I think this question poses a false choice. I suggest this because the long term goals are achieved through the incremental wins when you scope your work in doable, clearly defined chunks. In other words, structuring your work into small, manageable interations, as Agile data governance will, helps you not only enable your team to scrum on the work more effectively, but it'll quantify your progress towards those long term goals too. That's why I don't think it's a matter of balancing between two approaches (quick wins versus long term gains). Rather, it's about how you honor the work it takes to achieve the small advancements along the road to your long term goal, all the while measuring your progress towards your destination.

Building on the mentioned strategies, I would advise implementing a phased approach to data governance initiatives to allow for quick wins while establishing a foundation for long-term integrity. Forming a cross-functional data governance committee is crucial for prioritizing projects that balance immediate business needs with data quality objectives. I would add the importance of developing clear data quality metrics and KPIs to track progress and demonstrate value to stakeholders. Additionally, investing in automated data quality tools can provide immediate benefits while supporting long-term goals. Lastly, fostering a data-driven culture through education ensures alignment between short-term actions and long-term strategies.

If I’m torn between short-term wins and long-term data integrity, here’s how I’d balance the two: ?? Prioritise Critical Data: I’d focus on achieving short-term wins in areas that don’t compromise data quality, ensuring that immediate goals are met without sacrificing integrity. ?? Implement Quick Checks: I’d put in place automated validation processes to ensure data accuracy in the short term while maintaining long-term standards. ?? Invest in Scalability: I’d make sure any short-term solutions can be scaled or improved later, setting the stage for long-term data integrity. ?? Communicate the Plan: I’d keep stakeholders informed of how short-term actions support long-term goals to align expectations.

Every change to any system seeks to get the maximum value for each dollar spent within the shortest time possible. The way to effectively manage the balance between short term gains and long term data integrity is through early identification of data quality goals and associated risks, analyze the tradeoffs to what can/will be built and how that effects on the data quality requirements, and document the decisions. Ultimately this needs to be documented explicit informed decisions by the appropriate stakeholders including any residual data quality risks. The business stakeholders and data owners are to be accountable for the decisions made. It may result in a subsequent roadmap of work to help remediate data quality requirements over time.