AI MDM - Embracing the future

We're pleased to introduce Camelot Management Consultants AG, the Innovation Partner for our Data Quality and Data as an Asset: MDM ThinkLab, scheduled for the 12th-13th of April in Berlin. 

Henrik Baumeier, Partner for Master Data and Enterprise Information Management from Camelot Management Consultants AG, shared with us a bit about their AI MDM Community and data-driven digital transformation. 

Henrik Baumeier has more than 15 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. Henrik Baumeier worked for more than 30 international companies in EIM and MDM projects such as Bosch, Siemens, DaimlerChrysler, MANN+HUMMEL, Trelleborg,  Vaillant Group, dormakaba, Koenig & Bauer, AstraZeneca, Roche, Merck, Eli Lilly,, Evonik, BP, Lanxess, SABIC, Vetter Pharma; Novartis, Takeda, Teva, FrieslandCampina, PMI, St. Gobain, ANWR, Wingas. He is heading the Profit Center Enterprise Information Management within Camelot which is continuously working in innovative topics like Artificial intelligence in MDM or Value driven data quality management as well as classical MDM and EIM consulting.

1. The digital transformation affecting the corporate world definitely enlightens the need to become data-driven organisations in order to benefit from advanced analytics and overall better business processes. How does MDM help organisations to get there?

Self-learning algorithms, IoT and Blockchain are already and will profoundly change business reality in the next years and decades. To stay at the forefront, organizations have to understand how to manage their enterprise information to tackle some of the pressing challenges.

An integrated, cross-unit and cross-company approach for Master Data Management (MDM) embedded in a holistic Enterprise Information Management (EIM) is required to ensure that information related initiatives go hand in hand and support the overall business objectives. Only when all data initiatives and innovation projects are aligned, data-driven digital transformation can be empowered and the potentials fully exploited.

An EIM strategy boosts your organization in building up capabilities for structuring, describing and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency and enable business insights.

2. As our Innovation Partner, you'll bring the ever-so hot topic of AI applications for MDM. Can you share with us something about the AI MDM Global Community that Camelot created?

The Global Community for Artificial Intelligence (AI) in Master Data Management (MDM) is designed to foster systematic knowledge transfer and exchange with other companies, researchers and experts.

Community members are provided with continuously updated content, comprising interesting lectures, latest research information, innovative use cases, lessons learned and how-to guidance.

Furthermore, design thinking workshops will be conducted in Europe and the United States of America to ensure continuous inflow of new ideas. The workshops also offer the chance to share thoughts and ideas as well as challenges that will be discussed within the community. We recommend companies to benefit from this great opportunity and find partners for co-innovation, joining forces in the endeavor to bring first AI & MDM lighthouse uses cases to life.

3. What are practical examples of AI applications for MDM that companies can expect to be able to adopt today?

One example is a personal assistant that guides and assists users in the master data management system. Research forecasts that chatbots will be responsible for cost savings of more than $8 billion per year by 2022, up from $20 million this year. Less (or even no) end-user training and support will be required as chatbots will guide users and answer MDM and tool related questions. AI speech and AI gesture control will allow to process commands and to capture nonverbal feedback. AI machine learning will process the information and will have access to the AI knowledge representation of the company.

Another example is a data quality watch guard that performs data plausibility, correctness and duplicate checks. AI will check for duplicates and data quality of records based on attributes as well as information outside of the MDM application such as: transactional data, CAD / PLM data, SOPs, etc. AI machine learning (e.g. a deep neural network) will perform the correction of typical/ individual / regional errors, having access to the history of past changes. In combination with AI reasoning and AI knowledge representation the solution allows to investigate the root cause of data quality issues autonomously.

There are multiple practical examples of AI applications in MDM which immediately deliver business value. Many of them are elaborated and developed further within the Global Community for AI in MDM.

4. You've been helping companies in their MDM journey for many years already. What changes (if any) do you reckon that occurred in the driving reasons why companies decide to invest in improving their master data? 

The main changes are improvement of agility with flexible architectures, adaptive teams and big data insights as well as redefinition of processes particularly in manufacturing enterprises. Automation and increased usage of machine learning also play an important role. Another influencing factor has been building up resilience for digital risks such as data breaches and ramping up for new data privacy regime.

5. Let me ask you, Henrik, because we hear a lot about it and there seem to be different opinions about whether Blockchain has any applications for MDM or it's only a fad. What is Camelot's take on Blockchain and MDM?

Blockchain does not have an obvious direct connection to MDM, as MDM is often only seen as customer/vendor/business partner/material. However, through smart contracts new opportunities are arising.

Take a broader look at the example of  personal master data where we have a big variety of new use cases such as, managing personal health data via blockchain to maintain control.

As another example, sensitive data such as formulations or intellectual property which need secure sharing and access could be managed safely within an entire supplier/customer network based on a blockchain network with included trusted computing and smart contracts. Several of these use cases have already proven with the Camelot Hypertrust Platform. Camelot created this blockchain-based permissioned platform of distributed apps to discover targeted use cases across the entire value chain. 

For more classical master data you could as well think about a GS1 blockchain network using smart contracts to allow secure and controlled access of business partners to master data.

We thank Henrik for his contribution and we look forward to meeting the Camelot Management Consultants AG team and other MDM Managers, professionals and enthusiasts at our event in Berlin.

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. camelot-mc.com