From scientific data to financial data, experts agree on six main dimensions that indicate high-quality data. These data quality metrics can be applied to product compliance as well, and they can indicate whether or not you have data that is ready to meet regulations accurately and efficiently.
Lacking consistent and high-quality data is one of the biggest barriers to meeting materials compliance requirements. Without the data you need, you may find yourself scrambling to fill in data holes, verify outdated data or search for data you thought you had, but are unable to find in your database.
Consistently checking your data and adhering to these data quality metrics will help your team improve the quality of your data, which in turn will strengthen your materials compliance reporting.
The Six Data Quality Metrics
Completeness
Completeness refers to whether or not any information is missing from your data. Have you or your supplier filled in all the necessary information about a part or component? Is there any aspect of your component that is unaccounted for? Is information like part numbers, the supplier, or descriptions provided?
To ensure your data is complete, review it as soon as it is received. If there is incomplete or missing information, contact your supplier or your internal team that provided that data as soon as possible to resolve any issues.
Uniqueness
Uniqueness means that your data is not duplicated within your system, either with the exact same identifying information or a slight variation of that information. For instance, if you record one part within your system and then later record that same part with only a slightly different part number, you no longer have unique information. This can lead to confusion about which part to include in a data set and create doubt about the accuracy of your data.
When recording new data about your materials, double check whether or not that data is already in the system. If it is, use the accurate data that is already provided rather than duplicating it.
Timeliness
Timeliness means that your data is received or completed in a timely manner. With materials compliance, this data quality metric can impact whether or not you have the information needed to meet a deadline.
Having timely data comes from consistently communicating with your team and your suppliers. You want to make sure everyone knows when you need the data and what the deadlines are. A plan should be in place so that accurate data can be in the system well before any deadlines.
Validity
Data validity refers to whether or not the data adheres to right formats and requirements. Are your part numbers formatted correctly? Do you have the right number of decimal places in your weight? Are you measuring using the right metrics?
For valid data, you want to make sure your product compliance team is well-trained to spot possible variations that could cause data to be invalid. When you check the completeness of the data, you will also want to check the validity of it, making sure all the information conforms to required formats. Software can be invaluable in enforcing data integrity with automated checks that validate data formats.
Accuracy
The accuracy of your data refers to how correct it is. For product compliance, this means that things like the chemical composition and weight of components are correctly reflected within your data.
To help keep your data accurate, you will want to make sure your process for testing and determining the chemical makeup of your components is done carefully. When looking over data, you should also be checking to see if the data seems right to you. If something catches your eye as an outlier, go back to your team or your supplier to verify the accuracy of the information.
Consistency
Consistency means that your data is reported in the same manner across your data set. For instance, if you are reporting a part that has two of the same components, make sure both of those components are reported similarly. Another example might be having your part numbers formatted the same way across your system. If you have data in multiple systems, make sure the information is as consistent as possible across systems to avoid confusion.
Measuring the consistency of your data also relates to the uniqueness of your data: you don’t want information about the same component reported in different ways. When entering data into your system or accepting data from your suppliers, you will want to check that the data is recorded in the same way throughout the system.
Get Support Improving Your Data Quality
Having high-quality data is essential when it comes to materials compliance. If you are a supplier, parts can’t get to your customers without having the data to meet necessary requirements. For manufacturers, lacking high-quality data could mean missing compliance deadlines that delay your products. To keep the quality of your data top-notch, you will want to review it consistently, keep your recording methods internally consistent and get answers to any data questions you have sooner rather than later.
For support in improving your data quality, contact Tetra Tech’s team of compliance experts. From supply chain communication to reporting management support, our team can help you meet product compliance guidelines accurately and efficiently.
