Analytics data revenue

Tom Bacon finds inspiration in a blog by Levi Brooks and applies this to the field of airline revenue management

Certain business problems are recurrent – and we are geared up to analyse the data in the usual ways time after time. We are ready to ‘do it again’, likely justifying our current procedures or, potentially, recommending a small tweak in our modeling. Since we are ready to respond and can therefore provide a quick answer, our organisation loves it!  Boy, aren’t we smart! Sometimes, however, we are much too quick to jump to our normal conclusion. In fact, sometimes we need to be working harder on ‘The Question’ – is there another way to formulate it so that we learn something new this time?

In his blog in 99u, Levi Brooks the co-founder and creative director of Use All Five, an LA-based digital design, development and strategy agency suggests that brainstorming the question can add new value.

Let’s apply this thinking to airline revenue management where a frequent question is this: Why did we miss the forecast?

So, most of the time, we are ready for this, ready to analyse the unusual blip in actuals that the forecast missed. Let’s see what happens, however, if we reformulate the question. Here are some examples:

Question the definition

Where did we get ‘the forecast’? Where did we get the ‘actual’? Are both unambiguous? Are both sources reliable? Has the definition of ‘actual’ changed over time, incorporating new phenomenon or behaviours? Should ‘actual’ be disaggregated, with multiple models capturing multiple underlying trends?

Question the impact

Does the ‘forecast’ actually matter in the pricing or inventory algorithm? Ideally, our models are robust and don’t rely so heavily on perfect forecast accuracy. It’s possible that the forecast variance didn’t change the actual price or inventory allocation much. This is, of course, an underlying goal of a useful model – ensuring the recommendation isn’t so sensitive to imperfect forecasts that it loses its value; we need highly robust solutions that acknowledge we’re going to have some forecast error.

Read rest of the article at: Eye for Travel