How do you make valid strategic decisions given the reality that 1) data are usually of unknown reliability, 2) frequently enfold the biases and/or perspectives of the people who created them.

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How do you make valid strategic decisions given the reality that 1) data are usually of unknown reliability, 2) frequently enfold the biases and/or perspectives of the people who created them.

At least One page. This week’s discussion thread is: How do you make valid strategic decisions given the reality that 1) data are usually of unknown reliability, 2) frequently enfold the biases and/or perspectives of the people who created them 3) most models fail to forecast the future and 4) are not even very good at understanding the present if it reflects any meaningful change from the past? In short, how do you use faulty tools to make good decisions?

For example, in 2016 The Economist’s research study pointed out that the IMF (international Monetary Fund) failed to forecast any – 0% – of the 220 economic downturns that would affect countries between 1999 and 2012. All 4,000 or so forecast models used within the USA failed to foresee the huge 2007 recession, as did almost all mainstream analysts and economists. Most then failed to realize how severe a recession it would be. In the 2016 election cycle political forecasting has almost always been massively off target.

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