Sean posted an interesting comment in response to my post about Simpson's paradox. His question was
How about another research paradox.You improve in all
requirements that are important to customers, significantly in the priorities
for improvement, and as expected the satisfaction index increases.However when
we look at how the customer rates their overall experience this has not
changed.
So the conundrum is: how can
satisfaction scores go up for a list of factors that customers say are
important to them, but stay the same for an overall satisfaction question?
The first thing to say is
that this is very, very, unusual. If you look at the relationship between
overall satisfaction and Satisfaction Index there is typically a very high
correlation between the two (in the region of .8-.9).
Let's put together a list of
potential explanations, and see which ones look most likely.
The way overall
perceptions are reported
Overall questions are often
reported differently to individual satisfaction scores and the Satisfaction
Index. If this question is reported as a percentage "top box" score
(and/or bottom box) then it will behave differently to an average, making it
more volatile but also less sensitive to some types of change (a top box score
would be blind to the elimination of poor performance, for example). It's
measuring different things.
As an experiment I looked at
the average overall satisfaction score, average Satisfaction Index and % top
box on overall satisfaction by month for one client with a very large set of
tracking data (42 months). The correlations were:
- Average overall satisfaction with average Satisfaction
Index: .86
- Top Box overall satisfaction with average Satisfaction
Index: .07
In other words average
overall satisfaction is very strongly correlated with Satisfaction Index, but %
Top Box is very poorly correlated.
Try looking at the
average overall satisfaction score as well as a top box figure to make sure
you're getting a fully rounded view.
Sampling error
If you're talking about the
change between one survey and another, rather than a consistent trend over
time, the issue may be sampling error. Whenever you conduct a survey there is a
certain amount of sampling error reflecting the fact that you only talk to a
subset of the people whose views you're interested in. This gives every piece
of data a margin of error, which will be relatively larger for a single
question like overall satisfaction than it is for a composite score like the
Satisfaction Index.
Sampling error may be
hiding real gains in overall satisfaction by making the score look higher than
it should in the first survey and lower than it should in the second.The Satisfaction Index is more resistant to sampling
error.
Asymmetric impact
Nigel talks about this quite
a lot in his new book. If improvement has mainly been in areas that are
"satisfaction maintainers" then you wouldn't expect to see much
change in average overall satisfaction, since the shape of the relationship
between a given and overall satisfaction is a bit like this:
What you would expect to see
is a reduction in the number of customers who are very dissatisfied overall, as
the key with givens is to keep performance above a threshold "tipping
point".
So is this the answer?
Perhaps partially, but it's unlikely that all the priorities for improvement
are givens. (It'd be nice to know the impact correlations!)
Improvements to
satisfaction maintainers may not result in big changes in average overall
satisfaction.
The nature of overall
satisfaction
Another possibility is that
customers have noticed improvements in specific areas, but this has not yet had
time to feed through to their overall feelings about the organisation. If so,
we'd expect to see overall satisfaction start to trend up (along with loyalty)
after enough time has elapsed. This could be confirmed with statistical models
given enough data.
A related explanation is
that overall satisfaction is a tricky beast. One of the reasons that the
Satisfaction Index is often preferable to a single overall satisfaction
question is that it is rooted in specific attributes. Overall satisfaction is a
much more nebulous measure, and is bound to incorporate many other influences
such as brand image and reputation.
This helps explain why there
may be a time lag between improvement in individual attributes and changes to
overall satisfaction. It takes much longer for customers to feel
generally warmer about an organisation than it does for them to notice specific
improvements.
Conclusions
So what is the most likely
explanation for Sean's paradox? My guess is that it is probably down to looking
at improvements in average scores against a relatively static % top box on
overall satisfaction.
If I'm wrong, and Sean's
talking about an average overall satisfaction score, then my guess would be a
mixture of some of the other issues I've outlined in this post. With a bit more
digging around in the data we might be able to eliminate some of them and
narrow down the search!