Master data management (MDM) represents a perennial issue for many organizations that want to establish and maintain a common frame of reference (some use the phrase “single source of truth”) within key organizational data and analytics. For many and for too long, many business leaders view MDM as an “IT thing,” allowing and enabling pursuit of master data objectives in the absence of explicit connection to business value chains and business processes.
In all instances, achieving high quality, high confidence, and ultimately high trust in the most critical data for organizations—customers, products, vendors, charts of account, and similar—is foundational. Master data domains are the “nouns” around which business value chains are organized.
The recognized importance of data increases as more organizations increasingly depend on analytics and their underlying data as fuel powering operational execution. The advent and increasing adoption of data-dependent technologies such as machine learning (ML) and artificial intelligence (AI) further accelerate the overall importance of data and analytics. The need for trusted data is inescapable.
Our data show the high perceived importance of master data and MDM (in 2024 to date, it ranks 23 out of 63 strategic technologies) as well as increasing importance over time. In addition, MDM and the presence of data leadership in organizations correlate positively. Furthermore, data literacy and MDM show clear correlation—relative stasis for organizations at which data literacy stayed the same and positive rates of change in both importance of MDM and data literacy when data literacy increases.
Data leaders need to realize that the promise and value of data and analytics in driving differentiated organizational performance requires achieving sound foundational elements that are mutually reinforcing: data leadership, data literacy—and MDM.
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