Publications from ODSW Social Insights: Letters by DSW (Vol 2) | Page 124

Practice Issues
the development of effective plans or the delivery of the service. Measures
such as ‘improved emotional well-being’ or ‘improved quality of life’ are
hard to measure and require good longitudinal studies.
It is more realistic to collect data about the intermediate outcomes
achieved. These could be data such as one’s readiness for work, how skills
and confidence have improved or the level of increase in exercise.
How does one then improve on the analysis? If you are dealing with enough
numbers, segment the data according to user profile, frequency/ length of
use of the service, access to other services/ training and other important
factors as this information may suggest significant differences. The
information may also throw light on any bias in the sample. For example,
older people may not have responded in the sample. This then needs to be
further examined. This cross analysis may then help in understanding what
some of the key factors in achieving improvements are.
It is therefore useful to consider what aspect of the service or intervention
was most or least useful or important, what other factors were important in
achieving change and what factors acted as barriers to achieving change.
At the heart of this is recognising that it may not be possible to establish cause
and effect, or to attribute the change entirely to the programme. What you
may be doing is establishing how you contribute to a web of interventions
which together enable more long-term and sustainable change.
When referring to benchmarking, outcome and impact, it is still more
constructive to describe the meaning and parameters for purposeful
discussion as various parties may bring with them different meanings.
Good programmes and exchange of views often take place when ideas
and concepts are kept simple, contributory and causal factors are clear
and achievement or credit are kept circumspect especially when we are
delivering human services.

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