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Community Risk Methodology, Process, Approach

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Community Risk Methodology, Process, Approach Community risk Methodology, Process, Approach Developed and maintained by the NFCC Contents Methodology, Process, Approach .......................................................................................................... 3 Good Practice ........................................................................................................................................ 3 Gaps ........................................................................................................................................................ 7 This content is only valid at the time of download - 25-09-2021 20:56 2 of 9 Methodology, Process, Approach Good Practice FRS Submissions which generally generated positive responses from the TWG were those that not only provide sufficient detail for review but also demonstrated a structured approach towards RMP which is the service’s golden thread throughout all of its decision making. Key to this is demonstrating how a FRSs risk assessment flows through and leaves a footprint in all areas of the RMP, informing activities and decision making: Nottinghamshire West Midlands Cornwall Cleveland Lancashire East Sussex Royal Berkshire A number of TWG members have noted the overt role Strategic Mangers/boards play in developing their RMP, with this engagement deemed important in overseeing the development of RMPs: West Midlands Cornwall South Wales East Sussex Avon Overall the TWG found that all FRS submissions, where sufficient detail was provided, utilized a range of local, regional and national data throughout the RMP process and is an important part of its methodologies. Whilst certain data sets and sources feature widely throughout the responses (mainly government and incident data), the TWG found significant evidence of FRSs seeking out data dependent on its own needs, whether this be through partnerships or multi-agency data sharing: Northumberland Devon and Somerset West Midlands Warwickshire South Wales This content is only valid at the time of download - 25-09-2021 20:56 3 of 9 Hertfordshire Cheshire Merseyside Bedfordshire East Sussex Royal Berkshire Surrey Avon Humberside As a result, TWG members quoted the use of information from external sources as good practice to underpin risk assessments. Whilst a full list of datasets can be found elsewhere in this report, the good practice drawn out by TWG members is the level of data used to make decisions, inform risk assessments and evaluate activities is good practice as it provides a stronger evidence base to work from whilst providing an audit trail of decision making and rationale. Setting aside national frameworks and datasets, good practice was found in the use of research when informing decisions made throughout the RMP process. Research has been identified by a number of TWG Members to have been used across RPP to both confirm or inform data analysis and decision making which has been undertaken as part of the FRSs RMP process: West Midlands Warwickshire South Wales Although in some cases the research is not detailed enough to form an opinion of its robustness or is targeted at specific areas. Of particular note is the use of research to inform response standards, with the strongest use of research linked to decision making being a look by a FRS at the response cycle from the point an incident occurs to the point an intervention needs to have taken place West Midlands TWG members have pulled out the use of software by FRSs as good practice but more from a perspective of risk modelling and also ‘what if’ software which FRSs use to predict the impact of a decision around RMP before making it: Nottinghamshire West Midlands Leicestershire Hertfordshire Tyne and Wear Avon The good practice here therefore is the use of software to not only aide decision making in the This content is only valid at the time of download - 25-09-2021 20:56 4 of 9 current tense, but also to understand the impact of future decisions. Geographic information systems (GIS) are widely used by FRSs to utilize data in a geographical way which helps target RPP activities and the distribution of resources: Nottinghamshire Northumberland West Midlands Cleveland Lancashire Cheshire Buckinghamshire Avon However, TWG has found that how FRSs utilize GIS systems differs, with some FRS utilizing it to map demand which drives positioning of resources: Northumberland West Yorkshire Cleveland Leicestershire Lancashire whilst others use demand data against other data sets such as IMD or Experian to map at risk people/communities (i.e. people based on characteristics): Nottinghamshire Devon and Somerset Cornwall West Midlands Cleveland Warwickshire North Yorkshire South Wales West Sussex Northamptonshire Tyne and Wear Cheshire Merseyside Buckinghamshire East Sussex Royal Berkshire Surrey This content is only valid at the time of download - 25-09-2021 20:56 5 of 9 Avon Humberside The benefits of the latter being a greater foresight of future risk. However, the underpinning good practice regardless as to whether the opinion is risk or demand comes from the ability of FRSs to drill down into the data and create risk profiles down to ward or LSOA area which allows for FRSs to be more efficient and effective at targeting its RPP activities: Nottinghamshire Devon and Somerset West Midlands Cornwall Cleveland Warwickshire North Yorkshire South Wales West Sussex Northamptonshire Tyne and Wear Cheshire Merseyside Buckinghamshire East Sussex Royal Berkshire Surrey Avon Humberside Where this has helped is the ability of FRSs to categorise communities, businesses, people and buildings in a hierarchical way which determines high, medium and low risk and influences decisions around the type of activities undertaken and the distribution of resources. There was evidence drawn out of the submissions by TWG members that a number of FRSs take an active look at future risk through looking at the profile of risk and future likely needs of their communities: West Midlands Northamptonshire Hertfordshire Cheshire However, this was largely limited to projected figures around population increases, demographic This content is only valid at the time of download - 25-09-2021 20:56 6 of 9 makeup of communities and housing developments that have been identified. Gaps Whilst FRS generally provided an overview of their approach to RMP, the work of the TWG was limited by the level of detail provided. A caveat to the narrative below therefore should be that where the submission was not detailed enough this may have presented gaps which under closer scrutiny a FRS may have filled but just not submitted it to the Research Project. The role of strategic boards and managers was highlighted as good practice by TWG. However, the gap that has been identified based on some submissions is the competencies, knowledge and understanding that is required in order to develop an RMP at all levels. This ranges from strategic level through to the practitioners actually developing the RMP with 2 submissions specifically raising skillsets in compiling RMPs. The use of data is widespread and has been identified as good practice by TWG. However, the detailed description regarding the use of data within a methodology or approach has been limited or absent from many submissions which has impacted on the ability to understand whether it has been applied or handled correctly. In addition, the quality of data is unknown although on a number of occasions the data sets are those used by other agencies. Whilst TWG members have highlighted as good practice the process of RMP being joined up and the use of data, there have been gaps identified which suggest that the lack of evidence, data or research at points throughout the RMP process impacts on the quality and robustness of decisions and planning assumptions made further down the line within the RMP process. How this fits together during the RMP process has also been flagged by TWG members, for example a number of submissions would suggest to the TWG that weightings based on severity of injury are given to risk types when mapping risk geographically in their RMP. A problem identified with this is the lack of detail around how FRSs approach this weighting and also get around a scenario whereby an area suffers a fatal fire but is generally low risk, against an area that may not see many injuries or deaths but has a higher frequency of incidents. Although research was mentioned to be used by FRSs, this was only the case in a limited number of cases (4), suggesting a significant gap in research may exist across the sector. The absence of either data or research limits the evidence base sitting behind decision making. One area where this was evident is knowledge and use of research around the response cycle to inform decisions around response standards. There is little evidence to show that when basing its decisions around response time standards that these are linked to an evidence base, but instead more based on what is achievable with the resources a FRS has and which is available. It is this that PIs would appear to be focused around. This content is only valid at the time of download - 25-09-2021 20:56 7 of 9 Very limited FRSs have overtly detailed what, if any, its approach is towards horizon scanning and how its RMP process takes into account any future change in risk and how they ensure they are able to react to it in a timely manner. In total only 5 of the 41 submissions assessed by the TWG explicitly detailed the approach taken to identifying future risk and demand. Whilst not detailed specifically in the questions reviewed by the TWG, evaluation was distinctly absent from the responses in all but a few submissions. Whilst only raised explicitly in 4 submissions, there is a general view of the need for greater evaluation of all activities which is also a requirement under national frameworks. Whilst few FRSs did refer to the use of evaluation for its prevention, protection and response activities the robustness of these processes is unknown as some of these FRSs have designed in house evaluation measures or are utilizing out of date data sets (economic cost of fire).
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