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Corporate Data Quality (CDQ)

 

“When companies accept that other companies have good data management as well and understand the value of joining forces, we can share the efforts of cleaning and updating client and vendor data, each and everyone keeping data sovereignty.”

Kai Hüener, CTO at CDQ

International business partner data

International companies can have thousands of clients and vendors all over the world. Maintaining this data is crucial to minimise risks and administrative efforts of fixing, for example, wrong invoicing or shipping.

In principle, this data is publicly available and accessible. However, the complexity of business partner data comes from the global scope with ~200 countries, each with several national identifiers, address formats, legal forms, languages, standards, etc., and with the data being subject to change. In many countries, especially in Europe, national company registers are available as open data. These sources help to find and verify business partner data like addresses from clients, vendors or suppliers. However, keeping this information manually up to date is an immense effort and, to make it more complicated, many countries do not have open and well-maintained business registers.

The Competence Center Corporate Data Quality, a research initiative formed by academic institutions – among them the Faculty of Business and Economics (HEC – University of Lausanne), the Institute of Information Management (IWI – University of St. Gallen), and the Institute of Accounting, Control and Auditing (ACA – University of St. Gallen) – has further investigated this situation.  To answer the difficulty of keeping clean and updated, compliant, and harmonised business data, CDQ (Corporate Data Quality) was founded.

The CDQ community jointly tackles the challenge

The idea behind the initiative is to share the data management efforts of quality business partner data between CDQ community members, thus protecting data sovereignty. Kai Hüener, an evangelist for data sharing and CTO of CDQ, explains the idea in his interview with the Support Centre for Data Sharing.

CDQ uses external sources like open business registers, commercial sources and crowd sourced input from the members of the CDQ community to provide a pool of business partner data. Member companies can make use of this pool by integrating the CDQ API in their respective system, e.g. SAP, and receive updates for their existing business partner data - before it causes difficulties. In return, the companies can decide to share their own updates with the CDQ community. CDQ validates the update and shares it with the community anonymously. Only public information is shared, no notes or comments, for example. If companies decide that they do not want to share their own business partner data, they can opt out and will not receive updates from the community. These are only available to the companies that agree to share their updates in return.  It is however possible to share data but excluding strategic key vendors or suppliers.

In addition, member companies do not need to change their standard format of business data, e.g. which fields a dataset contains, how it is called or their order. CDQ works with different standards, forms and metadata vocabularies. In that way and for a service fee, CDQ enables the business data sharing community to share the efforts of clean, updated business partner data. This is particularly attractive for large international companies like Bayer or Novartis, current members of the CDQ community. Each new member that joins the community improves the pool and the opportunities for AI to automate part of the process.

 

AI for automated validation of updates

Algorithms can already clean and structure addresses to make them comparable. They can also classify records after feedback loops from the community and find anomalies or patterns in updates that were rejected. In the future, algorithms can take over the role of validating and accepting updates. Using external sources, an updated VAT number from a CDQ community member, for example, can be validated in an automated way based on the information in the external source. The process of accepting the validated update can then also be automated.

Kai highlights that the basis for realising these new features is trust and the need for a change of mindset that will probably take another 2-5 years. Awareness for coping with data management jointly is increasing and more organisations see the advantage of crowd sourced business data management with a third trusted part for validation and organisation.

 

 

Name

CDQ

Sector

Software and related advisory services

Region

Switzerland / World

Countries

Any

Time

Ongoing

URL

https://www.cdq.ch/

 

Business model

Commercial

Participants

The Competence Center Corporate Data Quality is a research initiative formed by academic institutions, including the Faculty of Business and Economics (HEC – University of Lausanne), the Institute of Information Management (IWI – University of St. Gallen), and the Institute of Accounting, Control and Auditing (ACA – University of St. Gallen). This research is what founded CDQ (Corporate Data Quality).

Type of organisation

Commercial

Data sharing model(s)

Trusted third party that manages and provides crowd sourced, open and shared commercial data for its members.

Core impact

The efforts to maintain and update clean business partner data are substantially minimised, specially for large international enterprises by joining forces and sharing the data with the community.

Context

International companies can have thousands of clients and vendors all over the world, each with several national identifiers, address formats, legal forms, languages, standards, etc., and with the data being subject to change. Keeping this information manually up to date is an immense effort. CDQ addresses this challenge.