Can We Avoid Another Cataclysmic Meltdown Of The Global Financial System?

Chapter 2 The Fall of Business

Chapter 2 explains how financialized thinking came to dominate  the American corporate mind-set and what can happen if it becomes an obsession and financialization as a strategy goes unconstrained.

Faulty Mind-sets: Pleasing Wall Street vs. Pleasing Customers 

A prime example of a company who acquired this mind-set was GM. GM produced cars that had flaws that they were forced to recall, allegedly became they had focused on making money and pleasing financial markets instead of making good cars and pleasing customers. Instead of owning up to bad decisions and taking corrective actions, it seems that GM management tried to avoid added costs  of fixing its problems by remaining silent, or resorting to obfuscation and buck-passing.

This obsession with pleasing Wall Street prevailed at other US automakers as well, especially during the  period from 2001 to 2007 where the US automakers were losing market share and Wall Street demanded that they cut costs, and “make the numbers”, even if it impacted product quality and safety.

Shareholders Value Uber Alles

• • Shareholder Distributions Over Real Business Growth
• • Short-term Profits over Long Term Investment
• • Capital Accumulation over Re-investment and Job Creation
• • Short-term profits before longer term return on investment.

The ascendency of financial thinking had spilled over to other US companies that were under similar pressure to produce better short term profits and to make choices as to what was cheapest, not what was best. In other words, starting in first half of the twentieth century, there has been a gradual shift in corporate America toward balance-sheet-driven management and a mind-set now prevails that puts increased shareholder and distributions of dividends to shareholders,  before achieving real business growth and product and market innovation, capital accumulation before job creation, and short-term profits before longer term return on investment.

Taylorism Over Collaboration and Teamwork

Managers of corporations believed that it is necessary to measure business activity and work being performed, in order to manage profits and achieve their  financialization goals. This mind-set spawned the scientific management movement whereby the rank and file worker was to perform explicit repetitive tasks at a high rate of productivity  on a sustained basis and managers were to define the tasks, provide the thinking for improved execution and oversee their implementation. This approach (a.k.a. Taylorism) has since  discouraged feedback from the workforce and  discouraged collaboration, innovation and teamwork. There are now recent examples of American companies that are organized in ways that encourage collaboration between management and workers and those exposing the extensive use of Taylorism as being proponents of “scientific mis-management movement”.

In Chapter 2, it is also explained that in addition to excess financialization, another contributing factor to the fall of  business was the excess use of financial efficiency theory by corporate America, which had fostered a culture of management by the numbers, leading to lowering corporate productivity. Examples of how this has happened include stories about Robert McNamara and his whiz kids at Ford Motor Company and about how his  systems analysis driven conduct of the Viet Nam war had contributed to its ultimate failed outcome. A conclusion captured in this chapter is that Mc Namara’s “management by the numbers”  had led to major war decisions “that were chosen not because they were the best, but because they were the easiest to calculate.” How sad.

As is pointed out at the end of this chapter, this systems analysis approach to decision-making is often fairly rigid as systems analysis often takes too much time to complete and the questions for which answers are being sought often change before action  can be taken. In other words, this approach has proved efficient in providing answers to known goals, but it is terribly inefficient in figuring out what the goals should be, especially when dealing with problems in which a large number of sticky hard to quantify metrics have to be considered.