  In the name of meritocracy, modern economies devote increasing amounts of
resources to quantifying and ranking the performance of individuals and
organisations. Rankings send out powerful signals, which lead to identify the
actions of top performers as the `best practices' that others should also
adopt. However, several studies have shown that the imitation of best practices
often leads to a drop in performance. So, should those lagging behind in a
ranking imitate top performers or should they instead pursue a strategy of
their own? I tackle this question by numerically simulating a stylised model of
a society whose agents seek to climb a ranking either by imitating the actions
of top performers or by randomly trying out different actions, i.e., via
serendipity. The model gives rise to a rich phenomenology, showing that the
imitation of top performers increases welfare overall, but at the cost of
higher inequality. Indeed, the imitation of top performers turns out to be a
self-defeating strategy that consolidates the early advantage of a few lucky -
and not necessarily talented - winners, leading to a very unequal, homogenised,
and effectively non-meritocratic society. Conversely, serendipity favours
meritocratic outcomes and prevents rankings from freezing.
