Data quality is one of the biggest obstacles that organisations encounter daily. In this series of blog posts, we have already explored some of the different causes of poor data quality and how tooling can help solve these issues, but why is this level of focus necessary? Read on for our thoughts on why data quality should be one of the top priorities within your organisation.
Data is the most vital asset in any successful organisation, informing the decisions that are made at every level. It is therefore critical that the data can be trusted. But how can one confidently decide that the data they are intending to use is current, complete, correct and semantically matching their requirement?
It is not just decision making that requires an elevated level of trust in data. Regulatory requirements also require data to be of the highest quality and reliability.
For example, FR Y-14Q regulations utilise stress testing and assessments to evaluate the capability of organisations to weather adverse events. Accurate data is critical to avoid failing these stress tests and potential financial, reputational and strategic consequences. Confidence in these regulatory responses can only be reached by implementing a comprehensive data quality framework, enabling the organisation to move from a reactive, issue resolution approach, to a pro-active, quality by design approach.
Ensuring the quality of data may seem tedious, but current events such as the recent collapse of Silicon Valley Bank have shown the real world need for this level of focus. Financial services organisations were forced to rapidly interrogate their positions, using the data they have collected and curated, to effectively gauge the collateral impact the collapse may have on their businesses. Had they not been able to do so, their organisation may have been significantly weakened, and customers’ investments and trust may have been severely compromised.
Many organisations still struggle to overcome the challenges posed by siloed data architecture and governance, or by a labyrinth of systems making the effective location, assessment and interrogation of data exceedingly difficult. If this sounds like an issue your organisation has faced, or you are interested to hear more about the Holley Holland approach to data quality, please get in touch with Scott Anderson and Steven Whaley.