How To Reduce Data Entry Errors Down To Nearly Zero

Data entry errors are inevitable but they can be time-consuming to fix and worse, costly for business. But how do you stop a problem that’s fundamentally human, a problem that is impossible to completely get rid of?

The operative word here is to “reduce”. Reduction of data entry errors can occur on various fronts including the frequency in which they occur, the severity of the errors and even the timing at which data entry errors occur.  

Simply getting to the point of having fewer “big-deal” mistakes is a reasonable goal for all businesses. Of course, getting there isn’t always that simple.

Data Entry Error Types and Facts

Just before diving into some solutions for data entry mistakes, it’s worthwhile taking a look at some of the most common data entry errors and their implications. This will amplify the importance of reducing them.

Data Entry Faux-Pas:

  • Transcription errors – Errors of transcription are among the most common data entry mistakes – they include typos, repetition (of words) and deletion or words or numbers.
  • Transposition errors – Also ranking high in data entry error occurrences – transcription errors involve the incorrect sequence of numbers (ie. typing “716” when you meant to type “761”)
  • Unit/Representation InconsistenciesAlso very common, are mistakes involving the inconsistent use of dates and times, addresses, and measurements.

Data entry errors from either of the three categories can significantly slow a business process down. Imagine, how much time can be lost searching for a missing product, file or account simply because someone failed to label it correctly.

But there are high-risk industries such as healthcare and aviation, where the wrong data entered into a computer can lead to serious injury, illness or the loss of life. When you consider the extent to how far a seemingly small data mistake can go, you’ll agree how important it is to sweat the details.

Techniques To Reduce Data Entry Errors

Fortunately, with the right protocols and processes, you can significantly reduce the occurrence of data entry errors. And many of them are easy and affordable to execute. It just takes a willingness from both employers and employees to embrace these techniques.

Simple Ways To Keep Data Entry Mistakes At Bay

  • Use automation software to “auto-fill” the correct data where possible
  • Use software with double-checking features for accuracy/verification
  • Rely on comprehensive data analysis tool as a “safety net”
  • Create and refer to checklists as reminders for employees
  • Promote a culture that values accuracy over speed
  • Create a culture that fosters a low-stress environment
  • Take steps to reduce employee fatigue

Keep in mind that reducing data entry errors will also vary based on industry. That means someone filling out a prescription will have to verify data differently than someone who’s entering stock trading data and so forth. Ultimately, the key is to use a combination of technology, habits and an environment that enables your staff to work at their best.

Zooming In On One Important Tool

There’s one fix above that we want to discuss in a little more detail, and that’s the third point – relying on a comprehensive data analytics tool. This is important because again, humans are imperfect and even with plenty of fact-checking, errors can still slip through the cracks.

A data analytics tool such as our GLAnalytics solution works as a second pair of eyes, that proactively reports data inconsistencies, omissions, repetitions and other mistakes. Depending on the required formatting of the files you keep on record, you can set parameters for GLAnalytics to find numbers or words that don’t match the format of a particular document.

This allows you to find mistakes you would otherwise miss and, if done regularly, you can find these mistakes fast before they cause serious problems.

Data Accuracy Is Everything

It’s a fast-paced world where every minute spent has a monetary value attached to it. Due to the sensitivity of many industrial processes, it’s crucial that the data going into certain software is as close to perfect as it can get. Although mistakes will happen and there will always be a margin of error, accuracy is and will always be paramount.

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