"Collaboration without Coordination"
Collaboration without coordination i.e. being able to interact seamlessly and in a fully automated way in adhoc business relationships is the key to the next generation of agile supply chain management and industry 4.0. eccenca is enabling its clients to reach the goal of automating interaction and collaboration with business partners using internet of things and semantic technologies. In doing so, it is effectively producing the information for their supply chains that is making them agile, efficient and effective in a way that could never have been achieved without semantic technologies.
eccenca tools provide non-disruptive innovation to enterprises by seamlessly integrating cutting-edge technologies like RDF, SPARQL and HDFS with the existing mindset and technical infrastructure of the organization. They are designed to help organizations automate the extraction of meaning from silo applications, to link information from one source to information from others and to create integrated ways to query, access and interpret information across the organization. eccenca tools are using machine learning and semantic technologies capable of combining hundreds or even thousands of data models into a meaningful semantic knowledge graph. By combining these capabilities with HDFS and Spark on hadoop, datasets can be managed and data points can be analyzed in a timely, integrative and highly efficient way leveraging big data scale out infrastructure. Eventually allowing the organization to reduce redundancy of data management processes, data storage and streamlining the provision of facts to the business.
Supply Chain Capability Model
eccenca, a leader in semantic data integration and data lifting, has published the supply chain 4.0 capability development model based on its long-standing experience in working with various parts of the automotive and general industry supply chains. This model looks at the current state of data management and governance and provides three distinctive capability levels that lead up to a company's overall capability to develop and deploy next generation supply chain business models.
Key phases in the development of semantic supply-chain capabilities are:
It is obvious, that supply chain or value network participants need to find a rosetta stone to mutually agree upon the meaning of data and share critical operational data in a way that is meaningful for the entire group of stakeholders.
The question of course being (a) what is the rosetta stone and (b) if there is so much data to exchange, where to start and where to go next. We believe that the key driver for the selection of the data to start with, will be "your own itch".
It does not make a big difference with what kind of "payload data" you are going to start your journey of sharing data effectively in your ecosystems. It is useful to understand why the kind of payload does not matter and it is also important to understand why the semantic approach is going to work where other approaches have failed over and over again. First of all we are introducing a number of key concepts of semantic data that have already made the difference in many other industries and use cases and thus will make the difference in supply chains as well:
Effectively each data concept will have its own machine interpretable webpage that will allow machines and humans alike to unambiguously understand the meaning of this data object. Now how does that effect the supply-chain capability of any given supply-chain partner? Since the grammar is given by the World Wide Web (W3C) consortium, all your supply-chain stakeholders need to worry about is publishing or sharing vocabularies.Theoretically every member of the supply chain could start developing its own dialect. But effectively it makes much more sense to look at industry organizations like the APICS Supply-Chain council to lay the foundations of key data dictionaries.
Another key element that makes semantic supply-chain technology so effective is the fact that it is extremely simple to adapt existing templates or schemas into your own vocabularies. So for instance, the banking industry has gone through extensive lengths to create an identifier model for legal entities called FIBO. (They need it to report their business activities with these entities to the regulators.) Chances are that this model will do just fine for 98% of all Supply Chain 4.0 use cases you can think of. So why build your own vocabulary for that domain? When publishing data that is covered by the FIBO (Financial Industry Business Ontology), simply use their defined classes and properties (names) to classify and model your own data.
When looking at taxation, chemical substances, CAD/PDM data and many other domains there are ontologies (vocabularies) that are just as mature and capable of providing the level of detail that would be needed to describe supply chain objects. What has been missing in the past is a vocabulary to describe the types of data that go into the SCOR KPI model. This vocabulary however has recently been released by eccenca in collaboration with Fraunhofer and Infineon, so this gap has been closed too.
The bottom line is publishing and sharing data in supply-eco-systems have become dramatically easier due to the advent and maturation of W3C standards like RDF (Resource Description Framework) which are at the heart of the semantic web technology stack. There is no right or wrong in terms of what data to start with but your focus should be on creating an immediate return on investment in terms of supplier satisfaction, data quality or even process automation benefits.
Industry 4.0 and the Supply-Chain
In order to achieve the savings and efficiency gains expected from Industry 4.0 projects, manufacturers need access to large quantities of relevant information. Much of the data they need can be hidden in silos, locked in proprietary databases, or simply "out there" on the Internet. eccenca’s Semantic Data Management solutions open the doors to this data and provide a seamless understanding that enables efficient and effective decision making and thus the creation of the desired savings.
Industry 4.0 is increasingly having an impact on enterprise supply chains. This is posing a number of demanding new challenges to CIOs and IT Experts. When ever people are talking about industry 4.0 people typically are looking at manufacturing capabilities and resulting IT challenges. They are talking about the shop-floor, Manufacturing Execution Systems and the integration of cyber physical systems to form "Smart Factories". But realistically this development is not only about smart factories, but it hinges upon a parallel development of next generation supply chain capabilities. "Smart Factories", "Cyber physical Systems" and the "Internet of Things" will provide a whole new world of new collaborative opportunities and value creation processes.
The seamless and flexible integration of partners and value networks will create opportunities to produce faster, more flexibly and more efficiently but it will also add a whole new dimension of complexity to governance and management of supply-chains. Here are a few example SCM areas that are going to be impacted and that need to find new strategies to manage the ever growing complexity and ensuing data challenges:
"Collaboration without coordination" is the key idea behind eccenca's supply chain 4.0 offering. For machines to be able to collaborate it is important to define data formats and interfaces that typically are designed "lean" i.e. in a way to solve exactly the task at hand. With hundreds if not thousands of parties and machines to be synchronized in a supply chain eco-system, the cost of coordinating 1:1 relationships between all of these would be prohibitive. What is needed is a way to interact and connect and collaborate and commercially engage between parties without the need for the cumbersome effort of building a dedicated API for each individual relationship. Much rather what is needed is an API that is highly standardized and completely agnostic to the payload data itself. At the same time the payload data must be extremely extensible and flexible which could be achieved by allowing for an unlimited range of global and local data vocabularies which are dereferenceable and machine readable. The W3C standards RDF, OWL and SPARQL are the technical foundation to eccenca's semantic supply chain data solutions which meet these criteria and have the proven "enterprise readiness" to power the semantic supply-chains of the future.