To measure success of a complex concept can be as complicated as compiling the variety of the individual elements that underpin the model.

We can certainly prove that Speedwatch is a successful scheme when conducted under optimal conditions. However, to best describe this success can be more difficult than explaining the fundamental premise of the scheme. For example, how do we measure the successful involvement of communities vs. evaluating the impact on lowering average speed in what we consider a well-organised area compared to a less so? How do we define the quality of what constitutes achievements under these different circumstances?

With the extensive datasets collated over five years available to us, we discovered and defined specific benchmarks of success. We believe these are strong indicators of achievements, trends, and clear-cut results. However, to others the numbers could be interpreted differently dependent on the individual viewpoint taken in the debate about where responsibility for road safety lies, and what the common main objective is - if there is one. Some people might think that the lowering of the number of killed and seriously injured supersedes that of the lowering of average speed achieved by other means or only in specific areas. Some would disagree whereas we would suggest there is causation or correlation.

Because speeding is such a difficult issue to address uniformly (people speed for different reasons, at different levels, and at different times, and places), we might be able to demonstrate a significant reduction of repeat offence observations over time, but is this a genuine expression of behavioural change, or is it just indicating an awareness of the potential consequences of being caught by local groups in a certain area? Our stats cannot give a definitive answer to all of these speculations, only indicate trends. However, some of the trends demonstrated in our findings are very persuasive.

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