Episode 6: How to Break the Cycle of Bad Data
Today’s subject is very near and dear to my heart – taking out the garbage & cleaning up your data! I’ve spent my entire career in small business. And I’ve seen some pretty scary stuff when it comes to data quality.
At one company, I found almost $100k that they had paid to vendors for products that had never been received! All because they never reviewed open purchase orders!
At another company, I saw delays of two to four weeks in sending invoices to customers because paperwork couldn’t be located to verify the weights of products shipped! Many of these invoices were over $50k each! To make it worse, their customers typically paid 30 days late!
I’ve seen inventory count discrepancies of over $250k in a single month because data wasn’t entered into the system correctly. These kinds of mistakes can bankrupt a business. And yet they happen every day. Even on a smaller scale, data mistakes can cost tens of thousands of dollars over time.
But if it’s so costly, why does this happen? In this episode, I share three common causes of poor data quality and my six step process to clean up your data and implement strong systems to grow.
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