I listened to Bloomberg Radio the other day when Chris Whalen was being interviewed by Tom Keene and Ken Pruit. I was surprised by the level of agreement that I was having ... something that does not happen very often with most of the Bloomberg interviews.
Chris Whalen's webpage http://www.rcwhalen.com/ helped me to understand his conclusions ... and from there to his other writings including for example http://www.rcwhalen.com/pdf/2010-PB-03_Whalen.pdf and the list of various writings http://www.rcwhalen.com/articles.asp.
Chris Whalen seems to know history and the dynamic of what has been going on with the banking and finance institutions in depth over a long time ... but has then correlated the workings of the system with the results of the system in a very meaningful way.
The Whalen conversation was helpful to me to position my own views about what I call the "real economy" relative to his views about banking and finance and economic performance.
As usual, I see the metrics as being a central element in understanding a way forward that will engage all the participants on the global socio-economic playing field and make it possible to achieve meaningful money profits while at the same time building corporate performance that does well using the triple bottom line of people, profit and planet ... and also takes care of the issue of resource allocation to critical assets that are important for our future.
Chris Whalen appreciates the complexities of the instruments that have been created by the banking and finance experts ... including the idea that these instruments rarely have a real value adding dimension and as such the banking sector is more fluff than substance. This latter is my wording ... Chris Whalen is more sophisticated!
In the same week I have been having conversations with people outside the world of New York and banking and finance. While many are unemployed ... in the USA say 20% of the workforce or 15 million people ... there are 80% who are employed and earning. It was pointed out that a huge number of people were not buying because in reality they had most everything they needed ... two parents ... two cars ... two houses ... two children and they really did not "need" much more. Of course this makes GDP look awful, but GDP is a "silly" measure anyway. Is the country better off when people spend even when the spending is beyond their means, done on credit, and for things that people really do not need or want!
Hunting and fishing are pastimes that give many people a lot of pleasure ... they have little product that gets measured, but they produce happiness in all sorts of US communities.
So why is it that bigger is considered better by the stock analysts ... why is more and more the measure of prosperity? And the answer is that there is no good reason. Quality of life is not just about more product ... it is very much about enough and not so much about more. The metrics need to get changed.
One of the elements of the metrics system that should be in play is the "balance sheet" ... and specifically the relationship between what people have and what people owe, or might owe in the future. The balance sheet needs to be used at the individual and family level ... at the community level, the organization level, the government at all levels, and at the national level. Surprisingly the balance sheet is absent from many parts of the society ... and without balance sheet the checks and balances that are so valuable are also missing.
There are people hurting as a result of the economic meltdown of the past few years ... but the statistics suggest one sort of problem when in fact there may be a very different problem. Again this argues for the sort of metrics that serve to identify the problem in a practical and specific way. Good programs are going on in some places but not in every place ... bad things are happening in some places, but not in every place. The metrics have to be specific enough to help get resources allocated to where they are specifically needed ... not merely being some high level statistical model that has zero reliability around cause and effect. In other words we have to work on metrics in order to have metrics mean something!
In analysis of the economy as in many forms of analysis ... good analysis will show that the good is better than one might expect and the bad is a lot worse than one can imagine. They are both realities. The average of the good and the bad is really meaningless.
And applying this to the data flows and to media ... there is some good media ... but "OH MY", there is some bad!