Digital threads connects PLM, ERP and other platforms for simpler, faster and affordable integration.
Business reasons for data integration are diverse; they range from better analytics to workflow continuity, data sharing and virtualization. Business value is derived from enhanced connectivity, distribution, consolidation, simplification, automation for downstream consumption—from analytics at the source to cross-functional analytics overlaying multiple data sources.
Both business analytics and enterprise integration imply elements of data virtualization and transformation (extract-transform-load) as an abstraction layer between authoring and consuming sources. In simple terms, the former drives value reporting and decision-making, whereas the latter contributes to extending value creation through data consolidation.
As Gartner puts it in its Glossary:
- “Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain).”
- “Data Virtualization technology is based on the execution of distributed data management processing, primarily for queries, against multiple heterogeneous data sources, and federation of query results into virtual views.”
As discussed in a previous article, integration platform-as-a-service (iPaaS) brings together data governance, integration development tools, data translators, scalable cloud infrastructure, pre-built error handling and platform connectors. They contribute to liberating data integration practices by making these available to wider business and IT communities, without having to build workflows from scratch.
In this post, I discuss key decision criteria when it comes to selecting enterprise iPaaS solutions to build a holistic “connected data” ecosystem across PLM and ERP.
Beyond other definitions referring to PLM as a strategy, a process or a tool, I refer to product lifecycle management (PLM) as “the glue between product engineering and project execution (design, development, manufacturing), operations and engineering-IT (…) aligning people, data, processes and technologies.” Therefore, PLM-related business capabilities range across PDM, PLM, MBSE, CAD, CAE, ALM, ERP, MES and other technical solutions. Combining such solutions and associated systems is what enterprise integration is all about.
There is neither an expectation for all data to be mastered in one place, nor the need for all data points to be integrated in the same way. The notion of a “single source of truth” is often wrongly translated as implying one system or platform. In fact, it needs to be applied to the relevant data asset lifecycle—often spanning across multiple authoring sources as data is consolidated, therefore requiring levels of integration for downstream consumption and extension.
Smart automation and fast time-to-benefit are becoming differentiating factors when it comes to integration. Modern PLM, ERP, CRM, MES and other enterprise platforms offer SaaS options to facilitate adoption and provide implementation modularity and flexibility. SaaS integration involves cloud-to-cloud and on-premises-to-cloud interfaces, in a way that drives integration simplification and accessibility.
Like for SaaS, iPaaS platforms are prone to the use of open web APIs typically based on REST (representational state transfer) and leveraging SOAP-like (simple object access protocols) architectures to allow for effective service contract management across cloud- and on-premises based systems. Most PLM and ERP editors nowadays surf on open integration capabilities and the everything- and anything-as-a-service (a.k.a. “XaaS”) business model, though they mostly focus on their capabilities rather than strategic alliances:
- Infrastructure. Flexible storage, computing, network, database, middleware, etc.
- Software applications and platforms. Usage-based capabilities, configuration, extensions, managed maintenance, etc., though, most PLM vendors offer slightly less mature SaaS solutions compared to their traditional offerings.
- Per-integrated solutions within a given ecosystem. Extending into third party partnerships, including few iPaaS providers.
Not all solutions are equal, however, when it comes to capabilities, openness, enterprise architectures, technical architectures and more.
Some PLM editors have recently launched strategic collaborations when it comes to integration:
- As reported by Forrester in its March 2022 paper “The Total Economic Impact of SAP Integration Suite,” SAP offers SAP Integration suite as an iPaaS layer for pre-packaged SAP-to-SAP. SAP also has several public partnerships with multiple iPaaS providers to support legacy-to-SAP integrations and migrations. Some integrations include Jitterbit, MuleSoft, Snaplogic and more.
- On October 18th, 2021, Propel and Jitterbit released a press release announcing a strategic partnership to provide iPaaS extensions for “integrations with ERP providers catering to small, medium and mid-market manufacturers, including NetSuite, Infor and Microsoft Dynamics.”
- On September 29th, 2021, Siemens released the article “Building a Foundation for Our Digital Future: Say Hello to Xcelerator as a Service” where it rebranded their solution portfolio as “Xcelerator-as-a-Service” to mark a strategic focus on integration and analytics—including the opportunity to leverage previous acquisitions of MindSphere, Mendix and Supplyframe.
- In July 2020, SAP and Siemens Digital Industries Software announced a strategic partnership to build standardized PLM-ERP integration—albeit not positioned as an iPaaS solution as such.
Such partnerships are certainly positive steps towards a more open and federated integration capability landscape that provides more thought leadership and “ready-made” alternatives to often expensive and over-customized DIY integrations. There are many more integration use cases and iPaaS partnerships related to ERP and CRM. This is probably due to more advanced cloud maturity compared to the PLM scope. Most PLM solutions carry notoriously heavy legacy inertia, typically due to combined data, process and technical complexity.
Considering integration and a fortiori iPaaS solutions implies choosing a strategic interface architecture to implement functional data flows, covering wider questions such as:
- How are enterprise capabilities architected and implemented, and where is data mastered?
- How do internal and external teams consume data and through which business processes?
- How is data used and consolidated from one authoring application to another?
- How are business analytics gathered at source and shared across enterprise data lakes?
- What front-end and back-end data exchange architecture(s), tool(s), web services and API(s) should be used to build scalable integrations?
- How much can be standardized when leveraging communication protocol connectors and transformation layers provided by commercial off-the-shelf iPaaS solutions?
- What skills are required to configure and customize functional processes and data interfaces, enabling both enterprise “integration developers” and “citizen integrators” to coexist?
- What value is derived from the integration use case from a data consolidation point of view versus pure analytics?
Considering iPaaS does not mean turning a blind eye to what is under the hood and part of the “service.” On the contrary, the fact that certain things will be managed by a third party (in exchange for a fee) implies having visibility to what it is, how it is managed, maintained, shared and scaled, including how this relates to the relevant operational SLAs underpinning the “as-a-service” model.
What are your thoughts?