The Myth of Japan's Collapse


As anyone who has picked up a non-fiction book in the past five years knows, we have entered the “You May Be Surprised to Learn...” era.

Data analytic breakthroughs as well as fresh thinking in the realms of behavioral economics, neuroeconomics and other so-called decision-making sciences have taught us, for example, that most drug dealers make less than minimum wage, bonuses are relatively weak incentives and man is definitely not a purely rational economic actor. On Sunday, I also learned how Japan's economic failure may be a myth.

The article interests me from a risk management standpoint. (I'm not alone in my interest: David Wagner, director of crisis communications for Connecticut-based consulting firm Country Risk Solutions, also weighs on the article here from the perspective of a long-time U.S. expat living in Japan.)

While risk managers may glean some deeper lessons from Japan's own risk-taking challenges, the myth-busting component of the article may prove more instructive. The article's author, Eamonn Fingleton, picks apart the notion that Japan has suffered two lost decades since its stock market crashed in 1990. Those who promulgated – or, like myself, accepted – this notion committed at least three errors, according to Fingleton:

1. We measure the wrong things (e.g., overall gross domestic product (GDP) growth vs. GDP adjusted to a per-capita basis);

2. Our measurements are incomplete (e.g., basing our conclusion pretty much solely on overall GDP while neglecting other measures such as life expectancy, exchange rate and account surplus); and

3. We don't question long-standing narratives (e.g., ask 10 people about Japan's economic performance since 1990 and most, if not all of them, will say it was poor).

So, what might risk managers be surprised to learn about their own capabilities, initiatives and companies? Quite a lot, I would hazard to guess, if you are not continually assessing whether your organization is measuring the right indicators; measuring a sufficient number of indicators; falling victim to the sway of long-standing assumptions and narratives.

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