How Dirty is Your Data?

Every time I hear someone talk about data quality, I’m reminded of something I learned many years ago. Data is everything. It’s the life-blood of most any organization. Data is what drives business forward, what helps organizations better engage with their customers, clients and constituents. The data you report out is only as good as the data you take in. There seems to have been two different schools of thought that have evolved on this subject over the years:

Garbage in, garbage out – An early IBM programmer and instructor named George Fuechsel is generally given credit for coining the term. It is said that he used “garbage in, garbage out” as an easy way of reminding his students that a computer just processes whatever data it is given. The term has expanded way beyond the computer science world and now “garbage in, garbage out” is often used to refer to situations in the non-digital world, where bad decision-making occurs as a result of incomplete or dirty information.

Garbage in, gospel out – This is a slightly newer variation on the same subject, where people tend to believe and trust statistics, and data that are computer generated. The thought here is that if a report has been produced by a computer, it must, inherently be accurate and contain valuable information to base decision-making on. 

In the upcoming webinar Data Quality: Top 5 Ways to Prevent Garbage in, Garbage out, taking place at 11am Central on Thursday, August 11th, I will discuss this very problem with Sviat Lobach, Vice President of Product at Revenue Grid. What you’ll learn from this session:

  • The impact bad data has on organizations – not just poor decision-making, but also the dollar impact on a company’s bottom line.
  • Why most approaches to data management don’t properly address this issue.
  • How automation can improve CRM data quality.
  • The best ways to have clean and complete data in your CRM.

Save your spot today!

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