Do you trust your data? Would you bet your business on it?
Our customers give us invaluable feedback on what they want and need. Their voices are important, because without their information, we can’t be sure if we can solve their problems.
One major concern they share is the quality of the data itself. Because without confidence in the data, organizations risk losing significant revenue opportunities and reduced operational efficiency. Small data errors can lead to huge revenue losses, which can easily escalate into existential threats.
For example, one of our prospective customers uses a data aggregation tool. However, they discovered that the tool they were using was off by 150 impressions. When they gave this feedback to the aggregator, the response was, “it’s only 150 impressions - that’s not that bad.”
Yes, it is that bad. Here’s why.
For one thing, if your data is off by even a small percentage, you could be undercharging or underselling, thus leaving real money on the table. For another, 150 impressions here and 150 impressions there can add up very quickly.
But, there is a bigger threat here. And that has to do with trusting your data.
If you don’t trust one aspect of your data, you will likely end up questioning all of the data across the enterprise. If your entire enterprise no longer has confidence in your data, you are back to guesswork. And guessing could easily become fatal in the current landscape, especially for data-driven organizations. Suddenly, your strategic advantage - data - becomes a huge liability.
If you are a mid-sized business, one bad quarter can take you out of the game. And a couple of bad quarters in an off year could sink your business, and possibly your career. You might think larger enterprises can take a small hit here and there. But can they really? These larger enterprises will likely get even more inaccurate data - much more than “just 150 impressions'' - and thus make even larger-scale mistakes.
Again, if these enterprises don’t trust their data, how long can they keep guessing before they feel the pinch?
The fact is, you need to trust your data. It has to be 100% right, 100% of the time. In my next post, I’ll discuss how to build the foundations of a good data strategy to avoid this issue. Meanwhile, I would suggest you scrub through your data to make sure you are getting clean, accurate information to ensure you are making the right decisions, starting today.
Be Data Strong!
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Learn why a publicly-traded media conglomerate said, “We had previously invested over eight months of engineering to overcome a data challenge that took Switchboard one month to solve.” Email me to learn more: firstname.lastname@example.org.