Case Study: EON Optimum
The EON Optimum platform allows industrial, commercial and retail customers to visualise and optimise energy usage across their estates.
I was primarily responsible for the machine learning elements of the platform. I also sat on the EON architecture group. My main achievements include:
- Bringing the development in-house (from a consultancy)
- Recruiting and mentoring the team members
- Taking a POC to production
- Migrating clients from a legacy system to the new platform
The major challenge lay in understanding the functional requirements of the product. Whilst there was a general product roadmap, the details were unclear. Often it fell to the development teams to decide what the product should do, not just how it should be done.
The platform is primarily built in Scala with some Java and Kotlin (Spring Boot). It runs in the Google Cloud.
- Java, Kotlin, Scala
- Angular js
What did I learn
The importance of solid requirements, planning and strong management. Hiring great developers is not enough, they need guidance and focus. In particular “the business” needs to be clear about the product roadmap, goals, milestones and ROI.On a technical level, the developers need clear standards and a degree of oversight. Building a product of any size needs planning and management.
The agile “self-organising” concept has limitations:
- It only works if the team members are on the same wavelength, in terms of skills and experience
- It only works for small teams
- It doesn't work well across teams
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