Problem 2: We don’t think we’re making the most of all the data that we have
To begin tackling Problem 2, data analysts from over 30 different fire and rescue services came together for a workshop in London. The aim was to test this problem and understand more about how data teams operate within their organisations, what they spend their time on and the main issues they encounter working with data.
Figure 2 below is a snapshot of the make-up of the FRS data analyst teams. It suggests analysts stay for a long time in the FRS (11+ years) and work mainly in small teams of 2 - 5 people.
Figure 2: General statics of data analyst teams within the FRS based on survey responses.
There were many valuable learning points from the day. One reoccurring theme was effective resourcing. Many analysts felt too much time is devoted to data processing that can be automated, consuming resources that could otherwise be devoted to developing insight and understanding impact of data. This is illustrated by the chart in Figure 2 which summarises the percentage of attendees reporting how they spend time on specific tasks during a typical day: developing insights and performing trends analysis received the lowest number of responses. As may be expected the impact is greater in teams from smaller organisations that are often tied up performing day-to-day tasks such as cleaning incorrectly submitted data or responding to requests for reports.
Another notable idea raised on the day was professional recognition for fire analysts. The services may benefit from this idea in several ways. Formal accreditation of fire analysts would help to instil standards for data analysts across the fire and rescue services, while establishing career pathways and an opportunity for the services to support and recognise career achievement. It would also help to foster an organisational culture that values the importance of data and insights in evidence-based decision making.
Furthermore, it was felt that data competencies were not limited to those in data roles. The analysts agreed that an appropriate understanding of data was needed across the organisation from firefighter to Chief Fire Officer to ensure the right questions are being asked and that the right conclusions and decisions are being made.
Feedback from the event helped inform three data-specific problems for the program to focus on, all based around maximising the value of current data.
The three data-specific problems that were identified are:
- Outdated Incident Recording System (IRS) – the IRS is clunky and inaccessible making it hard to use aggregate data for improved policy making
- Lack of consistency in data standards – we do not have an open data standard for fire so sharing data is hard
- Lack of centralised data – fire and rescue services hold data locally so getting an aggregate view across all organisations is impossible
Work has begun on these challenges.
To address problem 1 the DDP is engaging with the Home Office, the custodian of the IRS, to explore what may be done to unlock IRS data for fire and rescue services.
Problem 2 is being tackled on a number of fronts. In collaboration with the NFCC Community Risk Programme, the DDP is investigating what third-party datasets would support improved identification of risk and vulnerability in local communities when integrated with FRS datasets. The Unique Property Reference Number (UPRN) is a standard for location data and could be used by services to connect disparate datasets to their local datasets - an idea explored in the UPRN workshop.
To explore problem 3, the DDP will seek to explore and develop proof of concept opportunities to bring together relevant national datasets. A national analytics capability could allow analysis to be conducted on the aggregate data and provide potentially new insights to local services and allow them to see their data in the national context. To achieve this, the DDP will seek to scale and leverage existing FRS systems and compare to those offered by the wider market to evaluate function, performance and cost.