Data has become a core element of the strategy for every organization. Enterprises need data in real time to succeed, and executive leadership must relentlessly pursue refining it. Executive governance needs to ensure it has the talent, technology infrastructure, automation, and artificial intelligence (AI) to deliver the data to drive success with minimal impediments to progress and speed. Thus, unsurprisingly, data management is a C-suite topic, with 46% of CEOs setting the data objectives.
Yet, there is a disconnect between executives’ perceptions of trust in data and the operational realities. Eighty percent (80%) of executives suggest they trust their organization’s data, but there is a significant delta between trust in data and its usability. When asked what percentage of their data they deem consumable or usable, more than half of the respondents indicated that this level is 60% or less—often significantly less. More than 95% of executives believe their companies would be more competitive, more innovative, and able to make faster decisions if their data quality were two times better, further emphasizing the disconnect.
Senior executives told us that the top reasons for bad data—the delta between perception and operational reality—are data governance and monitoring, suggesting that data management progress is not contingent on procuring more technology or hiring more talent. Respondents pointed to a lack of governance, but a lack of relevant skills was the least of their concerns. They expect more effective data management will enable success. This expectation is further underlined by 46% of respondents stating that a better understanding of the benefits and shortcomings of the respective solutions would be key for more effective data management. Conversely, only 7% cited more skilled staff would drive higher adoption.
Thus, a better usage of data quality solutions can be a crucial lever for more effective data management. By providing out-of-the-box capabilities, including monitoring, parsing, metadata management, and data curation and enrichment, these solutions can help identify, understand, and correct the issues leading to the delta we identified between trust and usable data.
Our research has crystalized four calls to action for enterprise leaders to improve the effectiveness of their data management strategies.
Embrace the data cycle and focus on the strategic value of data by taking a workflow-centric view of operations.
Facilitate the adoption of data management and quality tools by educating users and aligning tools with data management policies.
Drive effective change management by focusing on governance and monitoring to understand the data cycle better.
Enable business outcomes by clearly defining and articulating your objectives for data management.
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