Recently, I stumbled upon the work of W. Edwards Deming while doing some reading on the applicaton of stastical control to quality improvement. I'm not sure for whom Deming would today be a recognized name, and after reading The New Economics I have a few guesses as to why his reputation may not have persisted for as long after his death as has the reputation of F.W. Taylor, for example.
Deming, unlike Taylor, was not offering easy solutions to his clients, his clients being managers at for-profit companies, teachers and administrators in schools and universities, and politicians or public servants in government -- really anybody who cared to listen. Rather, he was offering a theory about how organizations could improve their overall performance.
The Systems Theory according to Deming
Of special significance to your author is the fact that Deming chose to call his theory "systems theory." Deming defines a "system" as follows:
A system is a network of interdependent components that work together to try to accomplish the aim of the system. A system must have an aim. Without an aim, there is no system. The aim of the system must be clear to everyone in the system. The aim must include plans for the future. The aim is a value judgment. (We are of course talking here about a man-made system.)
Included in this chapter 3 of The New Economics is Figure 6, which Deming calls a "flow diagram" of "Production viewed as a system":
Figure 6 illustrates the interdependence of the components (most economists would call them agents today) within the system. Deming uses the figure to explain how the product is the result not only of how each agent does his or her job, but of how well the agents cooperate to achieve their mutual goal of a happy consumer.
As Deming sees it, "[a] system must be managed. It will not manage itself. Left to themselves in the Western world, components become selfish, competitive, independent profit centers, and thus destroy the system." By contrast, "[t]he secret is cooperation between components toward the aim of the organization. We cannot afford the destructive effect of competition."
More specifically, Deming places the responsibility with management for studying the market, identifying and selecting goals, and clarifying and facilitating the communication of those goals among agents. In practice, this involves listening to agents more than talking, since it is the agents (especially the agents in contact with people outside the firm) that have the freshest information to guide goal development.
Deming suggests that the ultimate goal should be for every stakeholder in the organization -- stockholders, employees, suppliers, customers, community, the environment -- to benefit over the long term. Contrast this with fiduciary duty to maximize profits for shareholders instituted by Dodge v. Ford..
On my view, Deming was prophetic. This book was published in 1993, when the first of two major financial bubbles were just getting started. But now that the global economy has exploded into a chaotic frenzy of new markets and firms, most of which only roughly fit within traditional geographical or jurisdictional boundaries, it is now obvious that there is no institution in the world powerful enough to guarantee to any stakeholder that it will be favored over all others that contribute to an organization. Until a few decades ago, capital was king. No wonder that the owners of capital, often being the scarcest resource available to a firm, got special protection from government. What is the scarcest resource over the very long haul? As Deming could see even in 1993, the answer is human capital -- people power. The systems theory that Deming espoused is about optimizing firms to make the best use of human capital, and it is completely consistent with the systems theory Broken Symmetry seeks to understand in gory detail. Get in the habit of thinking this way, and life will not be the same.
Let's take one example of Deming's application of systems theory to the problem of optimizing firms. Deming attributes this application to Shewhart, who Deming says:
invented a new way to think about uniformity and nonuniformity. He saw two kinds of variation -- variation from common causes and variation from special causes. Common causes of variation produce points on a control chart that over a long period all fall inside the control limits. Common causes of variation stay the same day to day, lot to lot. A special cause of variation is something special, not part of the system of common causes. It is detected as a point that falls outside of control limits.
According to Shewhart, a lack of knowledge about common and special causes of variation leads to two mistakes:
Mistake 1: To react to an outcome as if it came from a special cause when actually it came from a common cause of variation.
Mistake 2: To treat an outcome as if it came from common causes of variation, when actually it came from a special cause.
The "Common Cause of Variation" is a Martingale
At this point, I can explain to my readers why I believe Deming's representation did not last long beyond his death. These statements, devoid of any experience with statistical or physical theory, must seem completely obvious, even trivial. They are not if one can understand and interpret what Shewhart and Deming (both trained as physicists) are talking about here.
What Deming and Shewhart call a "common cause of variation" is what most engineers, scientists, and even economists and other social scientists would recognize as a normal or Gaussian distribution in outcomes. As wikipedia explains:
By the central limit theorem, the sum of a large number of independent random variables is distributed approximately normally. For this reason, the normal distribution is used throughout statistics, natural science, and social science as a simple model for complex phenomena. For example, the observational error in an experiment is usually assumed to follow a normal distribution, and the propagation of uncertainty is computed using this assumption.
By contrast, when Deming and Shewhart talk about "special causes of variation," they're talking about distributions of outcomes with fat tails -- pareto distributions (a/k/a power laws), Levy distributions, and so on. Deming and Shewhart were studying Martingales and non-convergent stochastic dynamics decades before these became popular in academic fields! Even better, they were teaching managers inside large corporations how to recognize non-Markovian dynamics and correct system design without making the problem worse.
An Application to Financial Regulatory Reform
How might this be applied to the financial system? Fat tails developed, which almost destroyed the system. Lots of folks are jumping in now with reform proposals that promise to make the system more efficient, more stable. What would Deming and Shewhart have to say?
Chapter 9 provides some tantalizing clues. Chapter 9 is called "The Funnel," and describes a process whereby marbles are dropped through a funnel (which is wide enough for each marble to have some clearance) onto a table cloth, with the position at which the marbles come to rest being marked. Without doing the experiment yourself, you can imagine that the actual pattern of marks formed after such an experiment will be a cluster of marks on the table under a target under the funnel -- not one spot right on the target. As Deming explains by successively considering various alternatives, most active efforts to reduce the radius of the cluster of marks will not be successful.
- If at each drop, the funnel is moved from its last position to a new position to compensate for the last error (for example, by moving northeast to compensate for a mark southwest of the target), then the results are worse -- the pattern of marks has an even wider radius.
- If at each drop, the funnel is moved from its starting position to a position equal in distance and opposite the direction of the last error, then the results are even worse -- a plot of the radius of marks now shows distinct oscillations.
- If at each drop, the funnel is moved over the mark where the last marble fell, then the marks will merely drift off "to the Milky Way."
What's going on here and how is this relevant to the financial system? Banks are funnels for cash and other assets -- the marbles flowing through our system. The marks on the table are the marks on the books of each bank -- marks of how each asset is valued at a given moment. The various alternative rules for moving the funnel around represent the effects of mark-to-market rules on the financial system -- rules intended to correct for the default gaussian spread of marks!
- When corrections are made to book value in each period to account for newest market prices, volatility in asset value is increased. This is equivalent to moving the filter in a direction equal and opposite to the last mark after each drop.
- Making corrections to book values of cost only makes things worse, increasing volatility in the system even further!
- Marking assets to exactly the last market price (i.e., without taking into account historical value at all) sets the whole system adrift.
How and why was FAS 157, which implemented these rules, ever put into place? The answer is that the accountants who work on these regulations work for the banks and institutions that wanted to mark up their book value during the Great Moderation that preceded the present financial crisis. And they're not entirely to blame because most of these people do not have a systems-wide view of the consequences of these rules. But it should be clear how important they can be.
I hope this example demonstrates the instrumental value of systems theory to policymakers. Until now, law and economics (the economics being mostly neoclassical) was the only quantitative tool in the toolbox. What this example shows is that systems theory can provide insight. As Deming points out, none of the active efforts to correct the error would have been as helpful as simply moving the funnel closer to the table cloth or using a sticky table cloth (by analogy to the financial system, this could mean better matching the frequency of marks to market to the frequency of transactions or increasing the transactions costs relative to the size of the transaction).
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