How we took a service design approach to create an event for over 100 students.
130 students, one week
When The Data Lab came to us with the challenge of creating an event for 130 of their Data Science students, we knew that the project would be split into two parts. One would be facilitating the event; getting the students to combine design thinking and data science to create solutions to real-life problems.
The second would be actually running it.
The thought of having over 100 students, external guests, clients, and staff all together in one room for five days was a challenge. So, we asked ourselves: “How do we service design The DataLab Innovation Week event to make it easier for everyone involved?” In short – How do we do an event the Snook way?
Research, define, develop, deliver
At our kickoff meeting, we met our clients to understand their needs, their objectives, their budget, the timeframe, and any resources that were already available. This enabled us to understand the root cause of the underlying problem that our clients wanted to solve.
It was important for us to think of the whole event from an end-to-end perspective so that we do not omit any significant stage in the process, for all the different stakeholders involved. Next, we moved to developing a blueprint skeleton of the event.
The horizontal axis of the blueprint comprised of the different phases of the event while the vertical axis encompassed the back-stage, mid-stage and, front-stage stakeholders. We were then able to identify any touch points, including communication channels and processes, to support the front stage experience. Our blueprint skeleton enabled us to clearly assign roles and responsibilities to each individual, giving everyone involved a sense of accountability and transparency.
Prototyping remains one of our favourite mantras when it comes to service design. In this instance, we had to think of scaling up. In the past, we have run smaller but similar events like the CycleHack and Global Service Jam. We reflected on our previous experiences, taking into account what sessions worked well in the past and what could be improved and tweaked to accommodate more participants.
Logistics, logistics, logistics
The logistics aspect of the event was BASED around mitigating risks and preparing well in advance. For instance, ordering stationery, contacting caterers, and small things like checking that the tea urn was working days before the event helped in risk management. During the event, we also set some rhythms and rituals. These included morning and afternoon check-ins that resulted in effective cross-team communications. These check-ins served as a safe platform to exchange feedback that consequently aided in better preparation and delivery of the following day’s sessions.
Practice means improvement – not perfection. The DataLab Innovation Week event reinforced the notion that service design is an iterative process. It taught us that our service design role did not end once the event began, but rather was the ultimate test for the hard work and planning we had put in. In design thinking it is said that there is not such thing as your final prototype, only your latest iteration – and whether your prototype is a product, service, or event you never stop learning from doing and testing.