Leaders Discount Theory, Rely on Practice

By Gary Clayton

“In theory there is no difference between theory and practice. In practice there is.”
–Yogi Berra, Major League Baseball Manager

I can’t imagine a clearer statement of what has brought us into this deep recession. We want to believe that the experts are telling us something in which we can trust, yet as leaders, we need to be very cautious. We have recently seen a confluence of expert knowledge failures.

Leaders must be careful in picking which experts to listen to, especially when the experts make claims based on theories. In this last year, we’ve seen many failures result from blindly following the best theories experts could provide. We live in a world of practice, not theory:

• In theory, credit default swaps (CDS) were supposed to act as a form of insurance. Instead, they exacerbated and exposed instabilities in the financial markets when the “insured” called for the CDS buyers to make good on their commitments.
• Mortgage-backed securities were, in theory, supposed to be less risky than holding on to the individual mortgages. Instead, the value of the mortgage-backed securities collapsed as mortgage defaults rapidly increased.

How could the experts who created and marketed these financial instruments been so wrong? In each case, the experts relied on generally accepted theories that matched what they had experienced and had been taught. What could have gone wrong with the theories?

What Yogi Berra learned through practical experience was right – and what we take away from business school is often wrong: a theory is not always reliable. There is a good reason why economics is called the “dismal science”. Its basic tenets, its theories, are prone to failure, even catastrophic failure – and much of our financial industry is built upon these theories. All of us in leadership positions need to understand reality can be radically different than theory – and act accordingly.

No sensible scientist would ever tell you to always trust in a theory. A theory is an analytic structure designed to explain a set of observations. It is not a guarantee that the next observation will fit the theory. A good example (Figure 1) can be seen in mechanics, the physics of energy and forces and their effects on bodies.

Figure 1.  Science requires multiple theories to explain physical mechanics

Figure 1. Science requires multiple theories based on particle mass and speed to explain physical mechanics observations

Scientists use multiple theories to fit all observations

In high school physics, we learned about Sir Isaac Newton and his theory of gravity: F=G x m(1) x m(2) / r-squared. This theory falls within Classical Mechanics and worked great for understanding how everyday objects respond to gravity. It was all that was needed in Sir Isaac’s day.

Yet, astronomers noticed that their observations of planets and stars seemed to be inconsistent with Newton’s law. Albert Einstein realized a new theory of gravity was needed for very large bodies traveling at celestial speeds. This lead to his theory of general relativity and the field of Relativistic Mechanics. Scientists were ecstatic when his theory was consistent with their observations.

Other physicists, working with atomic and sub-atomic particles, found more observations that didn’t fit either theory of Mechanics, thus leading to the development of the theory of Quantum Mechanics. Yet even this theory could not explain observations made when those sub-atomic particles were moving near the speed of light, leading to the development of Quantum Field Theory.

Theories are based on limited observations - at best

Economists, just like physicists, have tried to base their theories on observations. Yet economies are chaotic by nature. They are based upon the interaction of billions of independent people, groups and businesses not just within a single nation, but the entire world. There are far too many factors, too many unknowns involved for any current day theory to be trustworthy.

In performing research, scientists are supposed to document the limitations of their work. To be complete, economic researchers would have to list multiple pages of limitations in publishing their work. Economists can say that their theories fit all observations that have been made in the time since some type of economic records was begun. But they can not reasonably say what will happen next week, next month or next year.

Economics and investment theories are based upon assumptions

Ever heard of the Efficient Market Theory? It assumes that the only source of risk is price volatility. In other words, investors will bid the price of a financial vehicle either up or down by their knowledge of the current and future value of the vehicle. Unfortunately, as we have seen with stocks like Enron, the real value may be radically different than what the market knows. And what about people who invested through Bernie Maddoff? Where did their $50 billion go? Could it be that extreme price volatility can be produced by other risks including fraud and incompetence?

Some economic theories are just plain wrong

What happened to the value of hedge funds? How could some of them suddenly go broke, losing everything for their investors? Didn’t they use the Nobel Prize-winning Modern Portfolio Theory (MPT) to manage their investments? Could it be that MPT has as many holes as Swiss cheese?

Unfortunately, MPT believes in efficient markets. But that’s not the only problem. What about MPT’s reliance on the Gaussian distribution or bell curve? Read what Wikipedia has to say about Gaussian distributions[2]:

For theoretical reasons (such as the central limit theorem), any variable that is the sum of a large number of independent factors is likely to be normally distributed. For this reason, the normal distribution is used throughout statistics, natural science, and social science[1] as a simple model for complex phenomena.

Likely to be normally distributed? Simple model for complex phenomena? What if the function is not normally distributed? And what if there are some complex phenomena whose effects are different than what is imagined in the theory? How great a risk will you be taking?

Think about Yogi Berra’s view on practice. It doesn’t matter what theory says. What is important is what you can achieve – or experience - in the real world.

In 1934, a pair of scientists reportedly proved that bees can’t fly because their wings were too short. But the bees don’t know that, they just follow Yogi’s edict: it’s practice that matters.

Don’t let theory suck you in to bad decisions or limit your horizons. Don’t let experts snow you with theories. Your followers depend on you to get it right.


  1. Modern Physics Fields. Retrieved May 21 at
  2. Normal Distributions. Retrieved May 21 at

Gary Clayton is a leadership coach who works with leaders and those who wish to become leaders in business and life. He has encountered the limitations of scores of theories in the fields of organization development, business administration and engineering.

Share and Enjoy:
  • LinkedIn
  • Google Bookmarks
  • Digg
  • TwitThis
  • Facebook
  • StumbleUpon
  • YahooMyWeb
  • Yahoo! Buzz
Categories : Science