Greedy algorithms can be arbitrarily bad on large NP-hard problems. But if we're using terms metaphorically, we could also say each greedy company is just a Monte Carlo sample of the whole economy. Some fail or stagnate in local optima; others succeed for longer. But the economy is too complex to expect anyone to ever find a global optimum, so continuous exploration of the landscape is important for overall growth. Thus we can aim for and admire success but should be vigilant against anticompetitive behaviors that stifle the sampling.