Editor | On 03, Nov 2019

Darrell Mann

I worked fifteen years in the aerospace industry at the start of my career. Safety was everything, something that united the whole industry. When planes fall out of the sky it is not good news for anyone. Therefore, the moment an incident occurs, it is investigated rigorously and the findings spread across the industry to ensure that a repeat will never happen. This is the way to build the world’s safest industry.

But then, of course, the innate human desire for ‘more’ sooner or later pushes systems towards dangerous cliff edges. We don’t know the full story of the two Boeing 737 Max accidents, the first, Lion Air flight 610 on 29 October 2018, followed by Ethiopian Airlines flight 302 on 10 March 2019, but we can see that something significant has shifted in the aerospace industry.

The Boeing 737 has a long history. The first 737 entered service in 1968, and, through its many evolutions, is now the biggest selling airliner of all time. The aerospace industry in general, and Boeing in particular have a long and successful track record of evolving their products in order to offer customers better performance, economy and reliability, and so, over the years, there have been several versions of the 737.

In order to ensure safety, the industry takes very complicated systems (‘600,000 components flying in close proximity’) and makes them ‘simple’ for operators by imposing strict constraints on what is and is not allowable for pilots to do. In terms of our Complexity Landscape Model (CLM), for a modern airline, the world looks like this:

One of the early evolutions of the Boeing 737 arrived with the advent of much more fuel efficient high-bypass-ratio turbofan engines. This new generation of engines offered the potential to save a substantial amount of fuel, but at the expense of having a bigger overall size than the pencil-like low-bypass-ratio engines they replaced:

These bigger diameter engines created a complicated problem for the 737 design team: how to fit them in the space under the wing without having to re-design the wing or the undercarriage. The answer, now widely familiar as an illustration of Inventive Principle 4, Asymmetry, was to design the ‘squashed’ engine nacelle. Here’s what the development of that new solution looked like from a Complexity Landscape Model perspective:

…the need for the new, higher diameter, engines created a complicated problem. When the designers successfully solved the contradiction associated with this problem the required made use of complicated design tools and methods. And then, once the problem had been solved and validated through a series of qualification trials, the productionised solution would be effectively no different from the operator perspective.

The latest, Max, evolutions of the 737, in theory at least, created a similar CLM development programme trajectory. Firstly a desire to improve performance triggering a series of complicated engineering challenges.

Yet again, the desire for increased fuel efficiency saw the creation of bigger, heavier engines, and yet again there was a desire to not make big changes to the undercarriage or wing design. This time the solution involved moving the engines forward and upward slightly. Principle 17, if you like. One of the consequences of this move was to alter the balance of the aircraft a little bit. Another complicated problem, but one that the engineers were able to solve using changes to the control software of the aircraft.

So far so good. Simple, resilient, well understood system, has complicated changes imposed on it, which get solved, and validated… and, hey presto, the new aircraft design returns back to ‘simple’ from the operator perspective.

Except. Not quite. This time around the business imperative was much greater than in the past. Airbus were winning lots of orders thanks to their new, fuel efficient A320neo, and Boeing were forced to offer airlines a more competitive 737. Costs are always important, but now they became even more so. One constraint put on the engineers was to ensure the flyability of the Max was as near as possible the same as for the ‘classic’ 737s. This would mean that pilots could be re-trained very easily. Again, complicated problem, but one the engineers seemed to have found a fix for. Another cost constraint then starts to appear: on-time delivery of the new aircraft. As is the way in the airline industry these days, if aircraft are delivered late, airlines benefit from substantial compensation fees.

This time pressure now hits the programme managers. And specifically the cost-schedule-quality iron-triangle. Which two did the Boeing senior managers want? On budget, on time, or to the right quality?

We can’t as yet know for sure how the programme managers and their managers chose to tackle this iron-triangle problem. But what we can say for sure is that the problem is no longer a purely technical one. Crucially, the moment we bring humans – most project managers count as humans, I think – into the equation, a complicated problem has become complex…

The problem context (environment) having transitioned into the Complex domain, now demands a system capable of dealing with that complexity. The fact that two 737 Max aircraft have fallen out of the sky and killed 346 people tells us that the system did not possess the requisite level of capability.

In the same way that it is very possible to push a technical system across a boundary (from Simple-to-Complicated, for example, or Complicated-to-Complex), it is also very possible that the business and social systems surrounding that technical system can also see similar boundaries being crossed. The premise for building the Complexity Landscape Model was to help organisations to know where and when such boundaries do get crossed. And the reason that premise arose in the first place was our observation that almost none of the world’s enterprises or those tasked with leading them had the first clue that such boundaries existed, never mind that they might be being crossed.