Could Big Data solve Qantas’ Problems?

By Clive Gold, CTO Marketing, EMC Australia and New Zealand

A thought struck me on the weekend… could mining all the data Qantas has access to, change their business model to drive profitability and keep the unions happy at the same time? Then I started to ponder about the aspects of their, (any), business that could be improved by ‘Big Data’, and thought about example of how to improve some of the fundamental issues that drive cost, service, etc.

A major cost of any airline is obviously the fuel they burn, and I would imagine that a major dent is made into a flight’s profitability every time they have in-flight delays circle around, or sit on the tarmac chewing through the avgas. As a large consumer of air-services this aggravates me when I arrive at an airport to find that a flight has been delayed… and it appears the airline knew about this for some time! Recently I found FlightCaster, (here), who uses a variety of data sources to more accurately predict if a flight is going to leave on schedule. Most
systems just report on past history, whereas they look at weather, sports activities, current network incidents, etc..  It seems to me like more accurate  information about departure and arrival times is a win win, better customer service and lower costs.

Let’s continue talking about customer service; I have to be one of any airlines best customers, almost totally self-sufficient. I am happy not to interact with any of their staff; I value being able to select my seat, use tripit and flighttrack (here) to keep up to date, and appreciate being able to check in while waiting in the security line or running towards the gate! I rarely consume their food or entertainment and I’m even built to fit their seats, (short legs).  All I want it fast and efficient!  Yet even on their top level of frequent flyer I have no personalised experience whatsoever. For example, every time I book a flight, I then log on to their site to select my seat! They know who I am, they should be able to detect this pattern, (I fly about a sector a week), yet I still have to click, click, click, click.. to get to ‘select my seat’.

Now if we put our minds to working out other areas where an airline could transform their operations by leveraging ‘Big Data’ it starts to become quite fun. Maybe a flight of fantasy, (pun intended.. dad joke), but imaging if an airline could decide which plane to send where in real-time? At any point in time a major airline has a number of planes at a particular airport, if they could maximise the load at that point in time and cut overall excess capacity, it drives profitability. If they tracked people’s food preferences they could cater more precisely resulting in less waste and more satisfied customers. (Pun again).

Just think about these things in your context for a while. You soon discover that every organisation has an ‘interaction’ or a ‘process’ can be improved by being able to analyse the available data at that time!!

To me that is what Big Data is about!

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One response to “Could Big Data solve Qantas’ Problems?

  1. Clive, I too have often thought about similar ‘inefficiencies’ or ‘hidden opportunities’ in all sorts of businesses and business models. As a data center infrastructure services provider though the challenges generally lie out the remit of what our clients ask us to help them with…however with the advent of ‘Big Data’ (what ever that really means) tools and the compute and storage capabilities (from EMC and other partners of ours) to quickly ‘ETL’ (probably better described in this instance as ‘ETLA’ the ‘A’ meaning ‘analyse’) all sorts of data I think we may have to shift our approach to customers.

    With regards the airline sector I think the issues are going to be surrounding how to blend the strategic value of ‘Big Data’ analytics/intelligence with the tactical demands of a just-in-time industry. Some of those ideas (particularly) the tracking of individual food/beverage consumption, provide both cost-control and service augmentation (read ‘cross sell’) opportunities. However the path to being able to do such things requires investment and effort. If ‘just-in-time’ service/logistic operations issues can be addressed/mitigated tactically in the short term with the same technologies or systems, then I reckon companies will consider their implementation. I guess that means ‘real-time’ intelligence as well as ‘mining’ the troves of historical data.

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