Four Valuable Recommendations to Improve Data Quality

10.10.2019

Recommendations to Improve Data Quality

Key takeaways from the focus group "Data Quality for Business Impact"

It is often the same problems that different companies face in the field of data quality. Here, it is helpful to exchange ideas and best practices.

Therefore, the members of the community of the Competence Center Corporate Data Quality have now started to meet several times for an in-depth exchange on data quality management. They meet as the focus group “Data Quality for Business Impact” and discuss topics such as

  • Data quality KPIs and metrics systems
  • Data quality management applications
  • Communication of data quality’s business value

These are the key takeaways from the focus group:

1

Think big, start small: Define few yet highly business-relevant data quality KPIs

While having a comprehensive data quality metrics system is everyone’s desired goal, the group concludes that the data quality journey is best begun by defining only a few highly business-relevant data quality KPIs. These are typically derived from previous data defects and/or an assessment of the most critical data attributes for core business processes. Based on these basic KPIs, data managers can expand the scope of their data quality metrics system by integrating further use cases or data domains in a step-by-step approach.

2

Choose metrics that matter to your company

Data quality is a multi-faceted concept, as it includes multiple dimensions (such as accuracy, timeliness and consistency). Data quality also depends on the context in which data is used. Consequently, there is not one single data quality metric for the entire enterprise. Instead, data managers define metrics that combine several data quality dimensions for selected attributes, for different purposes like business processes or for data domains. By doing so, data quality as being “fit for purpose” can be measured in a way that is best for the data user.

Beiersdorf, SAP, SchwarzIT, Swarovski and tesa presented their data quality KPIs and metrics systems during the focus group meeting in Düsseldorf on February 28, 2019 during the 65th CC CDQ workshop.

3

Define the most relevant usage scenarios for your organization in order to identify the most appropriate software

Contemporary data quality management applications are the “same, same but different” as one software vendor said during a focus group meeting. Many functionalities provided by data quality management applications are similar; however, each solution has its own benefits and drawbacks and differs in its focus areas throughout the data lifecycle. Consequently, the group concluded they should, therefore, define the most relevant usage scenarios in order to identify the most appropriate software.

At the focus group meeting in Zurich on June 27, 2019 during the 65th CC CDQ workshop, SAP, Informatica and Syncsort presented their data quality management solutions, while user companies from the group shared their experiences with the applications. Furthermore, the software vendors conducted web sessions with tool demonstrations for providing a deeper understanding of the solutions in July and August 2019.

4

Know your company's pain points to drive data initiatives

It is not enough to know your data quality issues; it is important to understand the impact these have on your business. Individual pain points are usually rather insignificant on their own, but the more you have, the more negative the overall effect. Typical figures that management wants to see, for example, are cost reduction, risk reduction and revenue opportunity. Of course, it not easy to get these numbers. In addition to business value cases, data horror stories can help increase a topic’s general visibility as they typically refer to low probability scenarios that have a highly negative impact on the business.

SAP and AstraZeneca presented their approaches for linking and communicating data quality to the business during the 67th CC CDQ workshop in Berlin. The focus group gathered business value cases and shared data horror stories during interactive work sessions.

To date, the focus group has met at three onsite meetings during CC CDQ workshops in February, June and September 2019 and in three web sessions. CC CDQ member companies can access the presentations and discussion results via the CC CDQ knowledge base. If you have content-related questions or want to attend the upcoming focus group meetings in 2020, please contact us.

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