In a recent dialogue with friend and colleague, Joseph Avellino, we wondered if there was a way to simplify the value delivered by effective data governance in an organization. We came away with a few conclusions that we agreed explained the value succinctly:
Data governance is strategic. It is a structured and disciplined approach to how enterprise data are procured, gathered, managed, maintained, consumed, and transformed. And in the digital transformation age, this strategy is directly linked to the effectiveness of the organization in achieving its objectives both short- and long-term. It is not simply a function that can be assigned and implemented and expected to occur without careful design and execution.
Metadata is vital to gaining intelligence about and unique insights into your business. As business systems become less monolithic and more symbiotic, enterprise-specific metadata that characterizes the flow, lineage, and traceability of data within an enterprise ecosystem becomes critical to figuring out how to generate positive network effects within the data ecosystem. This can be quite challenging when the core interaction is compliance-based. However, in industry in general and certainly in life sciences specifically, significant compliance-driven data strategies gain more support and buy-in when they return results to profit centers within the business.
Machine learning (ML) can apply automation with tangible results today. Companies that use intelligent systems to automate data governance design and execution can derive business-centric insights more quickly and effectively, allowing people and organizations to add human intelligence and decision-making where it is most needed.
Clear and applicable use cases provide a clear picture as to why companies need better data governance and intelligence right now. Companies that can articulate how these data governance and intelligence operations mitigate risk, reduce costs, enhance efficiencies and generate revenues will benefit the most from their data governance and intelligence strategies.
I'd like to get your thoughts on how you have defined the value proposition for your latest data governance initiative. In my next post, I will share thoughts on how data lineage helps track the flow and transformation of customer master data throughout an enterprise.
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