What are the tasks in the area of product data?

Product data are created in an early phase of the Value Creation and Supply Chain Process and are needed to the end, even over the lifetime of products. They describe products and supply all necessary information about a product for various recipients at various points in the Value Creation and Supply Chain Process. It is therefore the task of product data management to store relevant product information on the complete variety of products and make them interpretable available at various locations and points, whenever and wherever needed.

What are the typical challenges of product data management and how do you see them being handled?

The diversity of product variability and the complexity of today's products mean that the relevant data volumes have grown enormously. These, in turn, encounter a complex environment which is characterised in particular by border crossing over various areas across the entire Value Creation and Supply Chain Process. These border crossings are manifold and can concern for example as follows: company boundaries and company standards, national boundaries and linguistic barriers, process interfaces, interfaces in the area of information and communication technology.  In some cases, these interfaces may occur individually or bundled. Thus, for a considerable time, we have been dealing with a continuously increasing complex scenario in the area of product data exchange, which is difficult to be managed on a high efficiency level. Fully automated data transfer from machine to machine is the consistent response.

However, for a comprehensive machine realisation, a common foundation for all participants within the product data management environment is required. We find this in the systematic approach of Product Descriptive Classification and the development of common product data standards. In the case of already existing different standards, a harmonisation between these standards leads to complexity reductions and to the possibility of machine useable mapping strategies.

In principle, the approach of the solution is aimed at establishing a common unique "language" on machine level, which in principle enables each recipient to make a machine interpretation of the received encoded product data. At this point, the product descriptive classification standard eCl@ss can be mentioned as an example. eCl@ss is already able to provide property-based semantics on the basis of a quality-tested knowledge architecture and a data model according to IEC61360 and ISO 13584 for many product areas.

What are some tips for achieving borderless product data exchange with external partners? How difficult is it to develop and implement some inter-company standards?

I want to be honest; it is not a simple exercise. Firstly, an appropriate common solution concept must be developed with relevant partners. These concepts, which exceed company boundaries and sometimes even industry boundaries, require a common set of standards to be developed. It is also possible to harmonise already existing standards. In both cases, however, a basic common compromise is required. Depending on how pronounced this compromise is with all parties involved, the more easier or difficult it will be to succeed together. Common standards and norms are here an indispensable prerequisite and the key to success.

What is the meaning of industry 4.0 (I4.0) concept and the resulting requirements for product data?

Basically, production, communication, and information technology are interlinked in the area of I4.0. Direct communication from machine to machine using digitally networked data is essential here. Customer, order, machine, engineering, product data and so on, are automatically sent, received, and interpreted by machine. The goal is the self-organised machine control of production. A virtual representation of physical products and processes is required to realise I4.0. A "common language" must be spoken in the context of the networking of all active partners and process elements as transmitters or receivers of product data. This is made possible by common standards and norms.

Within this scenario of machine to machine communication by digitally networked data, any parties wanting to join will be forced to bring in its product data on I4.0 machine readable level. Is your organisation on the way to be fit for it in future?

The future requirements resulting from I4.0 makes the aforementioned statements all the more important and true regarding the use of a systematic approach, the Product Descriptive Classification, and the need for common and harmonised standards and norms.

With the founding of a Digital Expert Group and the start up of respective developments, the product descriptive classification standard eCl@ss has already made its contribution here, to be in future, a part of a corresponding solution concept with a ready-to-use consensual semantics. In addition to open standards, national and international standardisation organisations such as DIN, ISO and IEC shall also be taken in consideration.

What would you like to achieve by attending the 18th Edition Master Data and Data Quality conference?

It is important for me to record a wide range of different views on the area of master data and in particular product data. I am looking forward to getting impressions, enabling me to evolve ideas for possible future developments. In particular, the topic of artificial intelligence must always be kept in mind as to what extent this can have disruptive effect to today's approaches already in place or currently being developed. Maybe today it is not enough to think about the next step, however it seems to be the time to think about possible future developments for the day after tomorrow.

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Yiota Andreou


Ahead of the 18th Edition Master Data and Data Quality Conference, we spoke Gerhard Treitinger, Project Manager, Senior Expert Product Data Management System and Standardisation at BSH Bosch Hausgeräte and supporting eCl@ss as Head of Expert Group Home technology, household appliance. Gerhard spoke about the typical challenges of product data management.

Practical Insights From:
Akzo Nobel N.V.
BSH Bosch Hausgeräte
CAMELOT Management Consultants
Coca-Cola Hellenic BSO
Deutsche Post DHL Group
Jacobs Douwe Egberts
Robert Bosch GmbH
Teva Pharma
zetVisions AG


About the Conference:

This marcus evans event will focus on tackling challenges on the journey towards business critical master data, improving business process efficiency and reducing waste from poor data quality. For over 7 years this event has been a great platform for MDM leaders from multinational companies to benchmark and exchange excellent ideas. The 18th Edition Master Data and Data Quality Conference will take place from the 15th until the 17th of November 2017 in Barcelona, Spain.

Copyright © 2017 Marcus Evans. All rights reserved.

Previous Attendees Include: 

Adidas AG
British American Tobacco
Deutsche Telekom
Maersk A/S
Orion Corporation
Red Bull

About the speaker:

Gerhard Treitinger, Project Manager, Senior Expert Product Data Management System and Standardisation at BSH Bosch Hausgeräte and supporting eCl@ss as Head of Expert Group Home technology, household appliance
Gerhard has accumulated many years of experience in various technical and organisational tasks at BSH Hausgeräte GmbH. The organisational structures, products, and procedural challenges of the domestic appliance industry are thus well known to him. For more than 10 years now, he has been able to further extend this experience, especially in the area of master data, product data management and standardisation, and also to apply it to the benefit of the company and industry. For this, it is necessary to conceptualise and realise future solution scenarios in the area of product data management at company and industry level. Since common cross-industry standards are an important success factor, he supports the product-describing classification standard eCl@ss as head of the expert group home technology, household appliance and contributes as a consulter to the further development of eCl@ss.
Gerhard holds a German Dipl.-Ing. degree in electrical engineering and is particularly keen to discuss future necessary developments in the area of product data management to fulfil upcoming requirements by I4.0 and digitisation of the economy.

What are the challenges of product data management?

An interview with Gerhard Treitinger, Project Manager, Senior Expert Product Data Management System and Standardisation at BSH Bosch Hausgeräte

Gerhard Treitinger, Project Manager, Senior Expert Product Data Management System and Standardisation at BSH Bosch Hausgeräte

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