Why do we all know GIGO, but not quality in, quality out (QIQO)? It seems like an awfully pessimistic approach to data management that we only talk about the garbage, but not about the quality. Maybe it’s time to live in a world where QIQO is the default?
Quality In, Quality Out
The logic is simple. In a GIGO world, we worry about dirty data. We should be concerned about dirty data, of course, but a philosophy of QIQO would use quality data as a starting point, and assume that we can keep our data of high quality.
With most other things, the default assumption is a clean starting point. A restaurant kitchen has clean as the default, so that when it gets dirty through a meal service, it is then cleaned and restored to default. Shouldn't we take the same approach to data?
After all, that data informs so many of the day-to-day decisions on which our businesses run. And some of the big strategic decisions as well. So why is it reasonable that data should be dirty by default, that GIGO is a way of life?
We all need a QIQO mindset.
Gradient for Data Quality
With Gradient MSP, it’s possible to keep the data in your PSA high quality. Gradient puts you in a QIQO mindset and gives you the tools to stay there.
You know that quality matters. You know that clean data makes for better decisions, and ultimately better outcomes, and not just business outcomes but things like reduced stress, more time off, and a more profitable business. The good stuff.
QIQO is all about having confidence in your decision making, and that’s what Gradient aims to deliver. Quality in, quality out for all MSPs.
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