals, 3(7), pp.211-220. DOI: .
[11] Akpe, O.E., Mgbame, A.C., Ogbuefi, E., Abayomi, A.A. & Adeyelu, O.O., 2020. Bridging the Business Intelligence Gap in Small Enterprises: A Conceptual Framework for Scalable Adoption. IRE Journals, 4(2), pp.159-168. DOI:
[12] Akpe, O.E., Ogeawuchi, J.C., Abayomi, A.A., Agboola, O.A. & Ogbuefis, E. (2020) 'A Conceptual Framework for Strategic Business Planning in Digitally Transformed Organizations', IRE Journals, 4(4), pp. 207-214.
[13] Ashiedu, B.I., Ogbuefi, E., Nwabekee, U.S., Ogeawuchi, J.C. & Abayomis, A.A. (2020) 'Developing Financial Due Diligence Frameworks for Mergers and Acquisitions in Emerging Telecom Markets', IRE Journals, 4(1), pp. 1-8.
[14] Fagbore, O.O., Ogeawuchi, J.C., Ilori, O., Isibor, N.J., Odetunde, A. & Adekunle, B.I. (2020) 'Developing a Conceptual Framework for Financial Data Validation in Private Equity Fund Operations', IRE Journals, 4(5), pp. 1-136.
[15] Mgbame, A. C., Akpe, O. E. E., Abayomi, A. A., Ogbuefi, E., & Adeyelu, O. O. (2020). Barriers and enablers of BI tool implementation in underserved SME communities. IRE Journals, 3(7), 211–213.
[16] Nwani, S., Abiola-Adams, O., Otokiti, B.O. & Ogeawuchi, J.C., 2020.Designing Inclusive and Scalable Credit Delivery Systems Using AI-Powered Lending Models for Underserved Markets. IRE Journals, 4(1), pp.212-214. DOI: 10.34293 /irejournals.v 4i1.1708888.
[17] ODOFIN, O. T., ABAYOMI, A. A., & CHUKWUEMEKE, A. (2020). Developing Microservices Architecture Models for Modularization and Scalability in Enterprise Systems.
[18] Odofin, O.T., Agboola, O.A., Ogbuefi, E., Ogeawuchi, J.C., Adanigbo, O.S. & Gbenle, T.P. (2020) 'Conceptual Framework for Unified Payment Integration in Multi-Bank Financial Ecosystems', IRE Journals, 3(12), pp. 1-13.
[19] Ogunnowo, E.O., Adewoyin, M.A., Fiemotongha, J.E., Igunma, T.O. & Adeleke, A.K., 2020.Systematic Review of Non-Destructive Testing Methods for Predictive Failure Analysis in Mechanical Systems. IRE Journals, 4(4), pp.207–215.
[20] Olufemi-Phillips, A. Q., Ofodile, O. C., Toromade, A. S., Eyo-Udo, N. L., & Adewale, T. T. (2020). Optimizing FMCG supply chain management with IoT and cloud computing integration. International Journal of Managemeijignt & Entrepreneurship Research, 6(11), 1-15.
[21] Omisola, J. O., Etukudoh, E. A., Okenwa, O. K., & Tokunbo, G. I. (2020). Innovating Project Delivery and Piping Design for Sustainability in the Oil and Gas Industry: A Conceptual Framework. perception, 24, 28-35.
[22] Omisola, J. O., Etukudoh, E. A., Okenwa, O. K., & Tokunbo, G. I. (2020). Geosteering Real-Time Geosteering Optimization Using Deep Learning Algorithms Integration of Deep Reinforcement Learning in Real-time Well Trajectory Adjustment to Maximize. Unknown Journal.
[23] Osho, G. O., Omisola, J. O., & Shiyanbola, J. O. (2020). A Conceptual Framework for AI-Driven Predictive Optimization in Industrial Engineering: Leveraging Machine Learning for Smart Manufacturing Decisions. Unknown Journal.
[24] Osho, G. O., Omisola, J. O., & Shiyanbola, J. O. (2020). An Integrated AI-Power BI Model for Real-Time Supply Chain Visibility and Forecasting: A Data-Intelligence Approach to Operational Excellence. Unknown Journal.
[25] Oyedokun, O.O., 2019.Green Human Resource Management Practices (GHRM) and Its Effect on Sustainable Competitive Edge in the Nigerian Manufacturing Industry: A Study of Dangote Nigeria Plc. MBA Dissertation, Dublin Business School.
[26] Sharma, A., Adekunle, B.I., Ogeawuchi, J.C., Abayomi, A.A. & Onifade, O. (2019) 'IoT-enabled Predictive Maintenance for Mechanical Systems: Innovations in Real-time Monitoring and Operational Excellence', IRE Journals, 2(12), pp. 1-10.
How to cite this paper
@article{1709615,
author = {Chikaome Chimara Imediegwu, Okeoghene Elebe},
title = {Optimizing CRM-Based Sales Pipelines: A Business Process Reengineering Model},
journal = {Iconic Research And Engineering Journals},
year = {2020},
volume = {4},
number = {6},
pages = {232-245},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1709615.pdf},
abstract = {In today?s hypercompetitive business environment, organizations are increasingly turning to Customer Relationship Management (CRM) systems to streamline and enhance their sales processes. However, many CRM implementations fail to deliver expected results due to fragmented workflows and legacy process constraints. This paper presents a comprehensive review of CRM-enabled sales pipeline optimization through the lens of Business Process Reengineering (BPR). By synthesizing findings from academic literature, industry reports, and case studies, the paper proposes a BPR-driven model that restructures key sales pipeline stages?from lead generation to customer retention?for greater agility, visibility, and performance. Emphasis is placed on eliminating redundancy, automating decision-making, integrating real-time analytics, and aligning CRM workflows with business objectives. The paper also explores critical success factors, challenges, and digital enablers such as AI, predictive analytics, and cloud-based CRM platforms. The review concludes by offering a strategic framework to guide organizations in redesigning their CRM-based sales pipelines to improve revenue conversion and customer engagement in a data-driven economy.},
keywords = {Customer Relationship Management (CRM), Business Process Reengineering (BPR), Sales Pipeline Optimization, Workflow Automation, Digital Transformation, Customer Lifecycle Management.},
month = {December},
}