SESAME
Finding ways of improving SME response to flood events
Dr. Graham Coates
The Challenge
Flooding can significantly degrade the operational performance of Small and Medium
Enterprises (SMEs), which in contrast to large businesses often do not have the resources
and formal continuity plans in place to aid an efficient response and speedy recovery. Given
that SMEs represent 99.9% of the UK's private sector businesses, employ approximately 60%
of the UKs working population and contribute almost 50% of total annual business turnover,
their ability to plan, prepare and respond effectively to flood events is vital to the UK
economy. Early suggestions in our research indicate that few SMEs appear to have formal
structures in place regarding the continuity of their operations during a flood and its
aftermath. The SESAME project is taking a multi-disciplinary approach to investigate how
SMEs might become more resilient to flood events, in particular how they may improve the
way in which they respond to such disruptive events.
Our Approach
In order to find ways of promoting better responses to flooding for SMEs, the SESAME
project aims to investigate how these businesses currently deal with floods, and how they
might change or adapt their behaviour to lessen the impact of floods in the future. To
ensure the challenge outlined is approached from a rounded perspective, the SESAME team
involves academics from a range of backgrounds operating from different research centres
around the UK.
To date, team members from
the Universities of Durham and
Leeds
have
focussed
on
developing software capable of
modelling any geographical area
of the UK and identifying
businesses within that area
impacted by flooding based on
inundation prediction data. The
SESAME team has selected the
Lower Don Valley region of
Sheffield in South Yorkshire as a
case study area, which is illustrated opposite. Reasons for this choice of area include its high
concentration of SMEs from a range of sectors allied with their experience of significant
flooding in 2007 when approximately 100mm of rainfall fell in only 24 hours having a
devastating impact on more than 1000 businesses. Colleagues at the University of Sheffield
have carried out interviews with a range of businesses in the Lower Don Valley, which will
form part of the input to the agent-based modelling and simulation aspect of the project.
Other research carried out at the University of Leeds has involved a review of several
quantitative methodologies related to the economic impact analysis of flooding. Researchers
from the Universities of Kingston and the West of England have conducted pilot interviews
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aimed at gaining an improved understanding of the adaptive responses of small businesses
after they have experienced a flood event.
The Benefits
As alluded to earlier, the aim of the SESAME project is to develop a capability to model and
evaluate SMEs' current flood response strategies and investigate the potential of new
strategies, incorporating business continuity plans, such that recommendations can be made
that may influence changes in the way in which these businesses plan and prepare for flood
events thus enabling them to better respond in the future. Thus, the output from this
research will enable the SESAME team to advise SMEs in flood risk areas on how they might
improve their preparation and response to floods, which will empower them to become
more resilient and help them reduce the impact of future flooding.
Future Work
Amongst the several strands of the SESAME team's research, the current study of SMEs in
the Lower Don Valley region of Sheffield will continue, as will interviews of businesses in
other suitable case study areas. Also, work has started in the area of developing agents to
model SMEs based on interview data and literature. Flood modelling will be performed in a
dynamic sense so as to include the temporal element to inundation prediction within future
agent based simulations.
More Information
The SESAME project is led by Dr Graham Coates at Durham University with a multidisciplinary team consisting of academics from the Universities of Kingston, Leeds, Sheffield
and the West of England. More information about the research and team members can be
found at the SESAME website (http://sesame.uk.com).
Sources of Funding/Acknowledgments
The SESAME team gratefully acknowledge the funding for this research which is
provided by the UK's Engineering and Physical Sciences Research Council under grant
EP/K012770/1.