The Haddon Matrix is an extremely useful way to express the
factors associated with a hazardous event and the changes that need to be
affected in the host, the equipment and the environment (both social and
physical). I have covered the Haddon Matrix in a previous post, in fact to date
the most popular post on this blog. I am not denigrating the Haddon Matrix and
its usefulness but recent publications Nassim Nicolas Taleb such a The Black
Swan: The Impact of the Highly Improbable (2007, second edition 2010)
highlight the potential of unexpected, rare events in systems. Taleb does not
believe that effort such be wasted trying to predict these rare events but
rather than robust systems should be devised to avoid the negative impacts of
these events. So does the Haddon Matrix help to prevent hazards or accidents
when a Black Swan strikes?
The Haddon Matrix tends to focus on specific events and
their immediate impact. The ‘classic’ example often seen on the Web is a car
accident where there is a clearly defined agent or host, a clearly defined
piece of equipment and a fuzzy but often clearly defined environment at least
in the mind of the person who constructs the matrix. The matrix is focused on a
particular event usually one that is well known to the person constructing the
matrix. The event is singular and derived from thinking about common scenarios
of ‘what ifs’. Importantly, the event is divorced and isolated from its complex
context. The event is treated as an individual example of an oft-repeated set,
as an individual example of a particular kind of hazard or accident. This means
that the contours of the event are relatively well know, the limited impact and
the limited range of changes that need to be made to the host or equipment
clearly demarcated. The event is somewhat simplified by removing it from its
context.
Rare events can also be considered within the Haddon Matrix
and planned for but events that have never happened or are not within the
experience of the constructor of the matrix can not be considered. A series of
events could be dealt with by interlinking matrices or even by using Reason’s
Swiss cheese model of accidents but each matrix or cheese slice will deal only
with a single event not the interconnected system as a whole not the complex
and potentially unique relations that these rarities activate within the whole
system of which the event identified is only a part. In this case, however, the
accident or hazard itself is actually a chain or web of events operating in
unison under the influence of the rare event. The exact connections in the
system will give the rare event its character. Given the rarity of the event
can you be sure that when it happens again the system will be connected, or
rather interconnected, in exactly the same manner and so will the precautions
that you take have to be exactly the same? As the complexity of the system
behind the hazard or accident you are dealing with increases then the
possibility that impacts will occur via different connections or pathways is
likely to increase. A static Haddon Matrix may not be able to cope with such
dynamism that a Black Swan generates within a system.
Black Swan events may also imply that there are two classes of
hazards or accidents that need to be considered. The first is the hazard that
is known about, one for which have occurred and reoccurred again and again with
sufficient regularity that their characteristics can be well defined and
clearly defined steps taken to prevent their escalation. The second class of
hazards or accidents are those that occur so rarely that each instant is a
novel and unusual case with its own set of peculiar characteristics. These events
are so infrequent that no reasonable plans can be made to prevent them. It is only
after they have happened that we can understand why they happened, what aspects
of the system were compromised and then take steps to ensure that the same
pathways to failure do not happen again, although the next Black Swan event may
be so different as to circumvent our efforts.
If the Black Swan, almost by definition, falls outside the
experience of the matrix constructor then is the matrix of any use in these
cases? Black Swans may not be predictable but that should not stop attempts to
build a robust system to manage impacts. A densely connected system is likely
to transmit impacts rapidly from one part to another, maybe along channels or
by connections that can be predicted as weak links or pinch points. Ensuring that there are ‘firebreaks’ in the
system, potential break-points in its connectivity, could help prevent a
systemic failure even if the exact nature of the rare event is unclear and
unpredictable.
