6.4. Strategy and Simulation of Growth Scenarios
The main purpose of the model is to investigate easyJet's $500 million gamble to purchase 12 brand new Boeing 737s. Will it be possible to fill them? A rough calculation suggests the airline needs 1 million fliers if it is to operate 12 fully loaded aircraft – which is a lot of people.[] What combination of word-of-mouth and marketing will attract this number of potential passengers? How long will it take? What are the risks of price retaliation by rivals? These are good questions to explore using the what-if capability of simulation.
[] Let's assume each aircraft carries 150 passengers and makes three round-trip flights a day. A fully loaded plane needs 900 passengers each day (150*3*2). A fully loaded fleet of 12 planes needs 10 800 passengers a day, or 3 888 000 passengers each year, which is very nearly 4 million. If we make the further assumption that each potential passenger is likely to fly the available routes twice a year on round-trip flights, then the start-up airline needs to attract a pool of almost 1 million fliers to ensure commercially viable load factors. This rough calculation is typical of the sort of judgemental numerical data required to populate an algebraic model. Perfect accuracy is not essential and often not possible. The best estimates of informed people, specified to order-of-magnitude accuracy (or better), are adequate, drawing on the informal but powerful knowledge base derived from experience.
Figure 6.14 shows simulations of the growth of potential passengers over the period 1996–2000 under two different approaches to marketing spend (bold and cautious) and under the assumption of slow retaliation by rivals. Bold marketing spend is assumed to be five times greater than cautious spend (at £2.5 million per year versus £0.5 million per year). In both cases, the horizontal straight line shows the 'required' number of passengers to fill 12 planes. This line is a useful reference against which to compare the number of potential passengers. If and when potential passengers exceed required passengers, the strategy is deemed feasible.
Consider first the timeline for bold marketing in the top half of the figure. The simulation begins in 1996 with a very small number of potential passengers, just 5 000. The fledgling airline is virtually unknown to the flying public, despite its ambitions. In the first year of operation, bold marketing brings the airline to the attention of a growing number of fliers. By the end of 1996 there is a band of several hundred thousand enthusiastic supporters. Moreover, this band of supporters is beginning to recruit more followers through positive word-of-mouth. In the interval 1997–1998, the number of potential passengers rises sharply as word-of-mouth continues to stoke exponential growth. By mid-1997, the number of potential passengers has reached the target of one million required to fill the fleet. In the remainder of the year, reinforcing growth continues. There is a huge leap of more than one million potential passengers in the last six months of 1997 as the powerful engine of growth continues to gather momentum. Then, in the second quarter of 1998, growth ceases abruptly as the airline's message reaches all 3.5 million fliers in the imagined catchment region it serves.
Figure 6.14. Simulations comparing bold marketing (top chart) with cautious marketing (bottom chart) assuming slow retaliation
Source: From Supporting Strategy: Frameworks, Methods and Models, Edited by Frances O'Brien and Robert Dyson, 2007 © John Wiley & Sons Limited. Reproduced with permission.
The strategically important part of the timeline is the growth phase between the start of 1996 and early 1998. Bold marketing coupled with strong word-of-mouth unleashes a powerful engine of growth, which, in classic exponential fashion, begins small (and therefore invisible) and snowballs rapidly after 18 months.
Now consider the timeline in the bottom half of Figure 6.14, which traces the build-up of potential passengers from cautious marketing. Spend is cut by four-fifths from £2.5 million a year to only £0.5 million a year. As before, the simulation starts in 1996 with only 5 000 potential passengers. In the first year, the airline wins few passengers – not surprising because marketing spend is much reduced. In the second year, there is healthy growth in passengers, despite the low marketing spend. Word-of-mouth is now beginning to draw in lots of new passengers. Once the growth engine is primed it gets rolling and in the second quarter of 1998 carries the airline's passenger base beyond the target required to fill the fleet. Growth continues into 1999 until nearly all 3.5 million fliers are aware of the new low-cost service. Cautious marketing simply defers growth (by comparison with bold marketing), but doesn't seem to radically alter the ultimate size of the passenger base. One can begin to appreciate a persuasive rationale for caution. By the year 2000, the simulated airline has saved £8 million in marketing spend (four years at an annual saving of £2 million), yet has still got its message out to 3.5 million fliers!
Figure 6.15 shows the same two marketing approaches (bold and cautious) under the assumption that rivals retaliate quickly. Price equalisation happens in half the time previously assumed and as a result both timelines are noticeably changed by comparison with the base case. From the viewpoint of strategic feasibility, however, the bold marketing timeline tells much the same story as before. At the start of 1996, the airline is almost unknown among the flying public, and by the third-quarter of 1997 it has attracted enough potential passengers to fill 12 planes. Fast-acting rivals seem unable to prevent this rise of a new entrant from obscurity to commercial viability, though price equalisation measures do curtail the ultimate dissemination of the start-up airline's low-price message.
A strategically significant change is observable in the timeline for cautious marketing. The start-up airline is no longer able to fill its planes because it is unable to attract passengers. The rise from obscurity to prominence never happens. Cautious marketing attracts few converts and fails to ignite word-of-mouth. By the time the low-price message has reached a few hundred thousand fliers (at the end of 1997) it is no longer distinctive. Rivals are low price too. If this future were easyJet's, its planes would be flying half-empty and it would be losing money. Fast retaliation can prove fatal in a word-of-mouth market.
Figure 6.15. Simulations comparing bold marketing (top chart) with cautious marketing (bottom chart) assuming fast retaliation
Source: From Supporting Strategy: Frameworks, Methods and Models, Edited by Frances O'Brien and Robert Dyson, 2007 © John Wiley & Sons Limited. Reproduced with permission.
6.4.1. Using the Fliers Simulator to Create Your Own Scenarios
The Fliers simulator enables you to explore a variety of scenarios for a start-up low-cost airline. You can replay the simulations shown above, create new scenarios, and investigate the behaviour of many more variables. Open the model called 'Fliers Mini-Sim' in the CD folder for Chapter 6 to see the opening screen as shown in Figure 6.16. There is a time chart for potential passengers and required passengers, numeric displays for potential passengers and relative fare, and slide bars for marketing spend and time to change costs. Marketing spend is 2500 (in £ thousands per year) and the time to change costs is four years. These are the conditions for the base case scenario of bold marketing and slow retaliation already seen in Figure 6.14.
Figure 6.16. The opening screen of the fliers simulator
To get started, press the 'Run' button without altering either of the slide bars. The first year of the simulation plays out. Scroll through the time charts to view the behaviour of the conversion ratio, the effect of route saturation, churn and the increase/loss of potential passengers. Press the 'Run' button again to see the next simulated year and so on to the end of the simulation in the year 2000. For a guided tour of the simulation, press the scenarios button on the left. A new screen appears containing a menu of pre-prepared scenarios. Press the large green button for a year-by-year analysis of the base case. At the end of the analysis, press 'scenario explorer' to return to the opening screen. Then conduct your own experiments with other combinations of marketing spend and time to change costs. At any time you can learn more about the simulator by pressing the navigation buttons on the left of the screen. The introduction is a review of the easyJet case and the feedback structure of the model. The scenarios button offers a guided tour of the four pre-prepared scenarios already covered in Figures 6.14 and 6.15. 'Browse model' allows you to see the detailed model structure and documented equation formulations.
6.4.2. Simulation, Predictions and Scenarios
It is important to remember that simulations are not predictions or forecasts of an inevitable future. Rather they are scenarios – alternative futures that may unfold if the assumptions behind the scenarios turn out to be true. In this case, the assumptions include: (1) all the structural relationships shown in the map; (2) all the numerical values and algebraic formulations in the simulator; and (3) the specific parameter changes that differentiate the scenarios (such as a five-fold increase in marketing spend going from cautious to bold). Simulations are a way of rehearsing the implications of our assumptions about strategy in order to reveal surprises and hidden pitfalls.