At Socratus, we like to say things like ‘data is an honest broker of complexity,’ i.e., that even people who have conflicting interests or strong disagreements can still agree on the data that forms the basis for their assessments.
For example, a fossil fuel company and a climate activist might be able to agree on the extent of current oil reserves in a particular region even if they have diametrically opposite positions on what to do with oil. The US and the Soviet Union could agree on how many nuclear weapons they could each have.
In a rational model of conflict, we agree on the facts of the conflict and then bargain over our respective positions. But the real world of data is far more complicated.
To start with, we might agree on the truthfulness of a data set but disagree on whether it’s the right data set to mediate our disagreement. The climate activist might say that measuring oil fields is not in their interests at all - measure the carbon in the atmosphere instead.
It might also be in my interest to hide or fudge data relevant to our dispute - I may not want to tell you how many nuclear weapons I have or whether I have the capacity to make one.
Finally, it might be in my interest to deny data and facts altogether, i.e., not just dispute whether this data set or that data set is correct, but that no data is relevant and we will make up whatever facts that suit our case.
Therefore, if we really want to broker a wicked problem using data, we should have a trustworthy and honest process that
- Secures commitment and fidelity to data
- Produces the right data set and
- Mediates disagreement based on the data produced in step 2
- Obtains alignment based on commitment in step 1 and mediation in step 3
Even this is too ‘logical’ a process but at least it’s a little wickeder than the simple model where everyone falls in line once data is shown. Moral of the story: the hard facts captured in ‘data’ are deeply intertwined with soft assessments of trust.