Learnings

Outcomes

The outcomes of the project include: 
 
Insights from the user research were captured and helped design the trial: 
All interviewees ranked information about accessing priority services last when asking what type of information they wanted from a power cut notification. This included an equal split between those that self identified as requiring priority services and those that hadn’t. A decision was made to not differentiate the customer experience for users that are registered on the UK Power Networks Priority Service Register (PSR).  
Users preferred SMS, push, and email notifications, but they expected to be able to opt-out of specific notification types individually.  
Users mostly wanted to be informed of the following: 
Start times 
End times 
Status updates 
Whether the outage was planned or unplanned 
Users are aware of the options available for alternative charging locations and used other services that specialise in this.  
Most users were happy with the power cut affected area being referred to as an ‘area’ and some preferred to include the postcode in the notification. 
The project tested the solution with up to 500 EV customers (including vulnerable customers) prior to the deployment of the final API.  
A trial was run for three months, and 82 customer insights were captured from participants. Insights were pivotal to understand the customer journey for EV charging during power cuts, the risk factors contributing to quality of life, and the stress around EV charging access. Insights included: 
Further validation that enhanced notifications were unnecessary:  
Users that identified with the PSR characteristics were found to be less concerned about power cuts and didn’t require enhanced notification experience. This was because they were naturally more prepared for such eventualities with flexible work arrangements, not being reliant on one car per household, or having support in place.    
Accuracy of notifications:  
Most users reported they did not experience a power cut despite being notified of one. This was due to the location logic that had been set for the area was at a postcode sector level (e.g. SG11 1__).  
It was agreed that full postcodes would be used in the final solution, thereby narrowing the impact radius of faults.  
Insights on how useful the tailored notifications were to EV customers:  
SMS continued to be most desired channel to receive power cut notifications.  
94% of respondents said they would still be happy to continue receiving notifications based on sector level postcodes.  
78% of respondents said they were glad to be kept informed.  
A standalone API has been published on UK Power Networks’ Open Data Portal for ev.energy and other third-parties to utilise.  

Lessons Learnt

The approach to conduct a) user research, b) run a three-month trial, and then c) implement a final solution based on the learning was a simple and effective methodology.  
 
The methodology was tuned rather than changed to respond to the insights that were captured. For instance:  
The initial user research was planned to only be a survey, but it was decided to conduct some face-to-face interviews to explore more detailed questioning based on the feedback from the survey.  
The user research had prompt responses and good engagement which was possibly influenced by the incentive of £5 vouchers offered.  
The technical implementation of the trial used an existing API that serves the UK Power Networks power cut website, and ev.energy developed the trial power cast mobile app to pull the data from this API. This allowed us to quickly get to a usable solution and validate where any gaps or modifications to the data or API might be required. This was very successful but with one modification. The trial was originally planned to be run with 1,000 participants, but instead we took an approach of a slow, scaling of the trial from 25, to 50, to 100, and ultimately to 500 users involved in the trial. The trial stopped at 500 because we learnt that it was notifying users that were not affected by the respective power cut. This was due to the scope of data being too broad as at a post code sector level (XY01 0) and needed changes that were not possible to implement in the trial period.  Therefore, the trial was limited to a total of 500 participants and not the target of 1,000 but the learning informed the final design. It was deemed unnecessary to increase quantity because there were no further insights to be gained by scaling.  
 
The final solution design accommodated the trial feedback by creating a dedicated dataset from the live power cut web site to allow a specific set of filtering. The filtering removed any postcodes with single properties and therefore allowed faults to be shared at the post code level rather than post code sector. This was achieved following investigation and design with the data protection team and the enterprise data management team in UK Power Networks.