Jack Welch, Chairman and CEO of the US giant General Electric or GE from 1981 to 2001, has offered his experiences as a fool-proof survival kit which anyone – people, companies or nations – could use if they wish to be winners in a hostile competitive world.
Jack Welch: Produce what others cannot copy
In his autobiography ‘Straight from the Gut,’ which he published immediately after he left GE in 2001, he has narrated the strategy he adopted to make a turnaround in GE which was heading for bankruptcy at the time he assumed its captaincy.
GE, a reputed brand name for household electric appliances for many decades, had faced the inevitable problem of losing its well protected markets to cheap imports from Japan that had flooded the US and other consumer markets in 1960s and 1970s.
When GE could not survive the Japanese onslaught and was forced to close its doors, the reaction of any other person would have been to protest to the US Government and seek banning of Japanese imports, explains Jack Welch. But he and his team had burned the midnight oils for many days and finally zeroed on the cause of the GE’s plight.
That cause was simply that GE had been producing electric appliances like irons, refrigerators, ovens and deep freezers which involved low technology and therefore could be copied by anyone with ease. If they will go into high tech products which could not be copied by others easily, they would enjoy a protected market for some time, he and others at GE had reasoned.
So, Jack Welch had decided to close all the factories that had been manufacturing these low tech products and used the savings for doing research on three main products which involved high technology and, therefore, could not be easily copied by competitors.
These three products were electric power generating turbines, jet engines and sophisticated medical equipment like magnetic resonance imaging or MRI machines and equipment to undertake non-invasive surgeries, a novelty getting fast popularity at that time.
Having concentrated on these three high tech products, GE was able to eliminate the competitors effectively and managed to make a quick turnaround in its business within a few years.
What does this lesson teach the rest of the world? That is, the competition out there is fierce, cannot be avoided and should be faced with a matching strategy. That matching strategy, based on a world view that things around us are not soothing or comfortable at all times, makes it necessary for us to change from a simple production process to a complex production process. Why a complex production process? Because that is the way to keep our competitors at a safe distance from us so that they cannot grab a big chunk of our markets.
Today, a new branch of economics calling itself ‘complexity economics’ has offered the same advice to nations intending to create prosperity on a sustainable basis.
The world is not moving along a straight path
The world view that things can suddenly change due to events that are taking place outside our perimeter of action or even due to the way we make our living is known as non-linearity that gives rise to non-linear thinking. Non-linearity can best be understood by looking at its opposite, linearity. According to linearity which has given rise to linear thinking, Nature moves along a fixed straight line and one can safely predict where one would be after some years if one knows the direction and the rate of moving toward that direction.
For instance, if one joins as a junior executive of a company today, linear thinking makes him predict that after some time years, he would be the Managing Director of that company. This is because he moves up in the hierarchy of that company in a linear fashion.
Another example for linear thinking is that if a country has got eight per cent growth in the last few years, making predictions that it will continue to grow at this eight per cent in the future as well. Using this linear thinking, many analysts have predicted that China will take over USA by 2025 because it has recorded super high economic growth rates in the past ten years or so.
Laws of Nature that govern movement of natural phenomena
But, natural phenomena are not subject to a linear growth because they follow Laws of Nature, and not laws of men. There are four such Laws of Nature. The first is the Law of Impermanence meaning that every natural phenomenon passes through three stages, a birth, an existence and finally a death. The second is the Law of Cause and Effect – that every natural phenomenon is the result of something that happened earlier and what one has today will in turn be the cause of some other result tomorrow.
The third is the Law of Evolution or that every natural phenomenon is in a constant state of evolving meaning that it is changing into a new form characterised by two features. The first feature is that it is not entirely a new form that one would have and the second is that it is not entirely different from its previous form. So, the Law of Evolution ensures that it is neither new nor different.
The fourth law is the Law of Unity which is a little difficult to understand. The best example for this law is the human gene. Scientists have discovered that humans share a common gene with all other species connecting all of them together or, in other words, demonstrating unity among all species. Thus, all discriminations and differentiations that we make are all arbitrary, illogical and unsupported by evidence.
Mainstream economics: Assume a simplified world
The mainstream economists have used linear thinking to present their theories because that is the easiest way to approximate the natural world. Though nature is multi-dimensional, that is, it is being influenced and shaped continuously by factors that arise in all fronts, human brain has the limitation of being unable to capture more than one thing at a time. Hence, linear thinking is the best way to develop theories concerning the natural world.
This approach is not typical to economics but to all scientific disciplines. If one has to describe the natural world, he has to allow only one thing to change at a time and assume that all other things remain fixed. This approach is good enough for making predictions in the very short run.
For example, by looking at the sky, we can safely predict whether or not it will rain in an hour’s time or even in two hours’ time. But, that observation will not help us to make accurate predictions about having rains in one week’s time. This is because between now and in a week’s time, many things can happen that will change the formation of clouds in the sky. So, it becomes less and less accurate when one makes predictions by resorting to linear thinking when the time span involved gets longer and longer.
Complexity economics assumes a non-linear world
A group of economists have sought to resolve this problem by resorting to a methodology in science known as ‘complexity science’ that accommodates non-linearity. The new branch of economics that has arisen from this exercise is known as ‘complexity economics’.
The three main proponents of complexity economics, among many others, are Ricardo Hausmann of Harvard University, Cesar Hidalgo of the Massachusetts Institute of Technology and Eric Beinhocker of Oxford University’s Institute for New Economic Thinking. While complexity economics is simply an evolution from the previous branching of economics such as behavioural economics, Marxian economics etc, it draws principally from the development of the discipline called ‘complexity science’ relating to natural sciences. This is not unexpected because Hausmann’s first degree was in applied physics, while Hidalgo is a physicist by profession.
A complex system, as against a simple system, is composed of a large number of individual parts and the total system is not just the sum total of individual parts but much more than that. For example, imagine a human body. It has thousands of individual parts, but the ultimate human being with his intellectual and thinking powers is much more than the mere mechanical summation of the individual parts of the body.
Features of complexity economics
A writer on complexity economics, Steven N. Durlauf of the University of Wisconsin, USA, has elaborated on the main features of this new branch of economics in a paper he published in 1997 under the title ‘What Should Policy Makers Know about Economic Complexity?’
According to Durlauf, there are several main ideas underlying the subject. The first is that it is the direct interactions of people in an economy that leads to decision making. This is in contrast with conventional economics where it is believed that people interact in an economy through market prices and not directly with each other. However, the reality is that people have direct contacts with other people and are guided by them when they make decisions.
What I do is what my neighbour does
For instance, if all your friends use iPhones and not Samsung Galaxies, you tend to buy an iPhone conforming to the popular wisdom of your group despite the high price of iPhones compared to others of similar characteristics. Another example will be the voting pattern in elections. If elections are conducted stage by stage and not on a single day, the voting pattern of the elections conducted previously will influence the decision making of the voters in the subsequent elections.
Complexity economists call this ‘conformity effect’. This generates feedback effects, some positive and some negative, on individual decision making. The positive feedbacks can be ‘amplifying’ making the effect of the previous majority group decision much stronger on the subsequent decision makers.
Similarly, the negative feedbacks may be ‘damping’ making the effect of the feedback weaker than the previous group’s decisions. This is because an economy which is a complex system is much more than the summation of individual parts of the economy as being postulated in complexity economics.
Two together will produce a higher output than one each individually
The second arises from the increasing returns from the positive feedbacks described above. Durlauf has given the example of two scientists working together rather than individually. When they do so, they can make use of the positive feedbacks from each other’s work and make their findings much faster and much acceptable to the rest of the scientific community.
In effect, their output is larger than the summation of individual outputs. Thus, benefitting from these positive feedback effects, an economy which is complex and connected to each other will produce a much bigger output than an economy which is simple and not connected to each other.
Economies are also continuously evolving
The complex systems have several other aggregate characteristics too, according to Durlauf. One is the continuous evolution of the economy rather than remaining fixed as assumed in mainstream economics. Another is the non-linearity in economic relations, events and characteristics.
A third one is that an economy is always connected to its historical evolution so that today’s economy has certain resemblance and connection to what it was yesterday and tomorrow’s economy will have similar resemblance and connection to what it is today. It is not exactly the same between two time periods, but it is not different either.
An Atlas of Economic Complexity
Ricardo Hausmann and Cesar Hidalgo, with the support from Harvard University and the Massachusetts Institute of Technology, have applied the principles of complexity economics to design an atlas of economic complexity that maps paths to prosperity of nations in terms of the complexities underlying each economy in the world (available at: http://atlas.media.mit.edu/book/).
What Hausmann and others have done is to assess the complexity of each product being produced by a nation and prepare a map demonstrating its complexity level. For instance, the production of crude oil or timber is less complex than the production of turbines or jet engines. With the level of complexity which each nation has attained, it also accumulates a productive knowledge, as against the simple literacy which we measure to gauge the knowledge base of a nation. It is that productive knowledge that helps a nation to attain economic prosperity and sustain it in the long run provided nations have mechanisms to disperse that productive knowledge among its citizens and institutions to put it into practice.
Hausmann and others have concluded that most of the prosperous nations are wiser today not because their citizens are individually intelligent but because those nations have a diversity of knowhow and are able to recombine that diversity to create a wide range of smarter and better products. This process has been named by Hausmann and others as the ‘social accumulation of productive knowledge’.
What matters is not mere knowledge but productive knowledge
Thus, The Atlas of Economic Complexity is a measure of the level, diversity and the change in the productive knowledge of each nation as demonstrated by the complexity of the economies of each nation. Hausmann and others have used the Atlas to rank countries in terms of economic complexity and predict the future economic prosperity of these countries based on the historical development of economic complexity.
Sri Lanka ranks low in the Economic Complexity Index
According to the Economic Complexity Index for 2010, the country which has the most complex economy and therefore the highest productive knowledge base is Japan, followed by Germany and Switzerland. Singapore ranks at No. 7, the UK at No. 9 and USA at No. 13. These countries are ranked high because their production base is composed of complex products. In the Index, China is ranked at No. 29 because a large segment of its production base is still composed of simple products like garments, textiles, foods and construction materials.
Sri Lanka’s ranking in the index is No. 71, among countries like Namibia and Kenya. However, Australia, though a developed nation, is ranked below Sri Lanka at No. 79 because its production base is still composed of natural resources like coal, iron ore diamond, etc.
The projection of the future prosperity of nations in terms of the complexity of their economies is rather startling. Accordingly, China which many expect to overtake USA in the next couple of decades in terms of linear projections, is ranked at No. 70 in 2020, up from No. 81 in 2009. According to these projections, China’s per capita income is to rise from $ 3,744 in 2009 to $ 5,962 in 2020. The number one country in terms of per capita income is Norway followed by Switzerland. USA is projected to retain its position at No. 9, which it has in 2009 as well.
Sri Lanka’s prospects gloomy if simple economic structure is continued
The projections made for Sri Lanka should be an eye opener for the country’s policy authorities. In 2009, Sri Lanka with a per capita income of $ 2,068 is ranked at No. 92. If Sri Lanka has the same simple economy in the next 11-year period, it will have a per capita income of $ 2,852 in 2020, elevating its ranking by one notch to 91. This is in sharp contrast to what the policy authorities have projected for the country.
According to Sri Lanka’s current complexity map, almost 100 per cent of its products are simple products which can be copied by other competitors easily. Hence, year after year, Sri Lanka is facing the problem of maintaining and retaining a high economic growth. If the country wishes to move up and make that upward movement faster and sustainable, like Singapore, it has to convert its simple economy to a high tech based complex economy in the next 10-year period.
What Sri Lanka should do to attain that goal is discussed in the next My View.
(W.A. Wijewardena can be reached at email@example.com.)