Today’s businesses depend on data to survive. It’s used to better understand your customers, project sales, invent new solutions, and even keep an eye on your competitors. But what happens when that data isn’t reliable? There are several events and circumstances that can make your data less accurate, less organized, or even entirely unavailable.
Fortunately, most of these scenarios are preventable, in part because most of them are attributable to human error. Learning to spot and avoid these mistakes can keep your data cleaner.
Managing The Flaws
No system is perfect. Inherently, any system you use to collect, organize, or manage data is going to have flaws, and naturally, your employees are going to have flaws as well. The real secret to success in data management is learning how to manage those flaws—proactively recognizing them or compensating for them once they unfold. Troubleshooting your system and data recovery are key skills you’ll need to be successful.
The Most Common Errors
Still, it pays to recognize and try to prevent the most common errors from unfolding:
- Inaccurate sources. Your first mistake could be relying on inaccurate sources of data. If you are collecting data manually, this could mean using inappropriate sample sizes, trusting disreputable organizations, or erroneously reporting your data. If you’re drawing data in from another source, it could be a compatibility issue (explored later). Subject all your data to a final review before it’s committed to your system, and adhere to best research practices.
- Duplicate entries. Most systems also have a problem with duplicate entries. For example, you may have several injuries in the system for “Mr. Smith,” “John Smith,” “J. Smith,” and “Jon Smith,” even though they all refer to the same person. This can lead to confusion when identifying individual records, or completely skew your high-level view of the numbers. More thorough entry procedures and occasional cleaning can help you reduce the impact here.
- Incorrectly labeled entries. Incorrectly labeled entries are a simple problem, but a potentially destructive one. Most of the burden here will fall on your staff, or whoever is responsible for entering the data in the first place. Come up with a clear, standard, consistent procedure if you want your records to be labeled accurately.
- Malfunctioning systems. Of course, some data errors are beyond your control. If the software company you’ve partnered with suffers a catastrophic loss or manages your data irresponsibly, you could suffer the consequences in the form of lost or corrupted data. The best thing to do here is carefully to review your software partner candidates, and only finalize the deal when you’re confident in your partner’s ability to protect your information.
- Incompatible systems. Things get more complicated when you’re trying to sync two systems together. For example, you might try to feed data from your CRM platform to your financial management platform in an effort to accurately project sales. It the connection isn’t reliable, or if the two systems use very different formatting, you could end up with errors, lost bits of information, and mislabeled records. It’s best to use a platform that allows you multiple functionalities under one umbrella; if you can’t get one, thoroughly review the API calls before trying to link the systems together.
- Security vulnerabilities. If your company suffers a cyber attack, or if your system is otherwise compromised, the integrity and availability of your data may no longer be reliable. Worse, your customers’ data may be stolen or misused as well. Choosing a highly secure system, training your employees in best practices, and constantly monitoring for cyber threats are your best strategies to protect itself here.
- Reporting errors. Even if your individual data points are sound, you may still present them inaccurately it there’s a problem in your reporting. You may choose the wrong cluster of data, rely too heavily on data visuals to draw your conclusions, or mistake one report for another. Reporting is often the final step and the most important one for putting your data to good use. Be consistent here and follow the proper procedures.
If you can prevent even a handful of these mistakes, your data will be more reliable, better organized, and better protected from external threats. And since most of the corrective actions associated with these mistakes don’t cost much or take much time, it shouldn’t be hard for you to make up for them.
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