Expressing the results of a discovery exercise

A while back I wrote about how to conduct a discovery exercise in an incremental manner. This is where we have some idea of what we want to do but need research or some kind of investigation to validate our ideas.

But recently I was discussing with someone what the outcome of such a discovery exercise might look like. Aside from broad statements and a display of evidence, what might a success measure look like? I said for me, there were two ways to approach this.

One way is to think about the truth of a statement, in which case we’d use confidence as a success metric. Here, we have a claim or hypothesis and some level of confidence in that statement: 50% is total uncertainty, 100% is total certainty of success/truth and 0% is total certainty of failure/falsehood. So we start with a statement and a confidence level which is close to 50%; this shows that we are pretty uncertain about the truth of that statement. After our research, however, this should change; the percentage should move closer to 0% or 100%. This shows that we have much more certainty about the truth (or otherwise) of the original statement.

In practice, of course, we’ll probably start with several statements, and our discovery work will seek to move the needle on many of them.

The other way is to think about potential results of some prospective project, in which case we’d be looking at confidence intervals, and seeking to narrow those. So we might frame our original statement as (for example) “We are 90% confident that we can generate between X any Y annual revenue from a product like this,” where X to Y is a very wide range. The investigation work should seek to narrow that range: “Now we’ve done our work we are 90% confident that we can generate between A and B annual revenue from it.” Here, A to B is a narrower range; our discovery exercise has reduced the uncertainty of what the results might be of our prospective product.

Both ways of representing the outcome of the discovery exercise are estimates, of course, but they are a strong indication of the progress we’ve made, and the greater certainty our work has produced.

Photo by Uniformed Services University