Systems Engineering is all about using defined methodologies and approaches to design and create solutions for various transdisciplinary problems to manage complex systems over their life cycle. It is intended to transform stakeholder needs into a balanced system solution.
It is most popular for complex system design industries, such as aerospace, nuclear and medicine. However, the principles can be applied to all sorts of different design situations! 
Systems Engineering Approach
This systematic methodology can help to organize how we create solutions, provide us evidence that we need to prove to stakeholders that our solutions are necessary and can provide us the language to collaborate with our engineering partners.
Step 1: Identify Your Need
Clearly define your solution’s purpose and set your ultimate goal. Understanding the need is the first step towards finding the most effective solution.
Step 2: Leverage Existing Resources
Before reinventing the wheel, explore existing solutions that can be repurposed or adapted to meet your requirements. This helps optimize time, resources, and cost.
Step 3: Design with Precision
Conduct in-depth research, analyze alternative options, and consider the possibility of developing cutting-edge technology to address the challenge at hand.
Step 4: Rigorous Testing
Validate your design by creating a prototype to verify its efficacy before moving on to full-scale implementation.
Step 5: Building & Development
Carefully select materials and software that align with your goals and budget constraints, ensuring a seamless execution.
Step 6: Verification
Test the solution in real-world scenarios, ensuring it performs effectively in the context of its intended use.
Step 7: Operate & Decomission
Identify operating requirements, maintenance schedules, and sustainable practices for eventual decommissioning, ensuring the lifecycle of the solution is managed responsibly.
By adopting a Systems Engineering approach to design, we can optimize the problem solving process! By using a process like this it can help us avoid errors and invalid assumptions, help to manage real world changing issues and produce a robust solution!