Engineering change is one of those disciplines that looks technical on the surface but is really about how people, process, organisation, and systems fit together. Broadly speaking, engineering change governance spans four perspectives:
- Technical perspective — Change management systems, PLM/ERP/MRP platforms, CAD/CAM/CAE and PDM systems, with their technical interfaces.
- Organisational perspective — Decision-making structure and governance, modus operandi, approval flows, and organisational structures.
- People perspective — Skills, competencies, training, certification, learning, lessons learned.
- Enabling process perspective — Portfolio management, resource management, knowledge management, digital automation, performance management, manual processes — all the connective tissue across a wide array of business use cases.
Business first, system second
Not everything can or needs to be integrated or automated. Digital enterprise platforms support the management of complexity and provide operational traceability — but small or large improvements all require a strong focus on how people operate, what they formally and informally do day-to-day, and how they collaborate and share data.
In a digital transformation or continuous improvement context, it's often advised to "first change the people — improve existing processes and educate users before considering new systems" (Grealou, 2019). The ability to change is mostly about the people aspect: the ability to learn and, ultimately, to connect the dots across processes, data, and systems.
Practical requirements for ECM that actually works:
- A governed ECM process with stage gates to drive stakeholder alignment.
- A consistent, controlled approach to provisioning solutions — from business requirements through to processes, culminating in system capabilities and features.
- Robust, reliable system implementation steps (test, deploy, pilot, fix, go-live), typically enabled by a robust DevOps pipeline to streamline how changes are deployed and adopted.
- Real-world, pragmatic use cases to test system connectivity, functionalities, and integration layers.
- Effective user training and support, to ensure continuous learning and relationship-building.
Automation is an enabler, not a business goal or a uniform requirement across all enterprise IT systems. Systems and their technical interfaces alone aren't the answer to everything. Technology ultimately needs to be "humanised" — integrating people's points of view into the wider perspectives, supporting them in distinguishing the useful from the worthless, and providing solutions that genuinely enhance user experience.
What are your thoughts?
References
Government Data Quality Hub (2021); Hidden Costs of Poor Data Quality.
Grealou L (2019); First Change The People, Then Digital; virtual+digital.
