Discussion on relevance of standardized data integration documentation for modern manufacturing business
Sharing product data in the supply chain of modern manufacturing companies is complex as the product’s lifecycles typically involves several stakeholders and multiple digital systems. The communication between organizations within the supply chain changes on daily basis as companies for example changes software systems, goes out of business or merges with one another. Collecting and sharing the data business needs in a format that also allows for automation of processes is an increasingly common challenge for businesses today. This has resulted in middleware tools being widely used for integrations. Fortune estimated the data integration software market for example was valued at about 12 billion USD in 2022 and is projected to grow to over 30 billion USD by 2030. A main issue is the lack of interoperability of the data in between systems and organizations as the data models are likely custom for each application. This results in that (independent of software or versions used) significant effort is being spent mapping data tables between applications. An unnecessary expensive activity that often lacks the sufficient documentation for project deliverables to be scaled or re-used. The value of standardization (e.g. common data models, taxonomies and nomenclatures) of the data exchange format and high-quality integration documentation when connecting systems via middleware platforms is highly underestimated.
The integration challenges become even more prominent in circular economy inspired business models. When products or parts of the products is intended to be re-manufactured or recycled the data sharing requirements increases for example traceability and usage information becomes of high interest. Being able to tie back knowledge from all the products lifecycle phases to the design becomes critical for the ability to create better and more sustainable product or service offerings. The importance of ontologies and data standards to solve these integration challenges has been frequently argued in research. Having an ontology or a standardized enterprise data model that is enforced in all middleware tools will also allow for less effort spent on integration projects as well as providing the flexibility to more easily change or replace one software with another.
Data integration documentation based on relevant standards is argued to be foundational for a future proven manufacturing business. Accurate live (always up to date) documentation will be required to efficiently govern and evolve integrations across the enterprise architecture. Interoperable (by human and machine) and accessible documentation artifacts will be key when establishing new connections between applications. Being able to understand data lineage or a products digital thread from these documentation artifacts will become a critical business process enabler for the more sustainable manufacturing industry. The approach companies take when it comes to leveraging data standards and maintaining standardized documentation in integration projects will determine the total effort spent as well as the competitiveness in the data driven supply chain.
“We can observe from multiple data integration projects that high-quality documentation is a success factor. We understand the relevance of documentation for being better at integrations as well as understanding the importance of data integration and data standards in the data driven business”
-Alex Nordholm, Co-founder and Lead Architect at AKNINET