Part 1 of our 3 part Data Integrity Series
In Harvard Business Review’s The 4 Mistakes Most Managers Make with Analytics, two professors comment on issues that many face with their data: 1) Not understanding integration issues; 2) Not realizing the limits of unstructured data; 3) Assuming correlations mean something and 4) Underestimating the labor skills necessary. We have been at this for more than 27 years now and we fully concur with their findings. However, we would further add that there are three additional issues that can lead your executive team down a wobbly path: incomplete data, poor data quality, and siloed systems spanning an enterprise. As we all know, increased data integrity—the degree of completeness, quality and integration—results in better information for driving key decisions. But with many hands, minds and systems in the pot, how do we efficiently strengthen the quality of our data? This is a three part blog that walks you through practical tips for achieving data integrity.
Step 1: Identifying missing data
If you’ve ever heard the phrase, “you don’t know what you don’t know,” then you know what we are talking about. You can request report after report and make decision after decision without missing a beat. Until you realize that your decision didn’t account for the 300 additional data points that would have swung you in the opposite direction. To avoid this, try analyzing trends or visualizing key metrics. Software like Tableau enables you to easily visualize your data. With visibility into what you have, quality issues typically emerge – are there gaps and/or data inconsistencies that will prevent you from informed decision making? If you have questions about your data or suspect that there are issues with your data gathering process, we are happy to have one of our statisticians talk to you.
It’s completely natural to face data integrity challenges. Recognizing the issue is half the battle, and breaking down the work to remedy the situation into manageable pieces is the other half. Data is a critical organizational asset; the health of which is dependent upon multiple departments and people across your organization.
Stay tuned for our next blog on Data Integrity: Building a Culture of Quality Data.