Importance of data in our user centred design process
Written by Sonia Rides
Hi I’m Sonia and my role in the Digital and Service Design team is Information Specialist. I work with Lottie, the Information Officer to ensure that our service design projects are data driven and any new solutions provide business intelligence needed to drive continuous improvement.
As a service design team we work in collaboration with staff, partners and members of the community to co-design and deliver the services needed to work efficiently with the resources we have to achieve our outcomes. Data is key to any service design project. Without data we are only guessing at what customer needs or wants are, and how we can make the service more efficient. We need to look at the root cause of the problems in each case to identify true efficiencies and develop long-term sustainable solutions. For larger problems data can help focus scope and help us work in an agile way by identifying the small areas where improvements will have a big impact. Data helps ensure that we are fixing the right problem in the right way.
We are adopting the 4 stage agile approach, which emphasises the importance of data in any project. These 4 stages are: discovery, define, develop and deliver. Data is needed throughout these different stages of the project to support and evidence the service design, benefits rationalisation and return on investment. Two noticeable projects where data has made a big difference is our noise and failure demand projects.
Work has recently finished on our noise project to transform the way that noise is reported and handled by our residents. Very little data was available at the start of the project so it was difficult to establish information about the type of noise complaints being made and identify patterns in order to target resources and reduce demand. By the end of the project the service had moved from being reactive service with all noise complaints treated in the same way regardless of severity or resident’s needs, to a service that reduced demand by giving customers the tools to deal with some noise issues themselves where safe and appropriate to do so. Where intervention was needed by the council, we now have the data regarding type of noise, severity, time of day and impact to be able to establish patterns and target enforcement action.
Data has also been heavily involved in our on-going Failure Demand work which is looking at reducing the number of times bins are reported as being missed. Data helped us to quickly establish container deliveries and missed bins as the high volume areas for customer demand which were taking staff away from the normal schedule of work. This led to us being able to target our efforts and focus on the areas which would have the biggest impact and to break the work up into manageable chunks. Further analysis highlighted the high number of missed bin reports which are withdrawn, usually due to bins not being presented on time or on the wrong collection day. That helped identify work streams for education, enforcement and of the reporting process and form used to reduce the number of reports being made where the bin wasn’t actually missed or where a previous report had already been made about the same collection.
Once we started to try and drill down on reasons why bins were missed, it became quickly apparent that this level of intelligence was missing and that data quality needed to be improved to successfully reduce demand. A sub-group for data was established to identify ways to improve the data quality and increase the intelligence the data could provide so we could better understand the reasons for why bins were missed. This would have a two-fold benefit to both the customer who would see a reduced number of bins being missed and free up the time of the service spent dealing with missed bins. Simon, one of our developers, has also been working on a prototype for a missed bins dashboard to give staff the intelligence they need to identify patterns, root causes for missed bins and improve service efficiency. Work is still ongoing and there is a lot to do but there should be huge benefits to the customer experience and service demand.
