High quality data are among the most valuable assets any company can have. In hyper-competitive industries where there’s not much separating the companies from one another, simply being in possession of high quality data can be enough to give your business a leg up over everyone else.
If you don’t want to waste money on ineffective strategies, marketing campaigns, and outreach efforts to prospects and clients, it’s best to take care of your data diligently.
You can employ a variety of methods if you simply want to repair your existing company data. Data matching should make entries included in all of your databases more consistent while data cleansing will get rid of inaccurate entries that no longer need to be present.
Still, it’s better to not have to use those aforementioned methods just to repair the data possessed by your company. The ideal solution to the problem of poor data quality is to prevent those bad entries from being put into the system in the first place.
This is where it becomes wise to consider certain options that can help prevent the spread of low quality data in the first place.
Prevention Is Better Than Cure
The saying goes that prevention is always better than cure. This rings true even when it comes to the topic of data quality management.
Instead of having to do damage control and address erroneous data entries, it would be better for companies to set up safeguards that will prevent the encoding of those mistake-filled entries in the first place.
Of course, preventing the spread of inaccurate data entries is easier said than done. If you have plenty of customers, the sheer volume of information coming from them that needs to be processed and encoded into the databases can be the leading cause for the errors as well. It’s easy to get tripped up when dealing with that much data.
The good news is that there are still things that will be able to help you maintain higher quality data moving forward.
When trying to figure out what is data quality, it helps to go back to the basics. The quality of the data refers to its completeness as well as to its accuracy as it pertains to correct spelling and even how up-to-date a particular entry is.
That’s not all though. The quality of the data can also be affected by inconsistency.
If employees have different ways of inputting the data, chances are that your databases will be filled with all kinds of confusing entries that will be difficult to interpret.
This is why it’s important to govern your data entry properly. According to Techopedia, one of the core principles of data governance is setting guidelines for data entry.
The guidelines should clearly indicate how elements such as names, dates, and addresses should be entered. You can also include other guidelines to promote uniformity.
Regardless of which guidelines you establish, the bottom line is to have your employees follow them all the time to prevent the creation of wrong data entries.
Master Data Management
The Business Dictionary notes that master data management (MDM) tools are intended to provide users with “complete views” of data pertaining to customers, vendors, and even possessions of the company.
It’s easy to see why they can be helpful for the purposes of halting the spread of inaccurate data. Those tools can provide you with quick overviews of all your data.
If you haven’t integrated MDM tools just yet into your company operations, it’s time to change that. These tools can make working with mountains of data easier for you and all your employees.
Human error is inevitable and no matter how well-trained your employees are, they are bound to make data entry mistakes at some point. Whenever possible, automate data entry processes to make things easier to handle for your employees.
Automation is not always foolproof itself, but it won’t produce nearly as much errors as relying on more conventional data entry methods.