Data Quality
It’s time we had the talk about dirty data.
Every minute of every day in every company, bad things are happening to good data and to confuse the issue, good things are happening to bad data. So many people, departments, systems, and processes are involved in perpetuating poor-quality data that it’s impossible to pin the blame on anyone.
Data quality means the data’s fit for all your intended uses. And since the responsibility for maintaining data can’t be assigned to one person or unit, the problem keeps getting worse. With no quality oversight or data governance process, off it goes into the wide world of business usage, like a balloon released to the summer sky. The problems that poor data quality cause are generally undervalued, because data is so ethereal.
Corrections to data are notoriously difficult to manage, but the cumulative effect of bad data is insidious – and massively expensive. According to Gartner Research, “the average financial impact of poor data quality on organizations is $9.7 million per year.” IBM reported that US businesses lose $3.1 trillion annually due to poor data quality, as noted by Thomas A. Redman in a piece published by HBR. That figure should be setting your hair on fire.
We approach data quality by focusing on name and address data. Why? Because you can append a name and address. Everything is attached to it. And whether or not you’re doing a mailing or creating customer personas or expanding your business services to new markets, without continually tending to your company’s name and address data, you’re perpetuating errors. Everything that goes into a client’s profile is predicated on that person’s name and address. It’s the #1 piece of foundational data. It demands your full attention.
Undeliverable as Addressed (UAA) and return mail is byproduct of bad data.
If you do mailings, take a look at the amount of return mail. That’s a direct result of bad data. Return mail is undeliverable for a variety of reasons, and it means your system hasn’t kept up with the corrections. The problem is, at this stage you can’t “rewind” and fix the errors. Even if you did, where else has that data landed? It’s impossible to put that genie back in the bottle.
Return mail is costing you about $50 per piece. Thanks to bad data quality.
Data is the foundation of all we do. Focusing on data quality means treating your data like the precious asset it is. Through our cloud technology solutions, TEC solves your data quality issues by fixing the source system. We have the structure, the discipline, the expertise, and the bandwidth.
Why CASS Certification matters! The USPS threshold for certification is 98.5% accurate, and we don’t stop there. Our standards exceed this minimum threshold which results in, for many clients a seven-figure delta in terms of postage dollar savings!
So while you can’t outsource your data quality problem, you can outsource the responsibility of making sure your data does not deteriorate over time.