If you’re like most manufacturers, you’re probably looking for ways to digitally transform your business. After all, the industrial sector is one of the last bastions of manual labor in an increasingly automated world. But where do you start? And more importantly, how can you be sure that any new technology initiatives will actually generate results?
A recent “new word” is iPaaS, as you can guess, stands for “integration Platform as a Service. It promises a lot of good things such as allowing businesses to quickly connect disparate systems and applications together, leading to a more efficient and streamlined operation. Altogether it can take manufacturing companies to the next level and achieve a future state of the connected system.
My attention was caught by Lionell Grealou’s articles about iPaaS published at Engineering.com. Here are two links. Check them out.
Building Digital Threads with Enterprise Integration Platform as a Service (iPaaS)
iPaaS Can Democratize PLM-ERP Integration and Business Analytics
It stays 10 benefits of iPaaS, but most of them can be easily applied to any integration platform or solution – integration stability, low-code/no-code , connecting modern platform and legacy sources, shift from p2p to service-based, integrated IT infrastructure, data connectivity reduction the need in hard to hire skills and even magic AI/MI promise to interpreter data through the transformation.
I agree with Lionel’s statement:
Having said that, iPaaS is for sure no silver bullet when it comes to making integration simpler and easier to maintain. Nevertheless, it provides opportunities for greater control and rationalization—pending a clear and consistent enterprise architecture coordination and governance between user-driven RPAs and enterprise level platform integrations.
… and finally the concluding passage:
Finally, enterprise platform vendors (PLM, ERP, MES, CRM, and more) can use iPaaS approaches as a positive selling point when positioning their competitive advantage to prospects. It is important for them to align to third-party iPaaS solutions and standards, making the necessary APIs available in the relevant format for effective integration (e.g., REST APIs, GraphQL, etc.). Software editors can also drive new opportunities in making their legacy applications compatible with such API advances to facilitate backward and upward integration, as well as enabling seamless data coexistence towards cloud-based platforms and building effective digital threads.
As you can see in the article and Gartner MQ for iPaaS, many vendors there are “old new” names. If you’re in the integration and PLM business, you have most probably heard about them one or two times.
Nevertheless, the article made me think about what iPaaS platforms can bring to the table that will make integrations different from everything we’ve seen before for the last 2-3 decades of integration technological innovation starting from EAI tools, integration service buses, and other integration brokers?
Here are some of my thoughts that hopefully will help you to identify the right platform of choice for your future PLM integration projects.
Integration Abstraction Level
Integration is first of all ready to be used connectivity with the systems you need to work with and specific business processes. While anyone can build integrations, what can make it really different is to support some business logic out of the box. It is a combination of data models, API end-points, and templates that make it work seamlessly with many systems. Imagine your need to integrate with a financial platform. My hunch is that a scenario to connect between PLM system downstream to the financial system can be described in some formal way that can be reused no matter what PLM or ERP system you use. Such “templates” can be very helpful to tune future integration platforms.
Flexible Data Models and Business Objects
Complex business processes in product lifecycle management, enterprise resource planning systems and supply chain management requires data modeling that goes beyond passing a single value from one system to another. As a result, data needs to match business processes in existing ERP systems, product data management, and other systems. Integration flows is a complex process that requires matching data models to reflect business processes. Modern data management technologies provide a variety of mechanisms to model data and having them at your fingertips is extremely important to make integration successful.
AI/ML and Self-Learning Capabilities
Data and integrations are very complex businesses. Therefore suggesting how to recognize data and integration patterns can be a magic silver bullet to help develop integration processes in a much faster way. iPaaS platforms potentially have access to the data that companies are holding in many legacy databases and enterprise systems including SaaS solutions. Although it sounds like a dream, by iPaaS can offer some data rationalization and gleaning of intelligence from existing data silos and integration processes. I like the idea of plug-in systems and letting iPaaS do a job. Sounds like a dream? But our navigation devices are capable to learn our driving habits. Why iPaaS platforms cannot do the same after the integration of hundreds and thousands of PLM and ERP systems together?
What Is My Conclusion?
Integration is a complex business process. It was the same 20 years ago when I started to work with EAI platforms such as BizTalk and IBM WBI and remained the same now with modern iPaaS solutions. What makes difference is related to three main things: (1) speed to build integration solutions; (2) data intelligence and (3) ability to connect to systems we need to integrate right away. So, when you choose your iPaaS for future integration between PLM and ERP systems, follow these three principles. Just my thoughts…
Best, Oleg
Disclaimer: I’m co-founder and CEO of OpenBOM developing a digital cloud-native PDM & PLM platform that manages product data and connects manufacturers, construction companies, and their supply chain networks. My opinion can be unintentionally biased.
