I was discussing the data quality vendor landscape with a colleague the other day and he drew a very interesting parallel, an analogy about solutions and performance I hadn’t heard before. Frankly, on the surface it was almost comical—but the more I thought about it, the more I realized the significance.

For some reason, too often technology buyers (especially those in procurement) often don’t take the same view of buying technology that they do in so many other decisions they make in their daily lives. They’re tasked to find a solution that does ‘X’ without fully considering the differences. Often electing to make decisions based on ease or cost, and not results. To be fair vendor solutions do often sound a lot alike, but of course, the reality is very different.

Now, I could spew off a bunch of statistics and percentages that try to convey how important it is to maximize match rates and provide you impact figures around a single customer view, but this isn’t that kind of story.

Picture yourself in this situation… You buy an airline ticket from NY to LA for a wedding on a weekend. You depart on time, but when you land you find that you’ve arrived in Reno Nevada—Not LA! Certainly not your intended destination. You then come to learn that the plane you boarded was incapable of making the full distance from NY to LA.

Are you happy? It’s a silly question and almost comical—with a profoundly obvious answer, because what would be the point?

What if the airline refunded your entire cost for the ticket? Are you satisfied? Have they made you whole?

Take a step back, and think about it. If you think the issue is about the flight, you’d be forgetting the real point. You didn’t buy a flight because you needed a ticket, and you didn’t buy it because you wanted to go to LA. You bought the ticket because you wanted to attend your best friends wedding!

Just as the travel was about being at your best friends wedding—data quality is a function of a bigger picture. Data quality is about protecting and measuring business decisions and creating insights. 90% accurate or some other number less than 100% is simply not going to get you where you need to be. If you’re dealing with customer data you have to realize every record is as critical. It’s as critical as every mile in your travel.

“Every single” record is important. Skimping on data matching accuracy and failing to reach your destination in the name of budget or the effort of changing vendors is as silly as flying to LA and landing in Reno—and being happy with that!

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