Context on SDGC
The Service Design Network Global Conference (SDGC) was recently held in Dublin, Ireland. A truly global crowd with varied skills and experience participated in three days of talks, workshops and award ceremonies. I took advantage of the discounted public sector tickets to fuel up on inspiration and celebrate some excellent and thought provoking work. These are a few of the learnings I’ve brought back to the Service Innovation Lab. For more of what was covered at SDGC see the slides and videos of the talks.
For those new to service design or wanting inspiration Uscreates have partnered with BBC Radio 4 show The Fix to give an expose on how design-thinking works in action on tough social challenges. The show gives insight into all the small but significant actions designers do from talking to those involved to pitching ideas and all the pivots in between.
At the Service Innovation Lab we’re big advocates for working in the open and this collaboration captures the process and story in a way anyone can follow; and is an example to aspire to.
Designing with Data
Data was a common topic of presentations, workshops and conversations at SDGC. Trust, transparency, control and reputation are priority factors being considered when designing data driven services and are becoming an emerging economy of sorts themselves. Facebook-supported TTClabs.net have created a trust, transparency and control toolkit for “Improving user experiences around personal data” co-designed through a series of international ‘design jams’.
The website is full of tools, insights and patterns for building better digital services and a step-by-step guide on running your own ‘jam’.
Our ability to understand and communicate how data is informing our design process is critical to designing more innovative and resilient services. This is dependant on partnering with other disciplines with expertise in collecting, defining, analysing and representing data. While our relationship with data scientists in particular is symbiotic to how we understand problems, and also design and test solutions, we still need to find a common language to better bridge these silos. Anne Dhir from We are Snook says it’s important to design services with both data insights and design insights. Their approach: using design methods such as journey mapping and shadowing to understanding data like you would people, is a great starting point for those new to this space. This process has helped them define a bunch of research questions to challenge assumptions and motivations around data collection and use. One example they have is the responsibility of managing and protecting this data essential to deliver an effective service? Keep an eye out for their work within the UK public sector.
Design for Machine Learning
Artificial Intelligence and Machine Learning (ML) are emerging technologies many service designers are trying to wrap their heads around. I was excited to learn more about how to keep them in mind and what to watch out for through the design process. A workshop run by Futureice cut through the hype associated with the tech and shared a quick approach for assessing the suitability for ML and ideating its applications. They break ML into four use cases, Predict, Personalise, Recognise and Uncover Structure. Within an hour their data scientist and designer had us “learning to dance with machines” and I left with clarity and confidence to explore ML further.
Give it ago yourself Iadesignkit.com and look out for a workshop at the Service Innovation Lab in the New Year.
Engagement, Collaboration, Service Innovation Lab