Connected product engineering: what’s really needed for IoT product development?
We are bombarded by news about the IoT and how it will change our lives—and, how product makers will need to change to keep up. But what does that really mean for product design and engineering processes?
More connectivity means more complexity in the form of increased dependencies (or interdependencies) in product designs, which leads to a greater need for requirements management and change management.
A big challenge facing companies moving into the IoT space is simply how to deal with all this new complexity. Systems engineering is a proven way of tackling the potentially overwhelming complexity of developing highly interconnected systems. Systems engineering has been around in industries such as aerospace and defence since the Apollo program in the ‘60s. Now it needs to be adapted and implemented in many new industries participating in IoT product development. For further thoughts on this topic see the recent article, Systems Engineering and IoT.
Designing and engineering connected products involves a greater number and variety of people in the organization, creating a need for more collaborative tools, and the ability to easily share information geographically, organizationally and between tools. In turn this means:
- Web and cloud based tooling – available anywhere, with the security to ensure that only the authorised eyes have access.
- Collaborative processes – where roles, workflows and deliverables are clear to everyone—so everyone knows what’s required and what’s needed to achieve the requirements in real-time. Again, web/cloud-based tooling allows all stakeholders to interact with project information at any time, regardless of geographical or organizational barriers.
- Tools that can share information – so disciplines such as requirements management, architecture and design modelling, and quality management, which are very interdependent activities, can share information as openly as possible. Open technology initiatives such as Open Services for Lifecycle Collaboration are key to making this a reality. To ensure that product engineering is an optimally holistic activity, this sharing needs to link domains such as systems engineering, embedded and application development, and product lifecycle management.
Lastly, the IoT context fundamentally changes the dynamics of product engineering. For the first time, operational and usage data and analytics from connected products are now available to the engineering process. This feedback loop provides visibility into product performance and usage patterns, so engineers can validate design assumptions, and gain insights to factor into the product roadmap. Meanwhile, customer expectations are becoming dramatically heightened. It’s natural to think, “My smartphone apps are updated every day to fix bugs and to do new things—why not my IoT products?” These changes are driving a paradigm shift from research, then design, then make to continuous product improvement. Importantly, this shift must balance discipline in engineering practices to ensure confidence in the outcomes with the required pace of development to deliver competitive products with optimal speed to market. To accomplish this, organizations need:
- An IoT feedback loop built into your business to provide uninterrupted information flows throughout the product lifecycle, not just between development engineering tools. This includes: (i) the ability to flow product operational information to analytical tools, and from analytical tools back into development processes, and (ii) the ability to flow software updates into the field at any scale of product deployment.
- Agile engineering methods (for systems engineering and hardware development as well as software) – the ability to respond rapidly to new information and changing requirements and to continuously reprioritize engineering and development tasks to optimize the use of engineering resources.
- Dependable engineering automation everywhere – from capturing traceability between all engineering artefacts, to automated testing, automated transformation of engineering information such as code generation, and finally automated documentation to help with compliance.
This blog is just a whistle-stop tour of some of the key areas in which product engineering is evolving to meet new challenges. Each point could be the starting point for a more in-depth article. But I’ll leave that for later posts. In the meantime, take a look at these resources: