Master Data Management and business intelligence

Hervé Chapron at Semarchy explains how Master Data Management is democratising business intelligence

 

When discussing data management and business intelligence (BI), we can draw a compelling parallel to the construction and maintenance of a house. Imagine your organisation’s ecosystem as a grand, multifaceted home. In this analogy, Master Data Management (MDM) serves as the foundation and framework, providing the essential structure upon which everything else is built.

 

Just as a house requires a solid foundation to withstand the test of time, a robust MDM system ensures that your data architecture is consistent and capable of supporting your evolving business needs.

 

Then, the quality of your data is akin to the building materials used in constructing the house. High-quality, consistent data is like using premium materials - it ensures reliability and longevity.

 

Poor quality data, however, is comparable to using cheap materials, leading to structural issues, risks and costly repairs down the line. The various rooms within the house represent different departments or functional teams in your organisation, each with its specific purpose and needs, yet all interconnected and part of the same structure.

 

In this “data house” that we are building, BI tools and processes are the utilities and appliances. They’re essential for making the house functional and comfortable, transforming raw materials into usable, valuable assets. However, even the most advanced appliances can’t compensate for a weak foundation or poor building materials.

 

By investing in a strong MDM foundation and maintaining high-quality data, organisations can build a robust "data house" that not only sustains day-to-day difficulties, but also provides a reliable and valuable environment for generating business insights and driving strategic decisions. Yet only 25% of data professionals believe their organisation’s decision-making is data-driven. MDM plays a crucial role in addressing this problem.  

 

Why MDM matters

MDM comprises a comprehensive framework of processes, policies, and technologies designed to oversee and control an organisation’s critical data assets. These assets include information about customers, products, suppliers, employees, geographical locations, and more.

 

Often referred to as master data, these resources are essential to the organisation’s daily operations and strategic decision-making. However, without proper management and governance, master data can quickly become fragmented, inconsistent, and unreliable.

 

The primary objective of MDM is to create, maintain, and ensure the availability of a centralised, structured, accurate, authoritative, and consistent source of master data across multiple systems and applications. Doing so addresses and eliminates data inconsistencies and redundancies throughout the organisation.

 

Your data is your best asset as a business, and bringing back our data house metaphor, ensuring it is of the highest and best quality is extremely important for future decision-making. Without managing this asset, you could be letting great value pass you by. 

 

The benefits of business intelligence

Business efficiencies are significantly improved when BI is part of the ongoing strategy. Because of the reliable and accurate data set that is being used across the business, certain tasks can be automated to free up team time, such as report generation.

 

This use case highlights how other technologies, such as generative AI, can be integrated into a business’s operations seamlessly, but only when there is a strong data foundation in place.

 

Moreover, it gives businesses better insights into their internal practices. For example, better data can highlight a clear customer behaviour pathway and show where the business might be losing customers more frequently, therefore helping to allocate resources in the best possible places.

 

Improved BI can also help with tracking the market more closely and giving businesses the competitive advantage to react quickly and efficiently to relevant trends, demonstrating to customers and investors that you have your finger on the pulse. 

 

Data intelligence drives better BI

As mentioned, MDM is the basis for better decision making. By having a source of truth for your data, your business can trust the results and insights it delivers.

 

As a result, decision making can become truly data-driven, allowing for greater BI. Within this, data intelligence is extremely important to consider. This refers to the practice of treating your business data as a critical business asset; without it, no well-rounded decision making is going to happen.

 

Additionally, data intelligence also pushes businesses to answer more pointed questions: what is the purpose of our data? What justification do we have for retaining it? Seeking answers to these questions enhances operational efficiency and supports numerous data intelligence applications, such as data governance and facilitating self-service analytics, among others.

 

Best practice example: AI

By having well-managed data, you open your business up to many new opportunities. The widespread application of artificial intelligence (AI) across various sectors highlights the need for having the best data possible. Your data intelligence provides the high-quality, comprehensive data needed to build AI systems that can be trusted.

 

Clean, cohesive, and well-governed data is essential to effectively train AI models and ensure their outputs are reliable and free from bias. Otherwise, AI could yield flawed outcomes, leading to poor decisions and diminishing trust in AI capabilities. 

 

It’s also important because AI models need to be able to explain their reasoning and decision-making processes, especially in high-stakes environments like healthcare, finance, or government.

 

Without transparency and explainability, AI runs the risk of being a "black box" that makes decisions without any understandable logic or justification. Data intelligence helps provide the high-quality data and data governance needed to build trustworthy, explainable AI that businesses and wider society can have confidence in.

 

An example could involve using data intelligence to integrate and govern data from various sources in the financial services industry, such as transaction records, market data, and customer information.

 

This comprehensive and well-governed data can then train AI models to detect fraudulent activities, assess credit risks, or provide personalised investment advice while being able to explain the rationale behind their predictions or recommendations.

 

MDM and BI: a perfect fit

MDM ensures data integrity, consistency, and alignment across systems, creating a reliable foundation for accurate information. BI and data intelligence tools then leverage this framework to generate actionable insights that guide quick and informed decision-making. 

 

Additionally, BI provides deeper insights into customer behaviour, operations, and market trends, enabling organisations to remain agile and refine processes continuously. Often, companies leveraging BI see superior financial performance, as decisions informed by accurate data regularly result in optimised outcomes, outperforming competitors who rely on traditional methods. 

 

When combined, MDM and BI form a powerful synergy, generating valuable insights and driving positive business results.

 

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Hervé Chapron is SVP Global Sales, GM EMEA for Semarchy

 

Main image courtesy of iStockPhoto.com and Khanchit Khirisutchalual