Degree

Master of Business Administration

Faculty / School

School of Business Studies (SBS)

Advisor

Dr. Abdul Basad Sheikh, Assistant Professor, Department of Management

Project Coordinator (External)

Mr. Tanveer ur Rehman, Manager Procurement, DP World

Client

DP World

Committee Member 1

Mr. Faisal Jalal, Project Reviewer, Department of Management

Committee Member 2

Dr. Muhammad Shafique, Program Director MBA & Executive MBA, Institute of Business Administration (IBA), Karachi

Project Type

MBA Research Project

Keywords

Procurement Optimization, Intelligent Automation, Business Process xi Reengineering (BPR)

Abstract / Summary

In large organizations, procurement is a key function that ensures smooth operations, cost effectiveness, supplier performance, and governance. DP World's procurement processes are vital to its operations, given its role as a global trade and logistics provider with various business segments and geographic operations. The project was initiated for “Business Process Optimization in Procurement at DP World” to identify inefficiencies in the procurement function and create an intelligent automation solution to benefit the performance of the procurement function. A detailed analysis of DP World’s procurement process was conducted at the start of the study which included the Purchase Requisition (PR) to Purchase Order (PO) lifecycle. Through internal process reviews and meetings with stakeholders, it was identified that the process of procurement was well organized, but a number of activities were still very manual, requiring individual buyer knowledge, and repetitive administration. The major constraint and the issue was found to be the nomination of suppliers in the Request for Quotation (RFQ). It was a manual process which involved buyers searching the Approved Supplier List, selecting suppliers based on experience and putting together shortlists without a data-driven, structured decision process. This resulted in an increased cycle time, inconsistent supplier selections, reduced supplier visibility, and governance risk. The main goal of this project was to create a smart procurement process redesign and optimization. Business Process Reengineering (BPR) was used to analyze the existing process, identify the inefficiencies and identify potential for automation. The project focused primarily on supplier nomination, but also explored the possibilities of smart automation along the entire procurement chain. The identified problem was solved by developing the solution which is an intelligent procurement automation solution with two layers. The first layer was an automation engine built on the back-end using n8n workflow automation platform. This engine automatically suggests suppliers based on the analysis of procurement item categories and a comparison with the price range and delivery history of the approved suppliers. The system produces ranked supplier recommendations which substantially cut the effort in supplier selection. The second layer was a Procurement Management Web App to digitize and manage the entire P to P process. The application seamlessly integrates intelligent supplier recommendations into the RFQ creation process, helping procurement professionals make quicker and better sourcing decisions in a structured and governed process. The proposed solution provides significant operational and strategic returns. Automated supplier nomination saves 60-90 minutes every supplier search and evaluation to less than 5 minutes per RFQ. The solution provides consistency in procurement by facilitating sourcing across and ensuring that the sourcing criteria for suppliers is considered a standard set, thus minimizing reliance on buyer experience. It also enhances governance as it helps to ensure that only approved suppliers are recommended and keeps a full audit trail of procurement decisions. Also, visibility of suppliers enhances competition between suppliers, resulting in cost savings and better supplier performance. A performance evaluation framework was created to evaluate the anticipated impact of the solution from the procurement efficiency, financial performance, supplier management, compliance, and user adoption perspectives. The analysis, based on an annual procurement volume and spending pattern at DP World QICT, shows that there is considerable time savings, better cycle-time, better compliance and more suppliers used. Financial analysis also shows that the solution can create significant value, both in the area of operational efficiency and via improved sourcing competitiveness, albeit with not very high implementation and maintenance costs. It is recommended based on the results of this study that the proposed solution be rolled out in phases with DP World. Some of the priority actions are to integrate the automation engine with Oracle Fusion APIs, automate workflow triggers, improve the quality of supplier master data and conduct pilot deployments with procurement teams. In the medium to long term, further features like supplier performance scoring, real-time pricing intelligence, and advanced analytics should be integrated to further augment and support business procurement decisions. To conclude, this project shows the possibility of intelligent automation to substantially improve the effectiveness of procurement by decreasing the manual load, improving decision quality, augmenting governance and enable scale up of procurement functioning. The proposed framework offers DP World a feasible roadmap that enables modernizing the procurement processes and generate long-term value for the business by using data-driven procurement management.

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Available for download on Thursday, September 27, 2029

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