Unified Product Truth: MDM for Manufacturing Excellence
DOI:
https://doi.org/10.22399/ijcesen.3686Keywords:
Product data management, manufacturing information systems, master data governance, data quality, digital transformationAbstract
This article examines the transformative role of Master Data Management (MDM) in establishing centralized product catalog integration within manufacturing environments. As Industry 4.0 accelerates the proliferation of data across disparate systems, manufacturers face unprecedented challenges in maintaining consistent product information. The article explores how MDM principles establish a "single source of truth" for product data, addressing the unique complexities of manufacturing environments, including complex product hierarchies, intricate supply chains, and regulatory requirements. Through a systematic analysis of implementation methodologies, architectural approaches, integration patterns, and real-world case studies, the article demonstrates how MDM delivers tangible business benefits across manufacturing operations. The findings reveal that effective MDM implementation significantly improves data quality, reduces operational inefficiencies, accelerates product development cycles, enhances cross-system integration, and creates measurable financial value. This comprehensive framework offers manufacturing organizations a strategic approach to product information governance as a foundation for digital transformation success.
References
[1] Renan Bonnard et al., "Big data analytics platform for Industry 4.0 implementation in advanced manufacturing context," ResearchGate, November 2021. https://www.researchgate.net/publication/353769281_Big_dataanalytics_platform_for_Industry_40_implementation_in_advanced_manufacturing_context
[2] Arpit Sharma, "Master Data Management: A Must for Every Organization," ResearchGate, September 2024. https://www.researchgate.net/publication/384604555_Master_Data_Management_A_Must_for_Every_Organization
[3] Mounika Kothapalli, "The Challenges of Data Quality and Data Quality Assessment in the Big Data Era," ResearchGate, April 2023. https://www.researchgate.net/publication/370129565_The_Challenges_of_Data_Quality_and_Data_Quality_Assessment_in_the_Big_Data
[4] Robert Kolowitz & Majid Dadgar, "Data Governance in Manufacturing Organizations," ResearchGate, June 2019. https://www.researchgate.net/publication/334172905_Data_Governance_in_Manufacturing_Organizations
[5] Chun Zhao et al., "Master data management for manufacturing big data: a method of evaluation for data network," ResearchGate, March 2020. https://www.researchgate.net/publication/334493457_Master_data_management_for_manufacturing_big_data_a_method_of_evaluation_for_data_network
[6] Rajeev Dwiwedi & Fatwa Karim, "Critical Success Factors of New Product Development: Evidence from Select Cases," ResearchGate, June 2021. https://www.researchgate.net/publication/352019615_Critical_Success_Factors_of_New_Product_Development_Evidence_from_Select_Cases
[7] Sushil Prabhu Prabhakaran, "Integration Patterns in Unified AI and Cloud Platforms: A Systematic Review of Process Automation Technologies," ResearchGate, December 2024. https://www.researchgate.net/publication/387343271_Integration_Patterns_in_Unified_AI_and_Cloud_Platforms_A_Systematic_Review_of_Process_Automation_Technologies
[8] Ajay Prasantha Kumar, "Semantic Reconciliation Techniques in Multidomain MDM Frameworks for Heterogeneous Data Sources," ResearchGate, May 2025. https://www.researchgate.net/publication/391715662_Semantic_Reconciliation_Techniques_in_Multidomain_MDM_Frameworks_for_Heterogeneous_Data_Sources
[9] Riikka Vilminko Heikkinen & Samuli Pekkola, "Changes in roles, responsibilities and ownership in organizing master data management," ScienceDirect, August 2019. https://www.sciencedirect.com/science/article/abs/pii/S0268401218303529
[10] Reza Dabestani et al., "Exploring the enablers of data-driven business models: A mixed-methods approach," ScienceDirect, April 2025. https://www.sciencedirect.com/science/article/pii/S0040162525000678
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