With the increasing popularity of analytics and big data, business owners are becoming aware of the significant role that data management plays for an organization. Credit goes to factors like forecasting customer expectations, product management, availability, improved customer services, and competitor’s analysis, data quality management is a critical function for any organization.
One important condition applicable here is that the data should be complete, accurate, and consistent to help businesses make informed decisions. It won’t be wrong to say that modern businesses cannot afford to ignore data quality management.
Data Quality Management refers to the process that brings the right people, technologies, and processes in a combination to achieve a common goal of improving the health of data being circulated in the organization. This process is of immense importance since all the important business decisions depend on high-quality data. However, the process of managing data quality has got easier with the next-generation electronic document management systems.
The ones with seamless integration capability make value addition for an organization’s quality management system, improving the product quality and customer experience.
DQM is a very important process to make sense of your business data, which adds value to your bottom line. Here are three reasons that you need to have the DQM process in place:
To ensure an effective data quality management process, every organization need a structural foundation to support its quality management initiatives. The five factors that make a great foundation structure for implementing policies for high-quality data in your data units:
First and foremost, step in ensuring quality data is establishing the right hierarchy structure within the organization. Make sure you define the important roles such as data steward, business analyst, Change Manager, Program Manager, etc. to ease the data quality management at every level.
Now that structure is clearly defined, you must define the data quality. If you will not be able to make your employees understand the expectations in terms of data quality management, you won’t be able to make the most out of the critical information you have. However, the definition of data quality may vary from business to business.
Performing audits to keep a check on data quality is as important as auditing the financial data and performance of your organization. When you conduct regular data quality audits, you can ensure that the required data is circulated across the organization in the exact format defined under data quality objectives.
A well-defined process of reporting and monitoring data is also of great significance in ensuring data quality. You can have an electronic document management system in place to keep all the significant data recorded and documented for regular monitoring and reporting activities that improve overall decision-making.
Once you will have a document management system in place, you can keep a check on recorded information to mitigate the data errors. This ensures a process of continuous improvement for the data quality meant for internal as well as external communication.
If you want to implement a data quality management process, given below is the list of best practices you can follow:
Don’t let the bad data and insights make your decision-making process ill. The old phrase “Garbage In Garbage Out” fits perfectly well in this context. You must regularly review your data to identify the errors, redundancies, and inconsistencies and ensure only quality data flow in the organization.
You must have a firewall in all the systems within the organization to keep them clear of bad data and errors. A firewall is the best solution to stay error-free even when you have a large group of people to access data. It is, in fact, an imperative system to have especially in the organizations with multiple access points
In modern-day business, the integration-enabled systems are gaining tractions. The systems working together are a source of great outcomes. Integrating the process of data quality management with business intelligence triggers automation, which accelerates the process lifecycles.
As already discussed, it is very important to have the right people in the right place. You can ensure that through creating a hierarchical structure of roles and the respective responsibilities. This will further help you to ensure that all the standards defined in the organization are met without any inconsistency.
You must establish a data governance board within the organization to keep a check on the implementation of data quality policies and standards. It also includes defining an objective measurement process or scale that can improve the quality. When you will be able to measure it, you will be able to improve it.
An electronic document management solution is a perfect way to ensure that your employees follow best practices for data quality management. From documenting business-critical information till publishing or archiving it, everything can be managed through an advanced document management software like Qualityze.
There are many benefits that you can expect after having an EDMS in place. Some of them are:
Isn’t document management system a smart way to manage data quality for your business processes? So, make sure you take a step forward to new data quality management initiatives with the best document management software.
Maintaining data quality is vital for making your business processes more efficient for improved outcomes and confidence that help to make informed decisions. It can be done with the help of the right cloud-based document management software like Qualityze in place that fits well for your ever-growing and changing business needs.
Are you ready to manage your data quality?