Obliquity

Economist John Kay tells the story of arriving at Paddington train station, London to visit friends whose nearest underground (subway) station was Lancaster Gate.  Kay followed the standard London Underground map, taking two stops on the Circle line, changing lines at Notting Hill Gate, and two further stops on the Central Line, as you can see here. 

His friends found this hilarious; knowing the area well, they had the following map, which shows that in reality, the walk from Paddington to Lancaster Gate would only have taken a couple of minutes.

Kay's point is an obvious one - that all maps are better for specific purposes than others (a geographically accurate map of the London Underground is possible, but less useful, generally).    In his rather brilliant Obliquity - which is in praise of seeking things indirectly - he uses this and many other examples to argue that we often get attached to mental maps, or models, and use them to guide our actions when we would be better of without them.  He is particularly scathing on the way we take a high level objective (get to friends' house) and then break it down into plausible-sounding but misguided plans (use the underground) and metrics based on these bad models.  

Now in this case, there's a pretty good argument that if he simply had the right map, he'd have been fine - because in this case there is a 'correct' map to be found.  Alas most of the time our maps and models are mental constructions, not representation of the real world; in these cases there simply is no 'true' map.  The trick in these cases is to use our maps, but remain aware that they are maps, and be open to adjusting them.  

Some time ago, some friends of mine were seeking their dream home (high level objective).  They started off by listing the non-negotiables - size, number of bedrooms, districts, etc.  The list had some functional requirements (eg size of garden) as well as stylistic ones (eg no leaded windows), and they used this list (map of requirements) to check that they only viewed suitable properties.   This was an eminently sensible approach; how else to narrow down the thousands of options?

After seeing many houses that met all the criteria, but were somehow not quite right, they found one that they thought was perfect; as soon as they entered, they could feel that it was what they wanted.  They went ahead with a purchase, and have been living very happily there for some 14 years.  

What's most interesting is that their estate agent had, either by accident or design, shown them a house which did not meet their criteria (it actually had the wrong type of garden and leaded windows).  But it was the right house anyway.  By sticking to their carefully formulated strategy, with the specific objectives, my friends would have missed their dream home.

This rather mundane story shows an important truth - that most difficult and/or important situations do not have a clear description; that while we can try to force them into a rational decision-making framework, - things are in fact more complex than we can generally capture.  The map is not the territory, as the saying goes, and in the process of solving problems we learn not just about how to meet our high-level objectives but about the limitations of the objectives themselves.  

Kay's most compelling point concerns the way we constrain our thinking by looking to rigidly measure our progress.  He argues that once you attach a metric to an objective, hundreds of once-possible imaginative solutions to your problem become invisible.  In our results-driven climate, this is a profoundly challenging point, and I've been thinking about this in relation to all the conversations I am having with our senior students about their plans for applying to Universities in countries all across the world.  One rather brilliant British student was not excited by the obvious top choices anywhere she had looked.  Her initial mental model been the usual English-speaking countries, or the even narrower common-but-misguided Oxbridge, Ivy League or bust - but these were not exciting or energising for her.   Through some excellent advice, and lucky discussions she's found a fabulous place in France - and she'll learn French to go there, despite this never ever being on her initial personal map for the next few years.  In this case, her high level objective get a great College education was for a time hi-jacked by the narrow metric of this place, this place or that place.  I am delighted that she threw away these poor metrics and found a better way to meet her objective.

This point is also important as we head into recruitment season for new teachers.  We look at what we know makes a great teacher, what our departments need, and what specific skills are required.  We form a map of what's needed, and by and large we follow it.  Of course we need a good sense of what we're looking for so we can advertise and interview and appoint - but I'm wondering if we should hold this lightly, remain open to change, be more open to diverse candidates  and certainly avoid reductive ticklists.  

Kay's overall point reflects two versions of rationality.  Are good decisions at work, at home, in life,  for us and for our families, always a product of a carefully structured process?   Or can carefully structured processes sometimes crowd out the room for luck, chance, and an oblique approach?

References

Kay, J (2012) Obliquity: Why our Goals are best achieved Indirectly. Profile Books.