Master Data Management’s Direct Impact on Enterprises' Top and Bottom Line

Aug 03, 2023

Data Analytics & Transformation Services | 2 min READ

In today’s data-driven business environment, organizations are recognizing the critical role that core data plays in both business efficiency and business success. Master Data Management (MDM refers to the processes that enable businesses to manage their core master data – like products that they sell, customers, suppliers, employees, locations etc.).

While organization leaders understand the benefits of MDM through improvement in Data accuracy, they often struggle to provide direct ROI. MDM programs are often considered as indirect to other business transformation objectives. Through this article, we would like to provide some real examples to make understand that MDM can also directly impact a company’s top and bottom line.

This article examines the findings of a survey of a customer and compares the business problems resulting from poor master data, emphasizing the significant impact on revenue and operational efficiency.

Deepak Gupta

Former AVP & Global Practice Head

Data & Analytics | MDM | Data Science | AI

Birlasoft

Sales Impact:

One of the key findings of the study was to highlight the direct impact of bad master data on sales. In cases where the product was not ready for shipment due to errors in product design, recipes, bills of materials (BOMs), or inventory; the loss of revenue was up to 0.33%. Such errors can lead to late or incorrect delivery, dissatisfied customers, and lost sales opportunities. By managing and improving key data, organizations can mitigate these issues and increase customer satisfaction and sales performance.

The study also found that inadequate quality master data significantly impacts profitability. Errors due to waste, rework, and packaging, resulting from incorrect or inconsistent master data, contribute to approximately 0.2% profit impact on revenue. These inefficiencies add to cost rise, reduced efficiency, and lower product quality. By implementing robust MDM practices, organizations can reduce waste, improve resource allocation, and increase overall profitability.

Cash Flow Impact:

Inaccurate customer or product master data can significantly affect an organization’s cash flow. The study highlights that the delays in customer payments (caused by incorrect information) have a cash flow impact of about 0.47% of revenue Invoices. The incorrect information results in delayed payments and cash flow disruptions. An effective MDM ensures accurate customer and product information, enabling accurate billing and timely payments, thus improving cash flow.

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Full Business Story:

The study estimated that around 1% of revenue is at risk, considering the cumulative impact on sales, profitability, and cash flow data, due to bad master data. This figure is of critical importance, emphasizing that key data quality issues should be addressed within an organization. By implementing incremental improvements in key data, companies can mitigate these issues and aim to reduce revenue losses by about up to 0.5%.

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The role of Master Data governance and mature reporting:

While improving core data is important, it is equally important to put mature Master Data governance and reporting systems in place. Organizations can track, measure, and continuously improve their MDM processes. Mature governance ensures accountability, data management and adherence to data quality standards. Robust reporting strategies provide visibility into data quality metrics, issue resolution progress, and impacts the overall revenue. With robust governance structures and comprehensive reporting, organizations can drive continuous improvement in the quality of key data and maximize revenue.

The study findings clearly indicate that MDM has a direct impact on an organization’s cash flow. The sales, profitability, and financial implications of bad master data underlines the need – that organizations prioritize and invest in robust MDM practices and implement mature governance and reporting strategies using key data.

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