7 Cost-Effective Ways to Improve Data Quality
If your data is missing information or has particular information mentioned multiple times, making no sense whatsoever, then you have a dirty quality issue. Erroneous data can be defined as data that is inaccurate, inconsistent, redundant, and incoherent. It is usually caused due to human error, but systems are also not innocent in this matter.
Data constitute important aspects of your business. It is what helps the business make important decisions, which can mean the difference between profit and losses. With bad, unclean data, you can only expect an unmitigated disaster that can sink the entire ships, costing millions of dollars in losses.
Such errors can occur in all fields of business. Hence, an eCommerce business outsources eCommerce product data entry services to avoid the issue of dirty data. Businesses that deal with unclean data also have to deal with low productivity, low revenues, wasted time, and ultimately insolvency.
Accurate, clean data entry is the need of the hour. However, even after automated software assisting us with the task, the problems still persist. So how do we ensure clean data?
With the below 7 tips, you will be not only able to uphold the standards of data quality and avoid any mistakes whatsoever but also do so at a comparatively low cost.
7 Tips to Improve Data Quality
- Keep it Simple
Don’t overload yourself or your team with data. Yes, data is important, but stuffing your database with heaps and heaps of data does not do you any favors. Try to lighten the load. Find data that is irrelevant and flush it out from the data is relevant. Most data quality issues arise because of the overwhelming nature of data. Hence, keep the entire process simple. Only execute the task in regulated, scheduled bunches. This will help you stay focused on your task while ensuring the data is immaculate.
- Eliminate Data Redundancy
Dulcification of data, or as we call it, data redundancy can cause a lot of headaches for you. Data entry in itself is a time consuming and tedious job. So it makes sense that you do everything in your power to enter relevant data. Avoid re-entering data that already exists in the database. You can use software and automated tools to alert you of redundancy in real-time. This gives you a chance to rectify the issue before the data gets recorded into the database.
- Carry Out In-depth Analysis
Analysis or verification and double-checking of data is the primary responsibility of every data entry specialist. There are two methods in which you can accomplish this.
- Error Cluster Analysis
allows you to identify errors at the source, thus allowing you to rectify errors at the source proactively
- Data Event Analysis
In this case, events that create and alter data are studied in depth to root out the cause of an error.
Both the analysis methods can work phenomenally in fixing errors and helping improve your overall data quality.
- Outsource Your Data Entry Tasks
When it comes to data quality, you must first determine whether your staff is capable of getting the job done. Normally enterprises do not have the skill or technology needed to carry out ensure data quality. This is where offshore data entry companies come to the rescue. Aligning with them will not only get experts working on your data but also cut your operation costs by 40% to 60%. Also, as you are hiring expert professionals, you can rest assured your data entry tasks will be carried out with well-established quality standards in mind.
- Software Tools
Most inaccuracies in data are directly related to human errors. Software and tools can be perfect antidotes to these unwanted errors. They can catch errors that may easily be ignored by the human eye. There is an array of tools and technologies in the industry today that can effectively assist you with finding errors in your data and rectifying them before being recorded.
Software like ICR (Intelligent Character Recognition) and OCR (Optical Character Recognition) are phenomenal tools to identify errors and reduce your workload by tenfold. These tools will find errors in data that previously would have been overwhelming to find and suggest corrections to rectify the issue. You can customize this software according to your requirements.
- Set Accuracy Goals
Set well-defined accuracy goals and communicate the same to your team. Let them know what is acceptable and what you can do without it. Setting goals will bring everyone in your team on the same page. Hence, leaving no room for confusion.
- Do not Choose Speed Over Accuracy.
Speed is good; everybody wants a fast turnaround time when it comes to data. But it should never come at the cost of accuracy. Fast work can result in the commitment of many careless mistakes. Avoid these mistakes by prioritizing accuracy over speed.
The Bottom Line
High-quality data is crucial for a business to thrive in a cut-throat industry. The above tips, if followed diligently, will work phenomenally in improving your data quality without spending much on its execution.