The availability of and access to high-quality catalogue and repair & maintenance information is the key to success in the independent automotive aftermarket. In order to be able to offer TecAlliance customers optimum quality for the extensive TecAlliance database, the Information Management business unit is constantly working on expanding and improving data quality management.
The objective of data quality management is to plan and ensure the organisational, method, conceptual and technical requirements to manage data quality as asset for the following types of information produced in the TecAlliance Information Management business unit: vehicle data, product data, supplier data, inventory numbers, and repair and maintenance information.
In order to be able to sustainably convert the proprietary OE data into information valuable to the independent automotive aftermarket, the processes in Information Management must be continuously developed. In this regard, data supplied by industry parts manufacturers, for example, is extensively validated by TecAlliance upon each data delivery and evaluated each quarter based on defined criteria in the course of a supplier assessment. The evaluation results are reported back to the parts manufacturers so that they can continue to improve their quality. Those data suppliers who meet the appropriate requirements at a particularly high level are awarded the “TecAlliance Certified Data Supplier” seal of quality – currently some 70 percent of TecAlliance data suppliers.
The previously applied validation and assessment processes are based exclusively on objectively and automatically measurable quality indicators. Andreas Assmann, Vice President of Information Management Data Quality & Services, intends to comply with the wish expressed by the customers during the International Data Supplier Meeting to subject the supplier data to more extensive quality assessments in addition to the validation and supplier assessment. As of the first quarter of 2017, we will also be carrying out subjective quality assessments, which will provide clear results on the following ten particularly relevant dimensions of information quality: accuracy, credibility, unambiguous interpretation, consistent representation, objectivity, concise representation, comprehensibility, relevance, scope and completeness.
“Today, TecAlliance already uses a very wide range of validation and assessment measures with which we aim to achieve the best possible data quality for our customers. Despite this, our customers are unfortunately still critical of some of the catalogue data. That is why we will also be carrying out a subjective assessment of the supplier data from a user’s point of view. On the basis of the ten particularly relevant dimensions of information quality for catalogue data, we intend to find out just what problems and vulnerabilities the users encounter in their day-to-day work so that the data suppliers can optimise their data in these areas”, Assmann explains.