Living in Connecticut with some big trees in the yard, we stocked up on water, food we could eat without cooking, propane and then slept in the finished basement. We spent the entire time with running water (hot AND cold). We had no flooding, and enjoyed uninterrupted power, cable, phone and internet service. No trees or limbs down, though a small branchlette did tear a window screen on its journey down to earth but left the glass unscratched. That’s the extent of it.
We were fortunate. Also grateful for the funding and diligence of pro-active tree trimming around power lines that has been going on for years in this area.
Because of these facts.
Side note about Montreal. My wife went to Montreal on Friday to bring our daughter home after her summer there. They had planned to make the trip back on Sunday but as that was when Irene scheduled her visit they had to choose whether to come home on Saturday or ride it out up north and come back on Monday. They chose to arrive Saturday before Irene did. The right choice as it turned out; because damage to high rises which had been a concern for NYC never panned out there. But several windows were blown out of a high rise in Montreal – a building my family drove right by on their way home.
The point is that large scale trends can be irrelevant to specifics on the ground without being wrong. If your house did fine in Gloria (a REAL hurricane) but got flooded by Irene (JUST a tropical storm) the fact that, by some numbers, Connecticut did better than predicted doesn’t really matter to you.
That means that national or global economic trends of recessions, tight lending by banks, layoffs etc. may not be applicable to your business. Things may be better for you or worse depending on the specifics of your situation.
For example, most of my current clients are doing better than the national averages in recent months and are having trouble hiring. One whose business as always done better than his local competition is having hard times and seeing his numbers dwindle and is having to cut staff. We’re starting to track different data points to learn the causes of these things and how to exploit them.