The principles of laissez-faire capitalism are clear that government should not control business. This leads some people to think that government should have no involvement in business at all; that there is, or should be, a clear, bright line separating them. Obviously, that can’t happen. There is a constant dance about how they interact in terms of the total economy, but they are always interdependent. The debates being waged in Washington just indicate how complex this relationship is, and may indicate large shifts in the forces that balance them.
The idea that people hold “mental models” of the world may seem trivial or obvious, or both. Everyone has a way of seeing the world, affected by the cultures and the families in which we were raised, our own experiences, our personalities, and so on. Mostly, they account for our individual differences; why some of us are conservative and others liberal; some more optimistic and others pessimistic; some risk-taking and others more reserved and cautious.
The question of the “reality” of systems can quickly devolve into a philosophical battle about the nature of reality itself. Much of the answer for systems research depends upon how you define the system – as to whether it refers to the things that you are trying to learn about, or the process that you are using to investigate.
The position that I have taken is that “Systems are real for us, as humans, to the extent that we enact them.” As noted in a previous posting, both pigeons and fear are “real” in the sense that each can be examined as a phenomenon. Both may affect us in different ways, but though fear is more ephemeral, it is also real in its effect on human lives.
What, then, about something like money? The economic meltdown of the last week or so will continue to be analyzed by experts and pundits for a long time – and may yet have more consequences than we know. More importantly, whatever decisions are made in Washington, they are likely to affect all of us in very real ways. So to the degree that we participate in the economy, it is real.
The debate that has stalled decisions is largely philosophical. What is it that actually makes the economy function (i.e. what is the nature of the system)? Some see it from Adam Smith’s perspective, that left unhindered it functions as a self-organizing, self-balancing system. Others see it as a very human institution, controlled by powerful people and driven by greed and hubris. If you believe the former you simply try to rebalance it with as little intervention as possible. If you believe the latter you are inclined towards more regulation. In truth, we are likely to end up with some of both remedies, but only if they address the actual functioning of the system will they do any good.
At the risk of being just one more voice in the noise expressing half-informed opinions, let me try to use this as an example to sort through questions about systems.
My own approach is to start with the largest picture that (potentially) puts the rest in perspective. An economy is based on an exchange of goods and services. In what I think of as hunter-gatherer tribes, there was undoubtedly some division of labor, but resources were shared communally rather than exchanged. Once true exchange begins, there is a need to establish value of goods and services, even if it is for barter. (I need to believe that the day I spent pulling weeds from your farm is equal the repair that you did to my wagon, etc.) Bringing currency (e.g. paper money and coins) into the system just makes it more flexible, and less cumbersome to keep track of all of the actual exchanges and values in a barter system. I can take the money I receive as a promise of value, and exchange it for any number of other goods or services unrelated to my original work.
The pattern of action that creates an economy, as a system, is exchange. If the exchange stops the economy dies. Much of the incentive that keeps exchange flowing is the need for goods and services that you cannot produce for yourself. If we returned to living in communal tribes we could theoretically do away with economies – but we would have to get rid of most of the humans on the Earth in order to do that. In the mean time, purified water and electricity and fuel and food and clothing mostly come from centralized production sources, and people need money to exchange for those, and many other things.
Moving from a simple economy of exchange, though, to the world of finance, complicates matters. Systems of credit and debt let economies expand much faster than simple, direct exchange. If I run a farm that produces grain, I could spend a significant portion of my time finding buyers and transporting grain to them. If, though, I can count on you to sell my grain I can focus just on growing it. Assuming that you don’t have the money to buy all of my grain outright I could decide to let you take it on good faith (credit) and pay me for it after it’s sold. Alternatively, you could borrow the money from someone else (e.g. a bank), pay me now, and pay them after the grain is sold. In that case, of course, you would have to pay them back not only what you had borrowed, but also an additional amount (interest) for the use of their money. With the introduction of finance you have a whole new system – one that is related to the exchange of goods and services, but one on which money is used to make money.
The financial system, like the exchange of goods and services, has to remain in motion in order to survive. If everyone went back to paying cash for all transactions, banks (if they existed) would become nothing more than centralized safes, for which people might pay a small fee. If that were the case, though, very few people would ever have the kinds of houses in which they now live. Most would find it impossible to save the money needed to pay cash for a house because they would have been paying rent every month in the mean time. Likewise, businesses would have to accumulate cash in order to pay for materials and labor before goods and services could be sold, which would drastically limit their growth and the products they had to offer. So the financial system became the lifeblood of the economic system, so to speak.
Loaning money to other people, though, is a double-edged sword. It creates an income stream in the form of principle and interest that get repaid. A $200,000 mortgage, for instance, repaid at 6.25% over 30 years creates over $243,000 in interest payments. It also brings the risk that the borrower will not, for any number of reasons, repay the loan. To offset that risk, lenders rely on legal contracts, binding borrowers to their obligations, and on collateral that lenders can theoretically repossess and sell if necessary. On home mortgages, the houses themselves acted as the collateral, on the theory that they would be worth at least as much as the remaining principle of a loan if it went into default – a theory that got violated in the current financial meltdown.
Risk and reward became key principles in the financial system, and then turned into drivers of it. The greater the risk that a loan will not get repaid, the more costly it will be for a borrower to get a loan. This is not just a matter of poor character. It also has to do with things like the political stability of the place in which a borrower lives. Borrowers also become ill or die; businesses fail; buildings getting flooded or burn down, etc. In a stable and predictable environment, the probability of such occurrences can be calculated with some accuracy.
One way to offset risk is through insurance. In essence, insurers bet against the statistical odds. Knowing that only a certain number of calamities are likely to happen in a given, average year, they could charge relatively small premiums to large pools of people and expect to pay out less than they collected. In the mean time, the money that they held could be invested in other ways, allowing yet another income stream from it. Being a regulated industry, though, they are required to keep substantial sums of money safe in order to assure that they could cover even extreme years of disasters.
Financial systems also involve many areas that are not protected against losses, such as shares (stocks) of publicly traded companies. This has been the greatest pool of investments for businesses for generations, and also the central source of wealth for individual investors. But here the risks and rewards multiply. A good investment can multiply the money put into it many times over; a poor one can lose its entire value. Theoretically, the value of publicly traded companies fluctuates according to their performance in free market systems.
Throughout the economic system as a whole there remains a basic principle – that the value of what is owned and traded has some rationality, even if it is exceptionally relative and fluid. There are, for instance, formulas for calculating the intrinsic or fundamental values of an asset. These values get forgotten when markets heat up at times, but only relative to the amount of excess capacity in the market (e.g. savings, business profits, etc.), or speculation. When that capacity lessens, prices drop. I may choose to speculate on a piece of artwork at an auction and find myself caught up in a bidding frenzy against another fanatic. If I choose to pay an outrageous price to win the bidding I can hope that the artist gains popularity and favor with collectors, in case I decide to sell at some point. But the price I can get at any particular point in time will be a factor of the desires of other buyers in the market – and of their ability to pay.
By some reports, at the height of the mania about tulip bulbs in Holland in the 1630s, one bulb cost the equivalent of $76,000. Six weeks later, after the market crashed, it was worth $1. This was the bidding frenzy and the reality of the market. The ultimate price, though, was not a reflection of the financial capacity even of the very wealthy. It was the result of speculation amongst those who saw the opportunity to make money. Seeing prices rise, speculators with no interest in tulips per se took advantage of buying and selling, just as day-traders in stocks do today. The extent of the mania in Holland has been questioned by later research, including the idea that it represented a “bubble” like the one that preceded the stock market drop in the US in 2000. “For tulip mania to have qualified as an economic bubble, the price of tulip bulbs would need to have become unhinged from the intrinsic value of the bulbs” (http://en.wikipedia.org/wiki/Tulip_mania). Apparently some research said that it did not.
There are aspects of speculation that seem to make sense. If I know that I will need fuel for a fleet of vehicles in the future and I expect that the price of fuel will rise, it makes sense to pay less for it now. If I don’t have any place to store it, it makes even more sense to pay a supplier for the rights to buy it at an agreed price in the future. The supplier gets some money now and a known price for it then. (This is what Southwest Airlines did, which gave it a great advantage over other airlines in recent years.) The future price is a bet, and either I or the supplier will come out better on it, but it makes my future costs of business more predictable.
The point, though, at which trading becomes purely speculative, and unhinged from any intrinsic value, is the point at which the lines between investing and gambling blur to almost no distinction. While many might argue otherwise, this is one interpretation of what happened with the development of derivatives. Here’s a quick and simple definition:
Derivatives are financial instruments that derive their value from the value of another security or object. Futures contracts on pork bellies, crude oil, sugar, or copper, options on Wal-Mart or the S&P 500, and a bewildering array of securities linked to the movement of currencies, interest rates, housing prices, or even events—like the likelihood of a company defaulting on its credit. All these are derivatives (http://www.slate.com/id/2142158/)
Why would anyone take the risk of investing in something like that when they could own stock in a solid, blue-chip company?
The volume and investor interest in derivatives have soared in recent years for a variety of reasons, in part because stocks of big companies have been boring and less volatile. It’s difficult for professional traders to find much of an edge in the trading of Wal-Mart or General Electric when they simply move sideways over a several-year period. Meanwhile, commodities such as oil, natural gas, gold, platinum, copper, and ethanol have become highly volatile. The main way to play these markets is through derivatives. And the explosion of government and corporate debt in recent years has led to the development of new products that allow investors to assume or hedge interest-rate risk (http://www.slate.com/id/2142158/)
There seem to be two areas of significant concern and impact at the moment, which also converge in the middle of the problem. One is the failure of major financial institutions, and the other is the collapse in value of individual homes.
AIG was the first of the public financial institutions considered too big to be allowed to collapse. It actually operates as two separate entities – one a regulated insurance company, and the other a financial conglomerate. In all, it held over $1 trillion of assets through operations in 130 countries.
What do you do with $1 trillion in assets? Actually, you do two things at once. You use it to make more money, and you try to protect what you have. If you can do both simultaneously, you’ve done a great thing. The common strategy for protecting assets is hedging – essentially betting for and against the same thing at once. If you’re lucky, your wins pay off more than your losses. As derivatives got more and more complicated, though, all of this got more risky. The type of hedge that is blamed for a huge part of the latest problems is credit-default swaps. These are:
…private contracts that let firms trade bets on whether a borrower is going to default. When a default occurs, one party pays off the other. The value of the swaps rise and fall as the market reassesses the risk that a company won’t be able to honor its obligations. Firms use these instruments both as insurance — to hedge their exposures to risk — and to wager on the health of other companies. There are now credit-default swaps on more than $62 trillion in debt, up from about $144 billion a decade ago. One of the big new players in the swaps game was AIG, the world’s largest insurer and a major seller of credit-default swaps to financial institutions and companies (http://online.wsj.com/article/SB122169431617549947.html)
On the housing side, speculation had taken over as well. Buying a house is the largest investment that most families ever make, and for a long time represented the greatest source of assets. When real estate prices started rising rapidly, though, especially in places like California and Florida, both buyers and lenders began speculating – and we were back to tulips. On the lender side, though, it got more complicated. Mortgage companies apparently lost sight of any fundamental value at multiple levels. They lent far more money to people than their incomes and assets would justify, and they lent it on houses that were priced well beyond what could be justified – except by “exuberance.” They then offset their risks by bundling and selling packages of debt to other investors (after all, they were long-term, steady income streams, right?) This spread the risk, and later the damage, far into the economy as a whole.
And now the vicious cycles of feedback have begun. Those once-attractive adjustable mortgages ballooned so that homeowners couldn’t pay them. Banks started repossessing homes which no one wanted or could afford, starting the fall in the value of real estate. Banks and pension funds and investors who bought the debt lost large portions of their investments, driving down stock prices and the markets as a whole. Until the whole system begins to stabilize there is no way to value what remains, and therefore to calculate losses. Until that happens, banks are reluctant even to lend to each other, much less to small businesses or individuals. Even consumers who still have jobs and savings are reluctant to spend, slowing sales and growth of businesses, which will eventually result in job losses and less spending capacity in total.
And this is obviously not just an American problem. Markets around the world have been suffering significant losses, waiting to hear how this is going to get resolved. The numbers involved are amazing. As of 2005, there were $140 trillion worth of stocks, bonds and other financial assets, worldwide. Over $47 trillion of that was invested through institutions in the US. Moreover, the US has been the engine of consumption for a large part of the goods produced around the world. We are drowning in oceans of debt which there may be no one to pay.
As if we needed more, bigger dangers may loom in the future. With baby boomers starting to retire, there is a $53 trillion debt for Social Security (there are no savings – it gets funded by deductions from current workers) and that debt rises $2-3 trillion per year. It is not a pretty picture.
So where do you begin to target what is “real” – what will actually cause effective change – around all of the immense complexities and vested interests, in order to keep things afloat?
If the fundamental basis of the economy is exchange then that is what must take place. The Bush administration seems to have believed that by encouraging citizens to “spend the country out” of recent economic slowdowns (prior to this actual collapse.) That was the rationale for giving most Americans a special tax refund in the spring – increasing the national debt even further, of course. The theory would seem to be that debt doesn’t matter, you just have to keep the economy active until it recovers on its own. (That seems to be much akin to the idea that if you gamble long enough you’ll eventually win big and cover your debts, but I’m no economist.)
Ultimately, the economy survives on human activity. So there would seem to be some essentials about the functioning of the system related to that.
The first and most essential function is captured in economics as risk – but in human terms is about trust. Trust is fundamentally about the fulfillment of expectations. Promises and agreements that get made are kept. Information that is important gets disclosed. A value that is asserted gets confirmed (e.g. “yes, it’s really gold”). If I get cheated there is recourse, and so on.
At one level, people are not going to stop participating in exchange anyway. At least half of the world lives in cities, and few people still know how to hunt, farm, or weave cloth for making clothes. But the way that they approach exchange, even for basic needs, can be affected.
Much more at stake are the trillions of dollars of investments that have flowed through US banks and financial institutions. They have been at the heart of an international financial system which created trust that a fundamental value for assets could be established, and that despite periodic fluctuations in markets, sound investments over time would grow. That has been further evidenced by the importance of the US dollar as a key international currency, and the willingness of other countries to invest in it.
There is an aspect of “games” about economic systems. They are an ever-emerging pattern of interactions between humans. They exist because we participate in them. But our trust in them requires that there be some basis of rules – of acknowledged patterns – by which they function. Otherwise, there is no reason for people to save and invest for a time in the future when they are too old to work.
The danger of recent events is the perception that there is much more to be gained by manipulating the rules than by playing by them – that numbers in accounts have a reality unto themselves, with no need for a connection to the mundane things of life like sweat and soil. That is an expression of ignorance or hubris, or both. Left unchecked it could undermine the patterns of exchange in which people have been willing to participate, and tear at the very reality of economic systems.
How do you choose what you want to study – or learn more about, or better understand, or solve? In systems work, this entails the drawing of a boundary. The boundary separates what is to be examined from what is to be excluded. It defines the question or the problem. While this may seem patently simple, it is both the most fundamental step in a learning process, and the most complicated.
If you were a beginning student in science you might to study something like the food-gathering behaviors of pigeons as a project. Then you would have to decide where to find pigeons to observe. Pigeons seem to gather in parks in many cities, so that might be a convenient place to start. But when you get there and find pigeons eating bread from discarded hamburger buns, or popcorn tossed at them by children, what does that tell you about pigeons in general? You assume that you can generalize what you found to other birds like the ones you studied, but does that represent all pigeons? When do more research you find that pigeons and doves actually share the classification Family: Columbidae, and that there are 300 species within this one category, in locations all over the world. Most likely, the ones you saw in the park were feral Rock Pigeons, but even the terms pigeon and dove are not always used consistently. Since this particular project has no significant consequences, you just describe what you observed and predict that it applies to most pigeons like the ones you saw.
But what if you chose to study something much larger in concept, but less tangible? What if you chose to study fear? How would you begin to think about drawing a boundary?
Traditional researchers would probably react in a number of ways. First, they might tell you that you were crazy – that you can’t study things so large and nebulous. Then they might suggest that you narrow your study to some extremely small focus, like the fear response in rats subjected to unfamiliar stimuli, or whether fear can be detected by scent through hormonal changes in humans, or how fear affects perceptions of market conditions by stock brokers. You would then have to operationalize your definitions in order to have variables which could be observed and measured. In this case, the approach itself largely determines the boundary. If you’re going to do scientific research you have to do research that fits science.
You might decide to take this approach out of expediency (so that you could pass a class or complete a dissertation or get a grant.) But is studying finite aspects of fear the same as studying fear as a phenomenon? Frankly, no.
Then is it feasible to study fear as a phenomenon? It is theoretically possible. It clearly would not be easy, and there would be many, many disagreements about definitions and distinctions and approaches or methods.
The point is that if you want to study a particular thing, you need to be clear about what that is and draw the boundary appropriately. Most people don’t question this because it seems so obvious. I want to study pigeons so the boundary is around pigeons, right? Yes, until you learn that you need to distinguish between pigeons and doves and 300 species of them. Fortunately, science is filled with taxonomies for classifying almost everything, so you could just rely on those for making distinctions about pigeons (probably.)
If I want to study fear, is it any less “real” than pigeons? I doubt that many people would question the reality of fear, but still find it hard to compare to something they could see and touch. Whatever fear is, it seems to occur in animals as well as in humans. In fact, it seems to play a very crucial role in the behavior of most species above a certain level of anatomy and functioning. In order to study fear, though, I need to be as clear as I can about what that phenomenon is so that when I try to describe it I am describing it, not other things that may be related.
Drawing boundaries only gets more complicated when you begin to consider the many factors that can go into it. If the research or learning process is done simply on my own, for my own benefit, with no implication for any other people, then my decisions about boundaries can be fairly arbitrary. The way I define the subject may or may not make sense to other people, but I can just decide and deal with any consequences or complications. That rarely happens, though. Most research is carried out for some purpose in cooperation with other people, or at least with the intent that the findings will be accepted and understood by other people. In that case the boundary choices make more difference.
Systems theorists such as West Churchman, Werner Ulrich, Gerald Midgley, Mike Jackson, et al. have stressed the need for boundary critique – a process of questioning the choice of boundaries based both on philosophical and ethical considerations. Historically this was left to the Scientific Community or groups of professional experts to decide. The problem was that the drawing of every boundary involved a process of decision-making, and whoever was involved in that brought with them an existing pool of knowledge, ignorance and biases. In addition, many outcomes of affected people who were not a part of the process.
The discussions behind all of this got deeply into questions about the nature of knowledge and reality. If we can ultimately only understand the world through our senses and tools, as interpreted in our brains and through the languages that have evolved within our cultures, what is it that we really know? This is a critical question, but it’s been at the heart of debates for decades and is not going to get resolved here.
The result of these discussions led, in systems, to the links with participatory processes. If there was no absolute, fixed “truth” about the universe – if every way of understanding was limited, and involved some levels of interpretation – then you needed to think carefully about who was involved. If you omitted an important way of understanding, you might well miss important factors. From an ethical standpoint, people who are to be affected by decisions should have a chance to be involved in the information on which the decision is made. (From a practical standpoint, including stakeholders often garners support and reduces resistance when it comes time to implement a decision.)
The point in relation to boundaries is about how we decide to draw them. If things in the world are “real” then the boundaries that we use simply follow the natural boundaries in the world. If feral Rock Pigeons are an absolutely distinct species, then there should be no question whether one is or is not. (Not being a biologist, I’m sure what all the distinguishing characteristics are at the level of species.)
The messier question this leads to is whether systems are real. This is also a long-standing debate.
My Proposition: Systems are real for us, as humans, to the extent that we enact them.
This is not, for me, a matter of verbal or intellectual agreement. It is the extent to which we live as though things are real.
If this is skirting the issue about the nature of reality, I probably fall into a middle ground, so let me add just this much. If I slam my head down onto my desk, I expect that it will hurt – and I expect that it will hurt every time that I do it (until I lose consciousness.) Moreover, if we all slam our heads down onto our desks, I suspect that our reports of the experience will be fairly similar. Our heads and our desks are likely to seem quite real.
Not everything is quite that clear, though. When I was working in mental health in the 1980s, homosexuality was removed from the Diagnostic and Statistical Manual (classification of mental disorders) as a mental illness. Between the 1950s and the 1980s, depression was added to the DSM, with specific criteria to differentiate it from other disorders. Psychiatrists and other mental health care practitioners felt the need for a way to name a pattern of activity that they frequently encountered in practice. Benefits providers, on the other hand, strongly resisted this, since it codified the disorder as a medical malady that would need to be covered by insurance. Today, there is a debate about whether apathy should be included as a disorder in the upcoming revision, DSM-V.
My proposition is not intended to mean that systems are arbitrary human constructions. To the degree that we enact them, we endow them with real characteristics.
I have been struggling for years now with issues about systems. First, how do you introduce the basic principles of systems to students, or other people who are interested but have no previous background? There have been many different books and articles written at different levels, for different audiences, but (for me) all of them still leave questions or create additional confusion about what is really different about understanding things in terms of systems.
The most basic writings tend to use simple examples, explaining that a system is a collection of parts that creates a “whole” entity. You can have a box full of tires, spokes, chains, sprockets, metal tubing, etc. Only when those parts are assembled in a certain way, though, do they make a bicycle, which then has functionality as a means of transportation. The relationship of the parts to each other matters. But this is still a simple, mechanical system and often leaves the question, “so what – how does this explain anything new?”
Other common examples include the fact that there is nothing about the “wetness” of water that can be explained by the properties of oxygen or hydrogen molecules. It is only their formation into a system that allows this new property to emerge. The usual question is again, “so what? Isn’t this just like evolution? Over time, some things combined with others to form new, more complicated things?”
The more complex writings about systems start at the other end of the spectrum. Most quickly delve into philosophy and questions about the nature of human knowledge. Most also question traditional approaches and assumptions in science, while at the same time attempting to build on what is already known. In addition, many of the founding theorists and writers in systems were trained as scientists, and as such used mathematical formulas as the description and justification for their findings.
All of this only became more complicated as I tried to work with students in using systems as an approach for research. While there are a number of systems methods that make use of quantitative, computer-based models, they do not necessarily change the basic research approach. Agent-based modeling, for instance, is considered by many to be a systemic method, but there are many people using agent-based modeling that have no orientation to systems, as such, at all. So even in research and articles published in systems journals, or at systems conferences, there is often a looming question: is this particular piece of research systemic, and if so, is it because of the particular approach or methodology (and is that obvious), or is it only because of the orientation of the researcher (the user of the tool) or is there no necessary difference?
My own orientation to systems is much more basic and pragmatic, and that might be a helpful place to begin. (I have clearly drawn on and learned from many, many other theorists and writers; teachers and colleagues, but at this point is it much clearer for me to present my amalgamation of those ideas than to try to trace and credit every thread.)
Systems is for me a way of seeing and understanding; it is a way of framing or defining an issue.
For me, systems are patterns of activity.
This does not necessarily separate systems from traditional science. In physics and chemistry there is dynamic equilibrium. Atoms and molecules remain ever in motion, even within the most solid-looking substances, like granite. They just remain in a well-enough constrained pattern that they appear to us not to change. Most gasses, on the other hand, appear to have no substance at all. (Experiencing a gale or a hurricane or tornado changes that perception, of course.)
The things that we experience in life are all patterns of activity of one sort or another, held in dynamic equilibrium to different extents. Some are physical objects made of material elements; the chair that I sit in and the house in which I live. The chair lasts for a time; the house I expect to last longer. The water that I drink appears to be “gone,” but is only changed.
Many of the important things in our lives have strong psychological components. The stability of my home is more important than the structure of my house. I need for the people I love to remain “who they are” rather than becoming strangers.
This is where understanding – and research – become difficult. What are these things that I find so important, and how do I really come to know them? This is also where the break with traditional science often occurs.
I can understand many material objects by understanding the underlying components. I can take a watch apart and see what makes it “tick.” I can dissect a frog in science class and see the organs, but they only give me a limited amount of information in that state. (I can put the watch – a mechanical object – back together and it will work. I have to let other frogs make new frogs – a very different kind of system.)
Students in organizational studies often want to understand very complex things. Traditional scientific approaches normally imply either that (1) you can take it apart to see what makes it work, or (2) you can observe it like a culture in a Petri dish – and then in both cases you can measure and explain your observations with mathematical accuracy. Social science approaches sometimes limit the accuracy that can be expected by working only towards measures of correlation rather than causality, but still with a goal of being able to say something about the phenomenon in general (i.e. how it applies to the larger population) not just about the subjects of the study.
In the first case, identifying the parts of an organization almost inevitably results in the idea that “organizations are made up of people.” That is somewhat correct, but mostly not. All human social systems of every kind are comprised in some way of people, and the attributes and activities of people. Saying that people constitute organizations is like saying that gears and springs constitute watches. They sometimes do, but there are gears and springs in lots of things other than watches. And when you take some watches apart there are no gears and springs – there are parts that look more like the workings of cell phones or computers. The most unique and most common characteristic of a watch is its being an instrument for measuring time. There are many other instruments added onto watches today (e.g., altimeters, thermometers, heart monitors, global positioning systems, etc.) but if the basic instrument LACKS the ability to measure time, it is probably not going to qualify as a watch.
Complexity often leaves us in a quandary about identifying exactly what something is, and therefore explaining and predicting how it will work or behave. In that case, the best that we can often do is to explain what it’s like. It can be helpful, but it also sometimes comes at a price because the way that we understand something greatly affects what we expect of it. Gareth Morgan’s classic book, Images of Organizations, for instance, offers eight metaphors through which organizations might be seen (as a machine, as an organism, as a brain, etc.) Fortunately, he is careful to point out that “any theory or perspective we bring to the study of organization and management, while capable of creating valuable insights, is also incomplete, biased, and potentially misleading” (p. 5). Studying neural networks inside of Lehmann Brothers may provide useful insights, but it may not tell you anything about why it just filed for bankruptcy.
Most students, of course, don’t attempt to study an organization as a whole entity. Many attempt to study attributes or characteristics which they believe significantly affect organizations – for instance, transformational leadership. From a research standpoint, this still raises the same questions. What is this thing, this phenomenon, and how should you go about studying it? Most research courses throw students back to the approach of defining the variables of the phenomenon (taking it apart) and measuring them, with the hope that the measurements will add back up to the phenomenon. Not surprisingly, there is an instrument (the Multifactor Leadership Questionnaire) which breaks down the attributes and supposedly will “determine the degree to which leaders exhibited transformational and transactional leadership and the degree to which their followers were satisfied with their leader and their leader’s effectiveness.” Personally, I think that this puts us back at the watch analogy. The characteristics that get measured show up in lots of places (like gears and springs.) Gears and springs are one way to make a timepiece, but they aren’t the essence of it. You can make time devices with sand dropping through an hourglass, or using a sundial. So if you want to study leadership, what is IT, and then what difference does it make?
I have reconstructed this blog, at least for now, to test some of my own ideas about systems and the ways in which I understand them. Comments, questions, retorts, and alternate views are welcome.
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