November 13, 2018

Keeping Pace with the AI MDM Community. 

We're pleased to catch up again with Camelot Management Consultants AG, Innovation Partner of our MDM ThinkLab which happened last October in Berlin. 

Christian Fuchs, Head of Artificial Intelligence for Information Management at CAMELOT Management Consultants AG, shared with us a bit about their AI MDM Community and data-driven digital transformation. 

Christian Fuchs has more than 5 years of project experience in various Information Management projects, especially in the areas MDM strategy, Digital Transformation, Data Quality Management, Governance & Organization, Process & IT conception. Christian Fuchs is heading a team of data scientist and Information management consultants that is delivering innovative solutions for classical MDM problems based on Data Science and Machine Learning approaches.

1) Christian, what's new in the community since we spoke to your colleague Henrik in April and what are some of the exciting findings you can share with us?

The Global AI in MDM Community is growing! More than 80 MDM practitioners from industry companies mainly in the EU, US and APAC discuss and exchange ideas on a regular basis. In October, we had our third onsite workshop, bringing those experts together for two full days. The presentations and discussions were very fruitful. The community overall identified more than 70 use cases for AI in MDM so far. The next workshops are already scheduled for February 2019 in Mannheim, Germany, and Philadelphia, USA.

To deepen this knowledge exchange, we also started a webinar series. Newcomers are still welcome. Here you find more information about how to join the Global AI in MDM Community.

2) Do you see AI more as a disrupting force for MDM or more as a source for process efficiency or improvement?

It all starts with defining what AI is. Today, when we talk about AI for MDM we mainly refer to data science and machine learning approaches. These allow companies to leverage structured (e.g. tables), semi-structured (e.g. html) and unstructured (e.g. picture) data to improve their master data practice and increase their overall process efficiency. AI solutions are still highly specialized, meaning that they can perform highly specialized tasks only, but in a very powerful way. 

There is not the one AI solution and most probably will not be in future. There is a broad variety of highly specialized algorithms and services that are typically connected with classical business applications. On the long run, these single solutions might be merged as single puzzle pieces to a bigger picture – and then the disrupting force of AI in MDM will be more clearly visible. 

3) What are the prerequisites for companies to start using AI successfully in their organizations? 

As consultants we engage a lot with customers and we still see that there are very different expectations towards artificial intelligence in MDM. Some are very pessimistic, assuming that AI is just a buzz word that will disappear after a while, some are very optimistic and expect AI to solve all their problems. As always, the truth lies somewhere in between. 

If expectations are too low, then companies miss opportunities that lead to more efficiency as well as automation. If expectations are too high then sooner or later they will be faced by the reality of failed projects, disappointed stakeholders and declined trust in the MDM organization. In order to succeed with AI in MDM in the long run, it is important to set the expectations right from the beginning.

4) Which steps do companies need to take today in order not to be left behind in the AI-MDM game?

To achieve higher process efficiency with AI, companies should look for isolated MDM problems that rely on data and require a specialized solution. If these tasks are often repeated and create manual effort, then organizations should consider AI approaches. 

Highly specialized tasks could be, for example, mining rules from data sets instead of deterministic rule design, auto population of values based on forms (e.g. printed documents), searching outlier master data, predicting master data activities etc. 

We usually conduct design thinking workshops with customers to identify and assess use cases for AI based on their existing pain points. It is crucial to find a first case that has the potential to serve as light house project to convince critical stake holders and the management. 

In the end, the key success factor is to gain first experience with AI to see if it should be considered on the long run. This is something that each company has to figure out individually. Thus, companies are typically running a first short and crisp proof of concept before deciding about further investments into AI and MDM.

We thank Christian for the contribution and for the presentation last month. 

To learn more and to experience live content and interaction at our MDM ThinkLab 2019, contact us at

Yours, ThinkLinkers

CAMELOT Management Consultants is the globally leading consulting specialist for value chain management in the process, consumer packaged goods and industrial manufacturing industries. The company is part of the CAMELOT Group with 1,700 employees and headquarters in Mannheim, Germany. The integrated consulting approach and the close collaboration with renowned technology specialists guarantee project success along all consulting phases: from decision-making to the organizational and technical implementation. With more than 20 years experience in Enterprise Information Management we help companies make the best use of data along their entire value chain. Our service offering is part of the CAMELOT Digital Transformation framework that covers digital transformation end-to-end. We provide the necessary business and IT know-how to design and implement appropriate EIM solutions that meet your goals.