By establishing a lingua franca that extends throughout the supply chain, manufacturers can generate insights from the digital data encircling their employees, partners, processes and customers.
Within a supply chain, an enormous amount of data is generated by the activities and interactions of all involved, including raw materials providers, logistics companies, distributors, retailers and customers. These ever-growing data volumes that encircle individuals, companies, processes and devices is what we call a Code HaloTM.
Code Halos can be classified by the types of data they spawn and their application to the broader business ecosystem. The value of this data depends on the organization’s ability to apply analytics to yield insights and foresights that extend beyond pure transactions.
One way to make meaning from this data is through ontology, an approach involving the creation of a hierarchical description of concepts in a certain domain, combined with a description of each of these concepts. By applying ontology, organizations can codify and apply a formal structure to the Code Halos associated with the supply chain ecosystem, using various concepts of class, subclass, inheritance, relations, properties, instances, etc.
To successfully use ontology in supply chains, organizations must take a methodical approach that involves tight collaboration among different players inside and outside the supply chain, from end-to end. We suggest a bottom-up, iterative approach because at every phase, new concepts or relationships may be uncovered that must be integrated into an earlier phase.
Identify a knowledge framework to outline the high-level scope of the ontology: The first phase of developing a supply chain ontology is to identify the gamut of knowledge in the functional area under focus. This involves identifying the boundary of all domain and process knowledge areas and the high-level concepts contained therein.
Define domain concepts, the building blocks of the ontology, as well as the relationships among the domain concepts: Concepts usually include products, processes, services, metrics and best practices, as well as more specific concepts that are unique to the business. Defining the relationships among the identified concepts will link them using logical relations, resulting in a grouping of similar concepts. This will help create hierarchies and other relations in future stages of ontology building.
Detail the domain concepts to define the ontology in business terms: This stage covers a deep-dive analysis of the concepts and relationships identified in the previous phases by subject matter experts. Along with breaking down and defining individual concepts in detail, the relationships between the concepts are established at a lower level.
Build the ontology: The build phase involves using specific ontology-building tools and technologies. Requirements of this phase include ontology definition expertise using the output of the previous phase as input, along with an understanding of the Web Ontology Language (OWL). Different tools, both commercial and open source, are available to build an ontology (e.g., Protégé).
The build output will be a completely defined ontology in the standard format, which can potentially be integrated with multiple systems on an as-needed basis.
Continuously integrate and grow the ontology: Once the ontology is built, it can be shared with all supply chain partners and potentially integrated with their systems. This introduces the possibility of growing the ontology in collaboration with partners. With a recursive approach, the entire supply chain can be covered in a common language that is maintained and owned by all interested collaboration partners.
A common ontology will provide a shareable framework for data capture, analysis, information dissemination and communication within the business and outside of it, across interlinked and inter-dependent businesses. The framework can be enhanced to align information systems and remove barriers of data exchange between applications owned and maintained by different parties.
The established ontology will be the foundation for implementing Code Halo solutions and will provide a lens to meaningfully view the multitude of data generated at various supply chain stages from different devices, systems and other sources that generate usable data. With all of the concepts and relationships already defined, it becomes much easier to develop a comprehensive set of algorithms and run analytics on this data to generate meaningful information. The ontology can further be leveraged to relate concepts that would have never been linked in a silo-based view, resulting in analytical insights that potentially amplify business value.
Achieving a strategic fit among individual players has always been considered the Holy Grail of supply chain. A huge step toward achieving this goal is the emergence of a common language to classify data and interpret the information. With modern digital technology, the amount of data generated is enormous. If businesses fail to make sense of the Code Halos surrounding their supply chains — as well as their employees, their partners’ employees and the interconnected processes and smart devices that span the supply chain — they will likely quickly fall behind the competition and ultimately be rendered irrelevant.
By using ontology effectively, businesses can create a lingua franca to take Code Halo thinking from high concept to supply chain reality.
To learn more about Code Halo thinking and its application, read our whitepaper “Code Rules A Playbook for Managing at the Crossroads” [PDF], as well as a comprehensive account of how organizations can catalyze business with Code Halo thinking in our book Code Halos: How the Digital Lives of People, Things and Organizations are Changing the Rules of Business (John Wiley & Sons).