'…in our march to simplify reality with useful models…we confuse the models with reality. For many people, the model creates its own reality. It is as if the spreadsheet comes to life. We forget that reality is a lot messier.'
A good reminder from Shane Parrish about the limitations of models and how easy it is to forget that whilst models are useful ways of representing contexts and environments they are ultimately abstractions and so we over-simplify the real world at our peril.
There's a nice example he gives of how retail executive Ron Johnson, who had led Apple stores to become the most productive retail spaces in the world on a per-square-foot basis, failed utterly when he tried to do the same for the struggling J.C Penney. Flush with his Apple success Johnson was hired in 2011 by financial world bigwigs to turn the dowdy department store around. Taking his best ideas from what he did at Apple (notably consistent pricing with no discounting, immaculate displays, flashy products) he tried to apply them to J.C. Penney stores and create mini malls-within-malls. Shareholders loved the ideas and flashy pitches, boosting the stock price from from $26 in summer 2011 to $42 in early 2012.
But when it was implemented the transformation failed almost immediately. Customers were confused about what J.C. Penney was, they rebelled against the lack of discounting and the trendy new products, the pricing no longer matched the brand positioning in the market. The business had spent billions of dollars revamping stores but by 2013 the share price was in single digits and Johnson was sacked.
Johnson was a skilled and experienced retail professional but, as Shane says, the mistake was in using the wrong map to navigate the difficult terrain. Apple's positioning, context, history, customer base was completely different to that of J.C Penney and the shift was just too much. The territory was wholly different, so the map needed to be different too.
It's easy and quite natural, I think, for people who have shown success in one scenario to try and replicate that success in new scenarios using models and strategies that have worked in the past. As Shane says, we don't truly understand a map or a model unless we respect its limitations:
'The theory isn’t what it describes, it’s simply a way we choose to interpret a certain set of information. Maps can also be wrong, but even if they are essentially correct, they are an abstraction, and abstraction means that information is lost to save space.'
Once again, adaptability is key.
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