Effective Tools for Solving Twenty
First Century Problems
 

We live in a world where our very survival depends on how we adapt to an ever-increasing barrage of challenges. Try to imagine your life moving into the next few decades. The tests we will face in the future will be much harder to tackle than those in the past; natural resources are depleting, the climate is changing, global finance is collapsing – all of these will have grave impacts on the growth, development and survival of each one of us, our communities as well as our institutions.

Traditional ways of solving problems tend to break them into smaller and smaller parts in order to find their underlying causes. Once the cause is identified, we try to influence the situation to bring it to a more desirable state; once we think the situation is under control, we move on to the next problem. Unfortunately, our problems are interconnected - they aren’t simply economic, or environmental, or social, or personal - they are interconnected because the world is made up of systems that have distinct characteristics and components which work together to serve a purpose. These components are linked together through ‘feedback’ loops and delays in information and material flows that often lead to unintended, unexpected and even counter-intuitive results.

One of the main reasons why we have such a poor track record in dealing with the challenges posed by the physical world is our inability to recognise influences, patterns, structures and the consequent behaviour of the various systems. Systems are all around us; in nature, factories, trade and commerce, our cities and indeed in our communities and families. When we fail to see our problems in the context of systems, we find that fixing one problem often creates another somewhere else, at some other time.

If we want to come up with effective solutions for these systemic problems, we will need a language that will help us identify relevant systems. Once this is done, we can find areas of weakness, strength and leverage.

To better understand this language (the language of Systems Thinking), let’s take an example of a problem common to most cities across the world: that of traffic congestion.

When congestion in a part of a city becomes unbearable, the traditional response by most public policy makers is to build new roads or widen the existing ones (See Figure 1).


Figure 1. Traditional non-systemic view of the problem

This is the traditional non-systemic way of problem solving – an event occurs, we find a ‘root’ cause of our problem (in this case, capacity of the road) and try to eliminate it (build a new road, widen the existing one). Anyone living in a growing city has seen that building a new road might bring short-term relief, but after some time, the problem of congestion resurfaces and more roads have to be built - this cycle perpetuates itself. Why?

Let’s take a look at what really influences congestion. By building new roads or widening them, the road capacity increases. As the road capacity increases, travel time, or the average time spent to get from one place to the next decreases and becomes more acceptable. It seems, at least for now, that the problem has been solved.

However, as ‘travel time’ decreases, gradually, the attractiveness to drive (See Figure 3) and to use personal transportation increases, often at the expense of using available public transportation. Furthermore, as the ‘attractiveness of driving increases’, so do the number of discretionary trips made by any one person who has a car or a motorbike. By using more personal transportation and making more discretionary trips, the volume of traffic on the road again increases over a period of time. The two feedback loops B2 and B3 soon begin to counter any short-term relief brought by building new roads!


Figure 2. If the actual travel time is greater than what is acceptable, there is an increase in the pressure to reduce congestion. As this pressure increases, more commitments are made to build or widen roads. After a delay of a few months, or even years, committed projects are completed and the road capacity increases; for a given traffic volume the travel time, therefore, decreases (at least in the short term)
 

The story doesn’t end here. Once road capacity increases - which includes the construction of highways - so does the size of a region accessible within an acceptable travel time. This means that people can now live farther away from the city and its problems and still get to work on time. As the surrounding suburbs of the city grow, so does their population. As the population of the suburbs grows, the number of cars commuting to and from the city increase, which further increases the traffic volume (loop B4). Again, the more cars there are on the roads for any given road capacity, the greater the congestion, the greater the ‘travel time’. Any benefit brought by building new roads or highways is countered, this time by a growing, commuting population from the surrounding territories. As the travel time again increases, there is once more an increased pressure to build more roads - a reinforcing feedback cycle in which the pressure to build more roads continuously escalates.

A careful study of the systemic forces which influence traffic congestion shows us four feedback loops which, in the long run, counteract any short-term benefits brought by increasing the road capacity.


Figure 3. The entire systems model with four feedback loops
which counter the benefits of increasing road capacity

Once the initial analysis of a system is complete, using influence diagrams it is usually a good idea to create a working computer model of the situation. Influence diagrams are good at showing cause-and-effect relationships between variables, i.e., ‘what would happen to B if I do something to A’, but they don’t show the behaviour over a period of time of the system. By trying to quantify the variables of the system using qualitative or quantitative data, one can create a basic computer simulation which shows us what would happen over time to the key variables.

Similarly, many other problems related to business, sustainable development and even our personal lives can be understood by looking at the larger systems of which they are a part. As a result, the language of systems thinking helps us better understand how seemingly well-intentioned policies can face resistance and, at times, can even make the problem worse.

The real power of systems thinking and system dynamics modeling comes from the fact that they allow us to clearly expose the mental models we have of any problem. The description of the traffic problem above comes from one person’s mental model of the actual situation. Mental models are ubiquitous and often taken for granted. If you ever find yourself in the middle of a heated debate with someone, chances are that both of you have opposing mental models of a particular situation. By using the systems thinking method, we can bring together various stakeholders by exposing their mental models and help them arrive at a common consensus.

In order to become successful in overcoming resistance to the solutions that we implement to fight our challenges, we need to put more effort into understanding these systems. Quick fixes, rules of thumb and flavour-of-the-month management techniques are becoming more and more common, but most of these methods do not account for the dynamic nature of systems. As we have learnt, our problems are not only interconnected, but they are continuously changing over time and space. Until we start looking at the bigger picture (and help others see it as well), by using the tools of systems thinking and system dynamics modeling, we will not be able to become effective change makers.

Nowhere is the practice of systems thinking more relevant than in the field of sustainable development, where often, the challenges we have to deal with directly affect the quality of life of people. The science and practice of this field needs a much more rigorous approach; a better understanding of systems is a good place to start. q

Karan Khosla
karankhosla@gmail.com
EarthSafe Enterprises

The author is the new generation change that we want to see in our society. He was the resource person for a three-day training workshop for the TARA Livelihood Academy on Systems Thinking and System Dynamics Modeling Workshop on November 26-28, 2009, in New Delhi.
 

 


Back to Contents
    Donation Home

Contact Us

About Us