Skip to main content

The Rule of 3: Detection, Analysis and Resolution


Dylan Jones 3 minute read Data quality

Recent Experian Data Quality market research discovered interesting findings in the way large Britsh organisations tackle data quality. The survey focused on: The Rule of 3 - Detection, Analysis and Resolution.

Here are some of the key observations:

1. Widespread data quality strategy adoption -  99% of firms had a data quality strategy. This is an incredibly high statistic and clearly a sign of the times that no organisation can ignore their responsibilities for data given the demand for compliance and the increased performance that data can bring. That said, there are clear warning signs for organisations that are adopting incomplete data quality strategies. For example, the survey found that nearly a third of companies are not including all data domains in this strategy. This will certainly leave them exposed to financial loss and potential compliance failings.

2. Companies are mostly dealing with data quality defects reactively - 78% of companies employ this approach. This should raise alarm bells because a comprehensive data quality strategy should be calling for a much greater focus on proactive and preventative data quality management. As the huge leaps in manufacturing and engineering quality improvement of the last century demonstrate, it’s only when defects are driven out at the source do you truly reap the rewards of quality management.

3. Nearly 50% of companies struggle with analysis the most - This is not surprising because far too many data quality initiatives are localised, departmental initiatives that either lack the right analysis tools or data quality skills to perform the task adequately. Of key importance here is the need to build comprehensive information chains that model the pathways of data across the organisation. You need technology that can model these chains and profile, assess and report on defects found along the pathways. The message from the research is clear, analysing with spreadsheets and other legacy tools is outdated and ineffective.

4. 61% are dissatisfied with their resolution approach - Perhaps the most striking of all the results is that given such a high data quality strategy adoption, such a high figure of respondents were still unhappy with the resolution of their data quality issues. Part of the problem is no doubt caused by 63% of staff employing manual, reactive fixes. Coupled with the detection and analysis difficulties this will no doubt add up to frustrated customers and much longer lead times until discovered faults are finally resolved. Of course, adopting a manual approach means the defects are likely to occur again in future as prevention is of little importance to so many organisations.

In summary, a case of well done for many British organisations who have finally picked up the baton for data quality management but still a great deal more to do across detection, analysis and resolution in order to truly reap the awards that data quality management can bring.

Take a look at the Data Quality Formula  infographic from Experian Data Quality. This infographic demonstrates that without all 3 vital componants, the data quality formula just won't add up.