"Tech Recovery Under Way"
Interesting piece in the San Jose Mercury News, making the case that we've certainly bottomed and the tech recovery is underway. Spending on infotech equipment has been up the last two quarters, and the folks who -- it now turns out correctly -- told us that the recession began last March are telling us that the recovery is really well under way:
The reason so many economists missed the recession, said ECRI director Anirvan Banerji, is that they base their estimates on how the economy behaved in the past. When the economy begins to change, the past does not help predicting what will happen in the future [emphasis mine]. That's why many conventional economic models lead to exaggerated estimates of growth when the slowdown starts. At the same time, it also leads to undue pessimism when the economy begins to improve.
And that's what's happening again. Too many pessimistic forecasts are missing the sustained, although subdued, recovery and are worrying about a ``double-dip'' recession this year.
``We don't see a recession in sight,'' Banerji said.
A more interesting part of this pieec at the end, which talks about the importance of good information gatheirng and analysis in decoding the state of the economy and determining what policy is most appropriate:
She has urged Congress to spend more money on improving the government's gathering of economic statistics. The Federal Reserve would have undoubtedly cut interest rates sooner to stimulate the economy and the federal government might have started spending sooner, if they had more accurate data, she said.
I've been doing reading around the topic of Business Intelligence lately. BI software allows users to relatively easily sort through huge quantities of data to discover trends and patterns. I"'e likened the technology to spreadsheets, characterizing BI as a 'what-if' tool for non-financial data. You can, for example, see trends along a variety of axis -- or dimensions as they are called -- at once. How are these products selling in these locations in these time periods, and how have those sales reacted to price differences? My reading hasn't yet revealed whether or not there is easy technology that allows one to do forecasting based on those numbers -- whether one can run the trends and patterns data pulled from a BI application into a spreadsheet environment to extrapolate and play 'what-if' games with the variables. The point here is that the economy is now so huge, seems to change so quickly, and is so much more measurable than it has ever been before, that our tools for collecting and analyzing that data -- and informing our reactions to it -- have to keep up if we're going to be competitive as a nation. We expect our companies to be competitive globally, and for that they require great information systems. Why doesn't our country have the same tools?
11:40:01 AM 
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