Importance of Master Data Management (MDM) in Artificial Intelligence (AI)

Abstract

A typical organisation today has a process that spans across multiple entities like Order Procurement, Financials, Customer Relations, Inventory, Supply Chain & Distribution. This indicates critical business data flowing between the entities interwoven together to conclude the business transaction at the end of the day. With the industry shifting its gears towards welcoming Artificial Intelligence it is important to ensure readiness of the data flowing in the system across these entities. In 2023, McKinsey surveyed more than 80 large global organisations to understand their top objectives in maturing their Master Data Management and the report indicated the top four objectives as: Improved customer experience and satisfaction, Revenue growth by presenting better cross-selling and up-selling opportunities, Increased sales productivity or operational efficiency with seamless access to master data and Streamlined reporting (Kayvaun Rowshankish et al., 2024). The importance of clean and relevant data in Artificial Intelligence cannot be stressed enough. The Supervised Learning in Neural Networks & Deep Learning relies on the Labeled Data [Features mapped with Target] for training the model and aiming for high accuracy in prediction. The words predicted in Generative AI (Gen AI) over Generative Pre-trained Transformer (GPT) can rely on the clean business data flowing in the system.

Keywords: Master Data Management (MDM), Artificial Intelligence (AI), Single Source of Truth (SST), Hub and Spoke System, Mastered Data

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