In my first article I looked at ‘Bankable Signatures’ and whether they were relevant to the possible measurement of trust. The analysis was triggered by a pending Centre for Innovation Industry Economic Research (CIIER) research project looking at the measurement of trust.
The thinking about bankable signatures led to consideration of the linkages between believability, reputation, recognition, and outcome, and how perceptions of trust are impacted by them.
In my second article, I postulated a ‘barometer’ approach, based upon the presumption that:
As a general rule, if it is difficult to measure something directly, it is often useful to measure the factors which affect what you are trying to measure, and to measure the variations in those factors, in order to extrapolate likely effects on the outcome.
I argued that we know, from experience, that belief in a person or institution creates a propensity for trust in that person or institution, and, conversely, disbelief in a person or institution creates a propensity for lack of trust in a person or institution, and that the effect is that regardless of whether the initial belief is justified or not, the base point of trust is different for everyone.
I then concluded that: The simple barometer measure of trust is therefore the difference between expectation and outcome.
Further thinking, however, must consider that, just as the initial trust is an individual perception, not necessarily a reality, so too, are the expectations and the perceptions of the trust value of any outcomes.
Accordingly, the key measure cannot be a finite value, as each individual finite value is unique.
What we can measure, however, are the change or variation in those perceived values, as they relate to intrinsic or initial trust level, the expectation of a particular outcome, and the perceived reality of that outcome.
The sum, or median, of such variations then provides an indication of growth or diminution in trust levels across a coterie.
For example: Joe has a reasonably high trust in the government. He expects the CovidSafe app to work effectively (small downward variation in trust level). He perceives it to have few problems in practice (no reduction in trust level)
Eve is suspicious of the government. She doesn’t expect the CovidSafe app to work (no change in trust levels). She is agreeably surprised to note significant downloads by others (slight increase in trust).
On the base of this tiny sample, the aggregate change in trust level from initial to expectation is slightly down (healthy scepticism), but the aggregate change in trust levels on perceived outcome is a slight increase in trust (slight optimism).
Thus, regardless of the ‘start-point’ or intrinsic trust level, changes in trust (on any issue or structure where expectation takes place, prior to reality), can be measured and aggregated (for an average trust outcome), or the median calculated, for a ‘most people think’ trust outcome.
Using this approach to a range of different issues, for the same coterie of people, could also allow for weighted and ranking indices to be applied to the issues to establish broader levels of trust.
The end result of such an approach would be the development of what could be called: a Trust Index.
