Important methodological implications of using triangulation in complex policy and management

I

Triangulation is the use of multiple methods, databases, theories, disciplines and/or analysts to converge on what to do about the complex issue. The goal is for analysts to increase their confidence–and that of their policy audiences–that no matter what position they take, they are led to the same problem definition, alternative, recommendation, or other desideratum. Familiar examples are the importance in the development literature of women and of the middle classes.

In triangulating, the analyst accommodates unexpected changes in positions later on. If your analysis leads you to the same conclusion regardless of initial positions already highly divergent, then the fact you must adjust that position later on matters less because you have sought to take into account utterly different views from the get-go.

Everyone triangulates, ranging from the everyday cross-checking of sources to more formal use of varied methods, strategies and theories for convergence on a shared point of departure or conclusion. Triangulation is thought to be especially helpful in identifying and compensating for biases and limitations of any single approach. Obtaining a second (and third. . .) opinion or soliciting the input of the range of stakeholders or ensuring you interview key informants with divergent backgrounds are three common examples.

Detecting bias is fundamental, because reducing, or correcting and adjusting for bias is one thing analysts can actually do. To the extent that bias remains an open question for the case at hand, it must not be assumed that increasing one’s confidence automatically or always increases certainty, reduces complexity, and/or gets one closer to the truth of the matter.

II

Now return to our starting point: The approaches in triangulation are chosen because they are, in a formal sense, orthogonal. This has another profound methodological implication: The aim is not to select the “best” from each approach and then combine these elements into a composite that you think better fits or explains the case at hand.

Why? Because the arguments, policies and narratives for complex policy and management already come to us as composites. Current issue understandings have been overwritten, obscured, effaced and reassembled over time by myriad interventions. To my mind, a great virtue of triangulation is to make their “composite/palimpsest” nature clearer from the outset.

To triangulate asks what, if anything, has persisted or survived in the multiple interpretations and reinterpretations that the issue has undergone over time up to the point of analysis. Indeed, failure to triangulate can provide very useful information. When findings do not converge across multiple orthogonal metrics or measures (populations, landscapes, times and scales…), the search by the analysts becomes one of identifying specific, localized or idiographic factors at work. What you are studying may be non-generalizable–that is, it may be a case it its own right–and failing to triangulate is one way to help confirm that.