For the umpteenth time, I've heard the expression - "It's the new normal". The recent NBC TV comedy series with that title became a fatality of that expression on May 11, 2013 when the series was cancelled (I guess it didn't become a new normal comedy series).
Usually expressed about the stock market or socioeconomic factors, the expression becomes a lazy justification for why a trend has defied some expected (or traditional) long term principle. The expression is also used as a club to hammer the laggards who preach that this change will revert back to the natural norm.
What is normal? Start first with the opposite - not normal, or the unexpected. So it is the frequency of how many times the unexpected occur that determine a "new normality". Here is where the statistician kicks in. When normal is described, I visualize the normal curve - that bell shaped thing we learned about in school.
But remember there are two axes (see April 13, 2013):
A. The vertical y axis - best visualized as the mountain top. Is the curve a steep mountain of a flat rolling hill?
B. The horizontal x axis - the data points of what you are measuring. Has the curve shifted right or left of the expected middle?
Does a perceived change in the curve mean a new curve or that the sample of observations that just happens to be outside the confidence interval (now it's getting very statistically deep)?
Unfortunately, those that opine about "the new normal" are never consulting the statisticians. But then again most statisticians are "A B normal" :)