Key Steps to Success with Data Accuracy
Several large manufacturing organizations recently shared their success stories in implementing data quality practices. These organizations described the processes and procedures that they put in place to ensure that the data they communicate via GDSN meets the data quality expectations of their trading partners.
An initial step that several manufacturers took to gain executive sponsorship was to undertake a quick assessment of the quality of product data that they were providing their Trading Partners. The universal finding of these quick assessments was eye-opening – the data was meeting neither internal needs nor trading partner needs. This lack of data quality was then causing re-work which frequently ended up taking Sales and Buyers time to resolve – time that then wasn’t available for increasing revenue.
The quick assessments focused on physically verifying the weight and dimensions for a sample of case products. These values were then compared to values that had been provided to Trading Partners and the values used to load your own trucks.
Next, a study was undertaken to identify the root causes of significant errors and to develop appropriate responses. For example:
- Product specifications different than actual production,
- Preliminary data not updated with final production data,
- Data values not communicated internally as product changes are made.
This analysis frequently identified the lack of formal accountability within the organization for the different types of data attributes and a formal process for controlling the accuracy of product data.
For smaller organizations the practical steps are easier to implement but just as important:
- Re-measure products once they are in production – measurements from samples may differ from production,
- Identify what changes to the product should trigger a re-measurement of the product,
- Ensure that measurements are taken according to the GS1 Rules – how to position the product and what the required tolerances are,
- Physically re-measure a sample of your products to determine the quality of your existing data,
- Review what information you may have provided your Trading Partners in past – i.e. old Listing Forms, etc.
These steps will help you be ready when your Trading Partners begin to audit your product data and implement scorecards.