Break out of the data quality trap

“Our data quality isn’t good enough” is a comment we often hear. Here’s the reality: We have yet to find an organization with perfect data. More importantly, we have never found an organization with data is so poor that it has been impossible to gain actionable insights. 

Don’t seek perfection. Your data is good enough. You have to start somewhere; if you don’t, you’ll never be able to move forward.

We’re not advocating recklessness. We know that your credibility is at risk if there are errors or inconsistencies hidden in your dataset. But the key word is hidden. It’s estimated – by the European Spreadsheet Risks Interest Group – that 94% of spreadsheets contain errors which remain hidden. The tightrope of credibility is routinely being walked! It doesn’t have to be this way. 

If you don’t have accurate data, get the insight you can from the data you have: Limit your analysis to exclude problematic cases and be explicit that initial observations are based on partial data. When there is transparency on how data quality issues are limiting insight, you are much better equipped to build momentum for issues to be addressed.

Related articles:

• The impact of common data quality issues
• Six-Step Data Cleaning Process