Causal Chain Analysis (CCA), often also called Root Cause Analysis (RCA)[1], is closely related to systems thinking[2] and the DPSIR approach[3].

At its most basic, a causal chain is an ordered sequence of events linking the causes of a problem with its effects. Each link in the causal chain is created by repeatedly answering the question ‘Why?’ A simple schematic showing the major components of a CCA are shown below in the Figure below.

CCA is predicated on the belief that problems are best solved by attempting to address, correct or eliminate root causes, as opposed to merely addressing the immediately obvious symptoms. By directing corrective measures at root causes, it is more probable that a recurrence of the problem will be prevented. However, it is recognized that complete prevention of recurrence by one corrective action is not always possible.

Unlike systems thinking which focuses on the dynamic and complex whole system interacting as a structured functional unit, CCA approaches have historically tended to be used in a linear manner, examining cause and effect. However, although often displayed in a linear fashion, it should be remembered that a causal chain is a component of a policy response system, which by its very nature is cyclical. See below:

For the purposes of GEF IW projects, CCA is likely to be the most appropriate approach for analysing cause and effect as it is a relatively simple, robust and informative process. Systems thinking approaches - such as Systems Analysis (SA) or causal loop diagrams (CLD) can be attempted but will require a much great input of time and resources.

[1] thwink.org - Finding and resolving the root causes of the sustainability problem.

[2] Donella H. Meadows, 2007, THINKING IN SYSTEMS a primer, Sustainability Institute.

[3] Peter Kristensen, 2004, The DPSIR Framework, European Topic Centre on Water, European Environment Agency