How to assess a wine without even tasting it

BEFORE there was moneyball for baseball, there was moneyball for wine. And yet, unlike in baseball, the use of statistical analyses in the wine industry remains relatively rare. What explains the difference?

In the late 1980s, the Princeton economist Orley Ashenfelter found he could predict the quality of Bordeaux red wine vintages based on characteristics such as the temperature and rainfall during the harvest year. In particular, he was able to explain the price of a bottle of Bordeaux through its age, the average temperature during the growing season between April and September, the rainfall in the previous October through March, and the average temperature in September, when the grapes are usually harvested.

Using just these variables, he was able to account for more than 80% of the price variation for vintages in the 1950s, 1960s and 1970s.

Just as with baseball scouts, this analysis threatened the status and existence of professional wine tasters and evaluators. Not surprisingly, they were offended and harshly critical. Since then, Ashenfelter’s predictions (for example, that the 1989 and 1990 vintages would be exceptionally good) have held up quite well. Furthermore, his analysis was based on simple regressions. More advanced statistical tools are now also being applied, with notable predictive success, to evaluating wine quality.

And yet, unlike with baseball, data analytics remain mostly a sideshow in the wine industry today. If anything, the role of subjective quality ratings has become more, not less, dominant, as a recent Wall Street Journal article highlights. Even relatively unknown raters are cited by wine stores and drive significant changes in sales; a rating of 98 instead of 94 triggers a massive uplift in demand. The bottom line? As long as people are influenced by the quality ratings pronounced by others, as taste-test evidence suggests, the wine industry is likely to remain dominated by connoisseurs rather than computers. | Bloomberg