In today’s fast-moving world you need to have the right information at the right moment to make the right decisions. Enterprises have an astronomical amount of data gathered from different sources: automatic imports, manual entries, etc. That data has to be verified, validated and processed to be fully usable, regardless of its origin.
What is quality data?
The data is of good quality when it is reliable, precise and relevant. It also needs to be complete and up-to-date.
There are a few myths regarding quality data. Many believe that setting a data management tool’s parameters is not mandatory, that data’s quality monitoring completely prevents errors and that the users are solely responsible for the data’s quality.
In reality, an analysis tool is more efficient if it is configured and maintained by experts. Despite the implementation of the best practices, it is impossible to completely eliminate the risk of errors. It is essential to monitor data collection to be able to react quickly if problems occur. Moreover, the quality of data must be a collective effort.
The importance of quality data
During the decision-making process, large datasets from various sources are analyzed and transformed into specific information. The quality of the data therefore greatly influences your decisions regarding your activities, marketing processes or relations with clients.
An efficient data management will then help you improve those processes. You will also be able to reuse that data and information in a timely manner.
If you want quality data, you need to implement measures and rules to properly collect, manage, transform and use that data. To achieve that, your enterprise needs the necessary skills for data compilation and analysis and to configure and maintain your software solutions. Your involvement in data collection will also help ensure its reliability.
Enterprises usually have applications to process data and generate dashboards with key indicators to assist decision-making. The displayed information must be clear and accurate. I have seen enterprise reports where the nature of the price was not specified. It sometimes referred to the FOB price, sometimes to the commission net price and sometimes to the actual net price… It’s the same with the date formats. If you have a meeting on the 2016/05/10, will you go on May 10th or October 5th? There should be no place for interpretation in the nature of the information. Quality data loses all its meaning when not properly presented. Decision-makers must have a clear and unified picture of the data to be able to make the right decisions.
The cost of non-quality data
Up to 40% of expected returns during the implementation of strategies are not met because the planning was based on non-quality data. The productivity and relations with clients can also be greatly impacted by non-quality data. Of course there is a cost to data collection, validation and processing but, to cite Arthur C. Nielson, “The price of light is less than the cost of darkness”.
The implementation of good data management measures will give you many business opportunities and the means to improve your processes and your relations with clients. Gartner – Measuring the Business Value of Data Quality