Updated: Nov 16, 2021
One of the key components of Bakboka's methodology is to use future-oriented research questions. Here is a list of our top reasons why:
Creating a question whose answer it is worth anticipating fosters good communication between our users and our teams. To generate a good analysis, we need to understand the decision-maker's pain from uncertainty. By analysing a question that is of interest to the decision maker, we share that same doubt. This means that we also share the pain of not knowing. That improves the pertinence of our output.
Creating future-oriented questions forces precision. To anticipate, we need clearly defined parameters. We need to know exactly what we're looking for. It is, for example, impossible to anticipate an 'economic rebound sometime soon'. What is an economy? What is rebound? Does it mean a 5% GDP increase by the end of next quarter according to the IMF, or does it mean something else entirely? If we want to know whether our analysis is correct, 'we were right' or 'we were wrong', then we need to use precise terms and define them.
By looking at the future, you get a chance to test your mental model. Traditional analysis has a tendency to either look at the past or at the present. To do so, analysts create narratives about what they believe best fits the situation, a mental model. This is necessary to be a good analyst, but often there is no way to test whether the narrative was correct. Without concrete metrics to evaluate the analysis, pertinence often becomes a question of how 'sexy' and sophisticated a theory is. Our take is that a good mental model or theory gives you an edge in predicting what is going to happen. If your theory is good, then you should be more often right than wrong about how events unfold.
Anticipation increases the stakes and fosters healthy doubt. If you write about the future and take position on it, then you run the risk of being wrong. Knowing that, you will want to make sure that your arguments are right. This often makes for a more humble analysis, which avoids many cognitive biases. Being measurably right or wrong will also force you to reflect on how you were thinking when you took your position. You can see what you might have overemphasised and what you did not emphasise enough. This feedback loop is invaluable to learn and get better.
Future looking questions force you to focus on what matters. Analysts do not collect or use the same information when they know that the forecast will be proven right or wrong, as when they do no. They hone in on what they believe really matters and has a strong predictive power and filter out unnecessary complexities. This makes for a clearer analysis.
You use the past to analyse, but you need more than that to anticipate. In order to make an analysis, you need a deep understanding of past and present. But for us, this is just the legwork. When you anticipate, you need to know how it fits into future trends and articulate it in a measurable way. This makes us work twice as hard to understand.