Explore two project scenarios where a team’s service design goal is to increase the user’s uptake of accreditation.
A project team set out to design a service that would achieve an increase in accreditations in an industry.
The team did user research to understand the problem space. They found that the higher the level of accreditation, the more complex it was for the users to do.
They realised they would need more time and money than their project had. So, they decided to design a scaled-down version to limit the offer to the first level of accreditation.
The project achieved its success measure to be on time and on budget for launch.
The number of users completing an accreditation peaked at two months after launch. After this there was a dramatic drop in accreditation numbers. There was almost no activity at six months post-launch.
In the two scenarios below, the same team takes a different approach to their service design. Their approaches impact the value and outcomes of the project.
In example 2, notice how the team uses research and metrics to make decisions about the service and ensure its success.
Two sprints after launch, Scenario 1's team decided to release its resources to work on another project. This was because they had achieved their success measure, to be on time and on budget.
Shortly after, the number of completed accreditations tapered off sharply. The team hadn’t planned or budgeted for further research after go-live. So, there was not enough resources to understand why the approach failed or how they could improve it.
The sponsors decided that the effort to restart the project was not worth the investment. The service continued to run but its success was limited.
Scenario 2's team did research with their users throughout the design and build phases. They wanted to understand how these users might engage with the service post-launch. They found that the users were a tight-knit community. It became clear that continued user uptake would rely on getting the community motivated to apply for accreditation through word of mouth.
For their post-launch sprints, they did user research to observe user behaviour. They found that users liked the format and idea of the service but became frustrated with its limits. This resulted in users recommending their community against using the service.
The team presented these insights and metrics to their sponsors. The sponsors gave the go-ahead for the full team to expand the service offering. This led to the service exceeding the previous performance benchmarks and becoming a self-sustaining success.