Insights from across the organisation can help the RM team understand unusual trends and adjust models accordingly, writes Tom Bacon

Take this hypothetical model: Yesterday bookings were up by a whopping 25% versus the forecast! Over the past week, bookings have exceeded forecasts by 8.9%, but over the past two weeks they are flat. The RM forecast algorithm, based on an auto-regressive moving average, adjusts itself by 3.1% in light of the stronger booking activity – moderated by the somewhat inconsistent trend. 

To sum up

Yesterday: Up 25% versus forecast
Past week: Up 8.9% versus forecast
Past two weeks: Flat versus forecast

With the model adjusting by just 3.1%, it obviously considers yesterday’s 25% jump a ‘blip’. Clearly it requires much more sustained strength to adjust the forecast by anywhere near 25%.

But what’s really going on here?

A completely analytical statistical model based on history must have some way to deal with such ‘blips’. It must somehow differentiate between ‘blips’ and true shifts in demand. In practice, a statistically based model must wait until the blips are persistent (no longer ‘blips’) before it completely factors them into its projections.

Be prepared to listen

In this case, rather than rely completely on the algorithm, the revenue management department should solicit input from the rest of the organisation – what’s really going on? 

Of course, these other departments may not have hard quantitative data to explain yesterday. That does not mean, however, that they can’t add value to the revenue management team. 

In fact, ‘stories’ from the rest of the organisation (sales, marketing, schedules) can sometimes help shed light on causation – for both blips and dips – that can help RM analysts adjust the model properly. Rather than rely on the algorithm to tell them if yesterday’s 25% was really a blip, RM can seek stories from the rest of the organisation to give insight into one-time events versus shifts in demand.

Of course, one of the key benefits of an RM system is to combat overreaction to anecdotes. The RM system relies on quantitative, statistically significant evidence before adjusting a demand forecast. However, the best solution often comes from effectively using both a statistical system along with such ‘anecdotes’.

In conversation with…

Let’s talk to each department to learn more about the 25% ‘blip’:

Sales: Sales is positioned to inform RM about events and corporate/group movements. Frequently, the blip is due to a major event. Sales can provide a calendar of such events and can advise RM of large corporate/group movements to aid demand forecasting.

Schedules: In addition to the airline’s own capacity changes, including retimed flights, the schedules’ team monitors the timetables of competitors and can advise RM of important changes.

Marketing: Marketing is a key source of blips. Special promotions – either initiated by them or by competitors – will regularly create blips. Even if marketing isn’t able to say ‘72% of the increase was due to marketing’, they may be able to offer an explanation as to why bookings surged. 

Distribution: Distribution can advise whether a blip is associated with a particular channel. There may be a special promotion (by the airline or by a competitor) focused on a particular channel.

Operations: A blip may occur due to a sudden flight cancellation by a competitor or another service disruption.

Input from the rest of the organisation can help RM determine:

• if a blip is out of normal scope (truly incremental bookings)
• whether the blip is more likely a shift in bookings from future periods
• how long the irregular activity may occur

The revenue management system is a critical tool for airlines to respond to demand changes in an analytical, disciplined way.  However, the system by definition will not respond immediately to abrupt changes in observed demand – it has no way of knowing if the change is fundamental and really warrants such changes. A link between RM and the rest of the organisation, even based on ‘stories’, can help RM respond more quickly to market changes.

Tom Bacon has 25 years experience in the airline industry and is now and independent industry consultant in revenue optimisation. 

Questions?  Contact Tom at tom.bacon@yahoo.com or visit his website http://makeairlineprofitssoar.wordpress.com/

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