How Often Does an Analyst Typically Make Attention to Detail Mistakes?

An analyst or data scientist typically makes 2-4 attention to detail mistakes each year, but it’s possible to make even less. While no analyst is perfect, there are many validation techniques that can severely reduce the likelihood of errors; these include double/triple checking code, files, and presentations, checking for duplication errors, sanity checking work, validating data and insights with prior experience, validating data against other reports and analyses, peer review, creating a checklist, and more! Value Driven Analytics can provide specific, actionable attention-to-detail training for your analytics team that can dramatically decrease the number of errors they make. Watch the video above to learn more about how to lower the risk of attention to detail errors.