Data Improvement Prioritization Analysis
EN Engineering was contracted to evaluate and prioritize improving different data components within the client’s data system.
This client had numerous business drivers for improving their data system, from regulatory changes to internal goals and initiatives. These, along with the multitude of possible data components to be improved upon, needed to be analyzed to determine the priority of improvements. Once this had been done, the client could plan improvement projects, beginning with those that would have the greatest impact.
We worked with our client to identify the importance of different factors and develop the prioritization analysis. The most important factors were the business drivers that required complete and accurate data. Our team then quantified the importance of each data component and evaluated the current state of the data. This analysis numerically evaluated the risk associated with incomplete data components based on its current format, quality, reliability, and criticality.
Knowing the priority ranking of each data component helped our client to determine which data initiatives to engage in first. The higher-ranked data components represented those components with the most risk to the system should they not be fully updated or integrated. As the ranking emphasized the criticality of the data component, higher-ranking components were also important to multiple business drivers.