When the British Airways planning department needed a major fleet replacement, a model developed by OR cut through hugely complex data to give an informed decision.
One of the biggest and most complex decisions any airline faces is replacing parts of the fleet. The driver for the latest decision was the need to replace the 747 fleet which is advancing in years.
Choosing a replacement may seem a simple cost/benefit analysis, but according to Neil Cottrell, Head of BA’s planning department, the factors involved are messy, multi-dimensional and difficult to pull together, requiring a more sophisticated method.
As well as the straightforward costs and potential for revenue from varying seat configurations, the planners had to factor in the impact on infrastructure – would the new planes even fit with existing airport stands and maintenance bays? – the time and effort required in familiarisation, the aircraft’s performance and range, flexibility, environmental impact and more. Needless to say, getting the decision right was essential.
These aircraft are expected to fly for the next 20 years, so BA can’t be accurate to the ‘nth’ degree. Looking at a number of different scenarios by varying several factors gives the best results. They use what is essentially a ‘heat map’ of results: bright red aircraft X is better by a long way, bright green aircraft Y is better by a long way, and then interim shades depending on how close the competition is. This approach allows planners to take into consideration uncontrollable variables, but that could have significant impact on the profitability of the airline and the best choice of airline for the fleet.
In order to model and predict this complex future, BA’s analysis starts with the most likely scenario and then includes a sensitivity analysis. In this way, they use the model to measure relative differences between scenarios, not absolute figures. This can be described as showing less concern that Scenario A will be showing a contribution of £Xbn a year and Scenario B £Ybn a year, but instead more interested in the fact that there is a £(X-Y)bn difference.
There is always a difficulty when using a complex, opaque model with so many variables of being certain that the outcome is correct. BA overcomes this with rigorous error checking, especially when something is changed. Each stage is ‘sense-checked’ against business understanding and historic data, and every time there is a major update to the base data, the results of the model for that year are checked against ‘actuals’. Any discrepancies are investigated and only once confident do BA move forward and use it to run scenarios to help make decisions.
The model gave the team the confidence to recommend to the board a mix of 18 additional Boeing 787s and 18 of the competing but larger Airbus A350-1000s.
The model is continually being improved by providing it with better and more comprehensive data, which will hopefully help with the next fleet order. There have already been opportunities spotted to make use of the model in different ways; studying the impact of changing configurations, where the number of seats in economy, business and first class are varied to see what impact this would have on route profitability.
But outside of this one decision, OR is extremely valuable to BA, who have the luxury of running an OR group independently, and have on tap a group of highly intelligent analysts who are very quick to provide understanding, insight and solutions to their problems.