I was back in the classroom, this week, interacting with bright students at Indian School of Development Management, Noida. These students challenged me to my core. Their sharp questions would often test my own depths – related to my knowledge of systems thinking, my understanding of how real world systems operate, my experience of working with communities and policy makers. It is these students who help me go deeper and explore my previously unexplored depths of knowledge and some glimpses of wisdom which is hidden deep within (this is true for all of us). It is a matter of time before some one helps us unearth it.
After many examples on how systems thinking is used, by making causal loops, and also by going through the systems thinking process, I finally decided to put up two slides which say what Systems Thinking is and what it is Not. These are my own, so I encouraged the students to add/modify them depending on their understanding and reading of the literature.
I am pasting these below:
What Systems Thinking is
–Method of Thinking
–Method to perform systemic diagnoses
–Engagement tool useful for communication
–Learning tool useful for testing assumptions
–Identifying impact pathways and
–Reasons that give rise to non linearity of system’s behavior
–Potential tool to generate insights and foresights
What Systems Thinking is NOT
–to predict future reality
–to control reality
–to identify who is to be blamed
–to be used in isolation
–to solve all problems at once
–to prove superiority
–to win arguments for the sake of just winning
Before the closing of our 16 hours of engagement, I requested students to keep these points in mind when they go out to interact with the real world complexities and the multiple stakeholders who would present their perspectives which would give them some information about why things are happening the way it is happening, but it would never be enough for them to understand reality in totallity.
In the next post I would elaborate on these points more to explain why I put them there. Stay Tuned!
There is a famous saying, “It takes a village to raise a child”. This week I saw it in action. What I also saw was the relatively inefficient and purposefully expensive way of bringing up children in urban ecosystems back home. I then took help of systems thinking to synthesize my observations and feelings. Some of them I am writing down here below…
In the hills of Devprayag there is a small village called Kim Khola. Until last month it would take a 45 min trek to climb a mountain to reach this village. But I was lucky. There is a road under construction which goes right upto the village. The taxi guy was generous enough to drive the car into the kachcha road. He took us as far as he thought was safe, not for us but for the car. We got down on the top of the mountain. We then went downhill to reach the village and went to the house where I was to spend two nights and two days.
It was in a nice setting. East facing porch, toilets, a traditional kitchen (with a wood stove) and one new kitchen with LPG. Two nice big rooms and a breathtaking terrace. The owner of the house also maintained a garden with newly planted Rosemary. He was a nice progressive chap. The house cooked amazing food. I ate with great satisfaction. Pleasant weather made my stay even more comfortable. It was a relief to be away from Delhi heat.
I was there for a purpose. My job was to uncover the reasons for disappearance of water springs of Kim Khola and how it has affected life of villagers, what they are thinking to do now and what kind of future do they envisage. I should say I was able to uncover some key things that I would not have if I was in Delhi reading on internet about Kim Khola and its springs. What I understood would be out in the publications as part of the project and I would share those when ready.
Apart from all the intelligent stuff, for which I get paid, I also observed social and cultural dynamics which were not part of my questionnaire or so called research scope. The home I was staying in was of a family having two teenagers, one boy and one girl. I would see the girl in house more often than I would see the boy. She would assist her mother in household chores with great skills and purpose. My mind first went towards categorizing this in the gender imbalance research theme, which we researchers jut love to spot every now and then. Its kind of that we are programmed. With some difficulty I tried to unlearn the gender stuff and started observing the structure more closely.
First, I think what I saw was a gender system evolved over time. It was not that the village was trying to copy an alien culture. Second, I think the boy use to be out of house through out the day but I did not feel any sense of discomfort in the family. They were at great peace with his behavior, partially because they were focused on doing what they do and more importantly they knew that the whole village is one big family. In cities we call them care takers. They are now increasingly being found inside day care set ups. One has to pay hefty money to be partially sure that their kid is in safe hands. Forget about things like learning by doing, interacting with nature, socializing etc. just finding a safe place to park your kids is enough. And this does not guarantee that the parents and family would feel no sense of anxiety.
How does systems thinking help understand what I observe? At a meta level, I am essentially comparing two systems here, village and city. The former acts more like a coupled system of Nature and Humans. Both interact and shape each other. Eg. The forests change in response to humans (massive deforestation for wood) and humans change in response to forests (loss of livelihood forcing out-migration). In between these interactions evolves the culture of the human network of friends and family. Cities act like a coupled system of Economy and Humans. Both interact and shape each other. Eg. The jobs change in response to humans (higher spending creates more jobs) and humans change in response to jobs (high paying jobs lead to increased spending). In between these interactions evolves the culture of the human network of friends and family.
If you observe, both the examples I give are reinforcing in nature. If forests go up the livelihood opportunities go up and so people help the forest grow. While if forests go down the livelihood opportunities go down and people start consuming the forest for sustenance. Similarly more spending creates more jobs leading to even more spending while fewer jobs create poor business growth further weakening the job market. The place based culture evolves through a combination of multiple such reinforcing and balancing processes. It is the combination of such processes that leads to the behavior of the system. Raising children in cities is becoming more expensive, high paying jobs are few, simultaneously social fragmentation is increasing leading to more spending on buying social services. Depleting forests and loss of traditional springs is leading to spatial fragmentation of the households causing increase in labor. The gender dimensions in the village or cities are not isolated events of this system. They also get affected and evolve over time with its changing environment.
Using such multi loop reflection I told myself that what I see, observe or collect information is just tip of the iceberg. Drawing conclusions based on that would be silly. Even though I may be able to jot down a hell lot of facts (like the time spent by boys and girls on household chores etc.). But reaching conclusions based on data/information that we are able to measure or see at a point in time is not uncommon. We are always tempted to run campaigns based on facts and data, often leaving out the deep structures, the reinforcing and balancing processes, whose interactions lead to events that we see.
“It takes a village to raise a child”. Of course it would, where else would a child be able to learn through the dance of interactions between human, economic and natural systems in a safe environment.
Farmers in India and across the world are witnessing new variations in weather and seasonal changes. The challenge to take decisions under these variations gets compounded because often there is no precedent to it. What decisions work best can be known through experimentation and mostly in hindsight. This makes adaptation to climate change a complex process. The cause-effect conundrum, i.e. which solution gives what result is almost impossible to predict with certainty. Thus, human decision making under such unforeseen situations needs to be aided by additional information or decision support systems. Climate Services, the delivery of weather based agriculture advisories using ICT, help aid farmer’s decision making process by providing timely weather forecasts and corresponding advisories on agricultural practices.
The information farmers receive on climate services provides them with an option of incorporating it into their agriculture decision making. But it is almost impossible to measure with certainty how much of this information do they incorporate, in what form and when. This makes impact evaluation of adaptation solutions, like climate services, a very challenging exercise. At times even the farmers are unable to clearly demarcate the important variables they use for their decision making process. This is so because in order to cope with weather variations there are many possible actions and solutions to be experimented with. But the most effective solutions may not be known to them at the early stages and thus their decision making keeps evolving as they experiment with a set of solutions. Through this process of iterative decision making they learn to adapt to weather variations. This makes adaptation a highly localized and continuous process with no clear traces of solution impact pathways. But a set of good practices evolve over time.
Challenges to measure or generate evidence of adaptation further hinder the uptake and popularity of good practices. There is also a theoretical difficulty in establishing units for measuring adaptation and establish monitoring systems for its evaluation. This makes communicating adaptation through evidence a very difficult task. It also challenges the imagination of policy makers who mostly rely on numbers for estimating impacts. For example, the climate mitigation negotiations use the 2°C limit of temperature rise as the reference for determining how much emissions need to be reduced to achieve this climate goal. But in case of adaptation there is a dearth of quantifiable numbers which could guide the policy planning process. Thus, policy making for adaptation requires a shift of two kinds
1) Moving away from relying only on numbers, and
2) Decentralization of policy making to account for localized adaptation processes.
This shift further brings up two challenges
1) How to measure what is intangible or un-measured, and
2) At what scale should the policy making process be localized.
Unless research on climate change adaptation focuses to find answer to these two challenges, policy making for adaptation to climate change would remain a very challenging task.
Note: This article was first posted on my linkedin on October 3, 2016 for TERI’s World Sustainable Development Summit 2016. Link: https://www.linkedin.com/pulse/challenge-policy-making-climate-change-adaptation-mihir-mathur/
Many people have been asking me how to use systems thinking, how to make models, what are the steps that I follow, how does the development process unfold? To be honest, there is not set template that one can follow and reach the end. As John Sterman says, “It is inherently a creative process.” But there are steps which can guide the model building process. Sterman in his book, Business Dynamics, mentions these steps in detail and I recommend everyone interested to go through them. I myself has used them to write proposals on research using systems thinking and modeling. But over time I realized that applying them required some degree of adaptation of these steps. Since in India the degree of complexity is relatively more as compared to other developed countries where data is available and reliable under most circumstances, we need to be very creative while trying to understand complex systems using systems thinking. To give an example, while working in rural areas one realizes how poor is the data availability even for critical resources such as ground water. I remember once on a water wind mill assessment trip we were struggling to identify water hand pumps which are dry and which are still pumping water, what is their depth, when they were installed etc. People in villages had some vague idea about their date or year of installation, depth etc. But all that was not good enough for us to take a call on whether to implement a water windmill or not. The only parameters for which data was available and reliable (to an extent) was the meteorological conditions i.e. the wind speed, direction, precipitation etc. That too because WOTR had Automated Weather Stations installed there. So this goes to show that while working in India data availability and reliability is a big constraint. The second constraint is the information and knowledge available to understand the local dynamics. Another example being, people in villages find it very difficult to estimate their household numbers be it water, finance, energy or livestock productivity. For eg. their income and expenses figures rarely tally. Giving them the benefit of doubt that they take short term loans, receive some money through family, friends etc. even then all these numbers would often not add up. I have had a first hand experience on this issue too. So modeling social, ecological and economic systems in informal setting in India is a hard, hard work. Lot of assumptions and (educated) guesstimates have to be done to complete any sort of modeling process.
All this relates to how one then applies systems thinking and modeling in dynamically complex situations and systems in India? Does John’s modeling process and steps help our cause? In my opinion they do, albeit to a limited extent. One needs to creatively adapt them and use his/her sensing to move ahead. In my experience serendipity also plays an important role. Almost every time I have been badly stuck in some of the most challenging modeling projects and then I have found a way out either by someone willfully joining the work or through some support. All of it being not part of original plan.
So after doing some modeling work in very un-ordered settings I have adapted John’s modeling steps and have penned them down. The pre requirements before these steps are that the problem has been identified, modelers have familiarized themselves with it and proper scoping exercise has been done with the end user and experts. The modeling steps then are:
Define purpose of the model and read about the issue or system of interest
List down sectors, sub systems and determine model boundary
Create Dynamic Hypothesis (DH)
Develop questions based on DH
Show DH to community (end user) and experts
Review the questions and DH after step 5
Collect information and data using questions developed in step 6
Develop initial versions of simulation model
Review DH based on simulation model
Show revised DH to community (end users) and experts
Show initial simulation results to community (end users) and experts
(Incorporate suggestions) Revise the model, its boundaries and develop questions to fill in information and data gaps
Collect data and information to fill the gaps
Develop progressive versions of model (eg. v2, 3…… v17…. and repeat step 13
Perform model calibration, sensitivity runs, extreme conditions test and finalize the model (sometimes back-casting also helps in model evaluation)
Share the results with community for mobilization and aiding action
Make model readable and fit for publication and dissemination
Get the model reviewed by an expert and incorporate suggestions
Publish the model and results
Plan for next phase and how to go deeper into the issue to initiate change process, then start from Step 12 or any other appropriate step as suited
The most important thing to remember is to celebrate learning at each step and document the learning process. You would often be surprised that the learning process is an equally important and influential outcome of the modeling process as much as the end simulation results are.
Where did I learn systems thinking? The answer is simple but confusing, even to me. Technically, I learnt it at my post grad college, Sadhana Center for Management and Leadership Development, Pune. This was a subject in our curriculum. We studied it for two years. First year we had systems thinking and then an elective on system dynamics modeling. Sushil Bajpai and Rajinder Raina were our mentors, professors, friends and fellow systems thinkers. They had this impossible task of teaching systems thinking to 160 idiots. When I reflect now I think my performance in class and particularly in exams was below par. That is according to my standards and interpretation. But my mark-sheet tells a different story. May be my professors were liberal, may be they saw something more than what exam results or written answers told them. They had an insight and a foresight on how to identify, nurture interest and develop potential systems thinkers.
But I did not really learn systems thinking alone in my college. I was introduced to it there, I read and heard it there, I also practiced it, applying to some of our corporate strategy cases. I had used it to study Dell company’s strategy on how their business model was different from others. Organised a systems thinking seminar calling the commissioner of Pune plus more audience. Sushil and Rajinder got Shiela Damodaran to Pune to conduct that seminar and we did more stuff. Linking Vipassana to Systems Thinking, the business model of Dabbawalas to principles of systems thinking. All that was very good but I was not really a systems thinking practitioner back then.
When I joined WOTR, Sept 2009, I worked with Sushil Bajpai and a bunch of brilliant folks there working on really complex social and ecological issues. The project was on climate change adaptation. It had all the elements of real world complexity that one can imagine. It also had institutional complexity which was to dealt with bringing in elements of learning organization pedagogy (more on this later). The project was a pioneering effort in the field of climate change adaptation in India. WOTR had a credible name and evidence in field which made them a potent force for community based natural resource management. But this project was a different animal and it brought in new animals at WOTR. I was one of them.
I learnt systems thinking outside my class room. A lot was learnt by observation and not implementation. For around 2 years, I was a fence watcher. Not committing myself into any one activity of the project but learning and observing about what is going on everywhere and what I think could happen. All these years I had the luxury to learn, read, observe, unlearn, relearn. This opportunity was rare, perhaps once in a lifetime. Did I made most of it? Only time will tell. But I had a ball. We use to have intense practical and philosophical discussions on what is true adaptation, why humans fail to understand how their actions are killing themselves, why peak oil would redesign our lives, would peak water hit us first or peak oil or are we living in an age of peak everything? Lot of systems thinking was used in our discussion. I was a mere spect-actor and Sushil did most of the thinking, talking and doing. It was like we had a high quality TED talk every week, coming from our field experiences and books that we use to read and the project ambitions. We use to be very critical of ourselves, our actions and the project itself. Questioning the sustainability of the institution, the project, ourselves and should we even live in cities anymore? Should we reverse migrate? Those were crazy discussions, beyond office space, at our homes, common meeting places, over beer and biryani.
I learnt systems thinking by looking and observing reality and then linking it with the theory of systems thinking. By reading books, not only on systems thinking but on multiple disciplines. I learnt systems thinking at WOTR, by listening to Sushil, by working on field with the team, by talking to community, friends, remembering the theories of books while seeing real world dynamics unfolding on field. I learnt it by practice but not only through implementation. I saw why and how implementation often is weak in rural areas and how, while I was leading some verticals of the projects, I was still making the same mistakes. I understood the power of the system we are in and how it influences our behavior. How we speak one thing, but do another and then still are unaware.
I think I did multiple post grads while at WOTR from 2009 till 2014. Un-parallel to any other experience. I learnt systems thinking through that journey and the journey still continues bringing in more surprises, twists and turns.
For many years people have asked me how is systems thinking different and what is so unique about it. What is the advantage of using it over other methods and techniques? To be honest, I did not had a short and convincing answer back then. It would take me 15 mins of talking to convey what I wanted to say and that too was incomplete. This of course meant that people did not get a clean and cogent answer to their question. I would also substantiate in the end by saying please read on systems thinking and then verbally mention couple of books. With more people asking me this question over time my responses improved incrementally. But they were still not good enough. Probably what was lacking in me was a thorough, continuous application of systems thinking and modeling on real world situations. Every now and then I use to use systems thinking tools to understand peak oil impacts, localisation benefits, resilience to climate change etc. but then the result was my improved understanding of these issues which would help me in my research and community work. This was particularly helpful for the climate change adaptation project that I was part of at WOTR. But how do I communicate this to others? What evidence exists?
Three years back I got an opportunity to apply systems thinking and modeling for urbanization project at TERI. Kabir and I spearheaded a team of young researchers and developed a city model representing urban carrying capacity and people’s quality of life. We did lot of systems thinking training and use of causal loop diagrams to draw how we understood the city system. A two day training was conducted on system dynamics modeling. The project was successfully delivered and generated much interest among its readers. Then we embarked on economics of grassland degradation project. This was an almost impossible project. We had the task of modeling a grassland ecosystem, Banni, in Kachch. There were so many unkowns in the system that at one point we thought of giving up. But then we worked hard and got very good support from our colleagues at TERI and research support by (institutions) Sahjeevan and ATREE. That project was a leap for us to understand the potential of applying systems thinking and modeling to solve real world problems.
After doing further projects on application of systems thinking and then teaching it to over 1000 students, now I feel I have a better answer to the question, ” What is the advantage of applying systems thinking?”. What I am about to write is purely my interpretation of the benefits I see and is not coming out of a text book. So one must be critical.
Let me quote the great Albert Einstein here, “We cannot solve our problems with the same thinking we used when we created them.” I paraphrase this, “Today’s problems come from yesterday’s solutions and today’s solutions will create tomorrow’s problems.” This speaks volumes about our journey in life and how we adapt and live. If this is true then I think systems thinking and modeling has a big role to play.
I think the real benefit of applying systems thinking to real world problems and even for theory development is that, ” It could help us take decisions and design policies, rules which would reduce the recurrence and severity of the problem we are trying to solve”. This I think is the biggest (potential) benefit of applying systems thinking and modeling. This could be achieved through multiple pathways. It is not necessary that one needs to implement the solutions and only then the results would come. Even the improvement in our understanding about the complexity of real world is instrumental in improving the policy design and decision rules which we use to run our families, companies, society and nations.
The only rider I would attach is that one needs to be very very honest while applying systems thinking and modeling because unlike other disciplines (statistics, math etc.) this discipline depends a lot more on who is modeling and whose mental models really matter. The reliance on the honesty and capability of the researcher and actor is of paramount importance if the potential benefit of applying systems thinking and modeling is to be achieved, as I describe it.
I think my biggest strength, that I discovered, was not my ability to do advance math or expertise in software or field research. It was my ability to stay put, pursue systems thinking and work through my limitations over time. There were a bunch of my classmates and colleagues who, in my opinion, were far better at systems thinking than me. But today I am the only one using it for a living. And I am no scholar or genius like them.
So systems thinking and modeling is for people like us, who are ready to learn and build their capacities. Why? Because I think it is very useful. How? Because, ” It could help us take decisions and design policies, rules which would reduce the recurrence and severity of the problem we are trying to solve”
I write this post today after an engaging day with students at ISDM on systems thinking and sustainability. The classes start at 9 am and continue till 5 pm. Today was the fourth day and it seems like we have come a long way, not only in terms of students learning systems thinking but the quality of engagement has reached a new level.
The striking point came when students asked me to explain my day at work, on how do I use systems thinking there and the process of its application. The question was striking because it made me feel like the students wanted to know how I have managed to reach this stage where I am doing professional projects using systems thinking and system dynamics. More so because for them the subject looked too difficult to apply in real world for finding solutions. They couldn’t really imagine on how diving deep into complexity of real world problems could yield fruitful results and generate solutions in today’s world. The question was also striking because it gave me a sense of honor because here were a bunch of 65 students interested to learn from my experience.
I feel motivated now to write this post and more on this subject to explain how I started my journey of becoming a systems thinker and convert my skills into professional occupation.
It was in July 2007 when I first learned about systems thinking. Mr. Sushil Bajpai and Mr. Rajinder Raina took our first class on systems thinking at Sadhana Center for Management and Leadership Development (SCMLD), Pune. The first presentation showed to us was of images from zoom book, a view of life going from microscopic to telescopic. That first presentation made an impression on me. What a fantastic way it was to show how things are interconnected and that we live in a world of systems and sub systems.
The next deck of slides explained us the definition of A System. How do we know what is a system and what is not a system. This was a tricky question. Reads easy but when one thinks about it, it is not so easy to define it well. After some deliberation out came the answer, “A System is made up of parts which are interrelated, interconnected, interdependent having a purpose”. We all went berserk in identifying systems all around us. Since then the subject never really left me. I went on diving deep into it. In the next classes we were introduced to Mental Models. That class in particular was fascinating. It introduced us to the fact that how all of us interpret reality, build images in our mind and use them to take decisions. More importantly that these mental models are flawed, because we use rationality to simplify reality which implies that there are lot of assumptions there which make our mental models inadequate and incomplete. This was quite a revelation for me. I came from a financial markets experience and there the whole game was who has got it right and who knows reality the best in order to predict it and mint money. The best analysts would draw large pay based on how well their models performed in relation with reality. This thought was so well rooted in me that learning about mental models was actually life changing.
The initial few classes had cemented a space for systems thinking in my life. Interestingly, one night in my hostel room, Amey Phadke and I were chatting just before calling it a day. Lying on our beds, with lights put off, we were asking each other where do we see ourselves after five years from now. I cannot remember what Amey replied, but I do remember clearly what I had said, because I said what I really deeply believed. I said, “It looks like I will join stock markets after college, but if you really ask me – deep within I feel that I am made for systems thinking and that’s where I would land up. Honestly speaking I think I would be doing systems thinking”. I did join stock markets after my post grad building equity valuation models for oil and gas companies, doing commodity research and interacting with institutional investors. But within six months I switched careers and moved on to work with Mr. Sushil Bajpai at WOTR and there began my journey of systems thinking and system dynamics, on job. And here I am today writing a post on it after 10 years of having that conversation with Amey at my hostel room.
The journey so far has been full of turning points and life changing moments, some planned, most unplanned.
I have struggled to put what is systems thinking into a succinct definition for a long time. I have also struggled to find a definition of systems thinking which makes most sense to me and captures the gist of systems thinking through that definition. My struggle began 10 years back, when systems thinking was first introduced in my post grad. Since then I have been giving long answers (and different versions every-time) to anyone who asks or writes to me “What is systems thinking?”.
Somewhere between 2015 and 2016 I decided to make a glossary of systems vocabulary, more for my personal use and then again came the question of what is systems thinking. So I decided to write down a definition which made most sense to me. The first version of it I shared with Gene Bellinger and after a brief exchange of emails with him I zeroed down on a definition that was acceptable to me.
Two days back I was taking a day long workshop cum lecture at Indian School of Development Management at Noida in NCR (National Capital Region of Delhi). After going through the slides explaining what is a system, what is not a system, how to identify systems, examples of systems, types of systems I came to the slide having my definition of systems thinking. Mr. Arun Maira, former member of Planning Commission of India, was there in the class, with whom I was doing team teaching. He expressed that it was one of the most refined definitions of systems thinking that he had seen or read. This motivated me and today I decided that I should publish the definition (via informal means like this for now) for gaining more feedback and to improve it further. Thus, I am posting the definition here for readers to evaluate it and provide feedback on how much sense does it make and how well it captures the essence of systems thinking. All views are welcome.
Systems Thinking Definition:
Systems thinking is the process of understanding relationships between variables within a system and between different systems and how they influence each other’s behavior over time.
The above definition is typed by me but I think many people, entities and their work has contributed to my learning which has lead me to this definition. I may not be able to remember them all and write down here, but let me try.
Sushil Bajpai, Rajinder Raina, MS Pillai, Rajesh Rajak, John Sterman, Donella Meadows, Khalid Saeed, Jay Forrester, Andrew Ford, Kenneth Boulding, Gene Bellinger, Arun Maira, Kabir Sharma, Pradnya Mathur, Sadhana Center for Management and Leadership Development (SCMLD), Tata Institute of Social Science (TISS), Watershed Organisation Trust (WOTR), The Energy and Resources Institute (TERI), Sustainability Dynamics (my own unregistered consultancy), International System Dynamics Society, System Dynamics Society of India (IIT Kharagpur) and All my students at TISS and SCMLD.
Came across this article this afternoon and it made so much sense to learn from that I thought of sharing it here. Please do read and share with others.
Dana’s advice for writing for change, whether in an OpEd, article, blog, etc.
BE CLEAR. Be specific, not abstract. Give examples, and be sure your words make pictures in peoples’ heads. Tell stories, give statistics, show the impact of the problem or the solution on the real world. People can form their own conclusions, if you give them the evidence.
USE A HOOK TO THE NEWS. People have to know why what they’re about to read is important. They think the daily news is important, so use that hook, even if you’re not going to talk about the daily news.
WRITE AN INTERESTING LEAD. A friendly editor once blasted me with: “That was the most terrific column you ever wrote, but it had a boring, killer lead.” A killer lead is an opening sentence that makes the reader yawn and turn to the sports page. (E.g. instead of “I have just had the privilege of escorting six Hungarian visitors on a cross-country tour of the United States. All six are agricultural experts. They came to see our farms.” It would have been better to start with something right out of the middle of the story: “The Hungarians thought Burger King was great. ‘So clean,’ they said. When they saw people carrying their own trays, they said, ‘So socialist.’”)
NEVER WRITE IN AN APOLOGETIC TONE, or a defensive one. Never, ever, ever, condescend to the reader. Never present a problem without providing at least a hint of what to do about it. Don’t get people all riled up and then drop them into helplessness.
WHATEVER YOUR SUBJECT, TELL IT THROUGH PEOPLE. Human beings are much more interested in other human beings than they are in ideas. If you care about something, let your care show as well as your objective evidence. If you’re writing about someone else – hero or villain – make that person as real and whole on paper as you possibly can.
BE HUMBLE. You don’t know everything. In fact no human being knows much of anything, compared with the immense wonders and uncertainties of the universe, so keep a sense of perspective. Say just what you can say and no more, say it with the appropriate degree of certainty and no more. That is the hardest lesson for me to follow. It’s a torture every day and a duty, a wonderful discipline and a Zen koan, the bane of my existence and the best challenge of my life.
Re posted from: https://www.facebook.com/DonellaMeadowsInstitute/
In the last few years the climate change threat has started to get a little too real to us. Temperatures have more or less stayed above 50 degrees C this summer in parts of India. The country has also been affected by drought for the second year running. “We have already done enough emissions which shall make the (global) average temperatures go up. Climate change is not something which will happen in the future. It is happening right now. April 2016 was one of the hottest months on record. Earth’s average surface temperature has already increased by around 1 degree C compared to pre industrial times and it is estimated that we are headed for up to a 3 degree C rise which could lead to dangerous climate change impact.”
The warning comes from climate change researcher Mihir Mathur, associate fellow, Earth Science and Climate Change Division at The Energy and Resources Institute (TERI) in New Delhi, who is picking up danger signals from planet earth and wants to mitigate the impact. For Mathur, climate change is a personal as well as global issue. Every individual has to worry. “Those who think that it is the responsibility of only governments and researchers to learn (about) and find solutions to climate change are not thinking right. There is no point in having a national or a state level climate policy when people don’t understand its importance or rationale.”
Surprisingly this researcher in climate change adaptation for policy formulation at the local and macro level comes from a finance background. He received his bachelor of commerce in accountancy from Maharaja Sayajirao University, Vadodara (his hometown), following it up with a master’s degree in finance from the Sadhana Centre for Management and Leadership Development, Pune.
What led to the switch? While working in the stock markets Mathur discovered how fossil fuel depletion would put a limit on economic growth. He asked himself deeper questions: was the nature of this growth sustainable? As he found out more about the interconnections between fossil fuels, emissions and climate change, he felt a “deeper calling to research upon sustainability issues rather than only use my skills in stock markets”. The turning point came when he discovered the issue of oil depletion (popularly known as Peak Oil) which could hit the world much before climate change. Research on peak oil (point in time when oil production peaks and then begins to terminally decline) made him realise that the world was very close to reaching the peak globally and that a systemic shift was needed if the world had to sustain itself. That discovery drove him to take up research on finding solutions to peak oil and climate change.
For field work, Mathur has to interact with farming communities to find out how weather variations challenge their agriculture decision-making. He studies how weather forecasts and agriculture advisories (sent by the India Meteorological Department and other private players) are helping farmers cope with these variations. He also works on developing future scenarios using computer modelling (simulating what happens or will happen in a situation) to understand how policies can bring about desired changes. A modelling project was recently completed where he developed an urban model using system dynamics modelling (understanding complicated problems using mathematical modelling techniques) to understand city futures, how cities would grow in future and factors limiting their growth.
Solutions for human beings to adapt better to the changes in weather and climate could be social, financial, environmental, economic etc, so his research is, in a sense, interdisciplinary. His research findings help improve the body of knowledge on climate change and are likely to contribute as inputs for development planning and policy planning.
Mathur has been part of one of the biggest climate change adaptation programmes in India, implemented by Watershed Organisation Trust in Maharashtra, MP and AP, covering more than 50 villages. For him it was an experience to learn how rural India understood climate change and the practical challenges it faced while moving towards adaptation and mitigation measures. He feels the whole project was a success as they were able to implement renewable energy solutions at scale, generate livelihood opportunities, do watershed development work, promote water budgeting and management, develop biodiversity registers, create disaster risk reduction plans, install automated weather stations for real time weather data at village level etc.
More recently, Mathur has been practicing system dynamics modelling to better understand how social, economic and environmental systems function and interact with each other. The idea is to understand and present the complexity of real life systems to academia, policy makers, researchers and everyone else. “Through the modelling,” he explains “ I am able to show how seemingly different sectors interact with each other and intervening in one sector could create a cascading impact on other sectors. An increase in the water supply for a city would lead to increase in demand for electricity (through pumping etc) which in turn could lead to increase of power supply which again could lead to increased water consumption for electricity generation. And that’s not all, increase in water consumption could lead to increased waste water discharge and without any increase in sewage capacities it could lead to water borne diseases. This is a hypothetical scenario but it’s clear that it is impossible to understand the dynamics of the real world without going through the process of studying their interlinkages.”
When it comes to global negotiations on climate change, Mathur says India is not going wrong as the country’s per capita emissions are very low as compared to developed nations. It is not fair to expect India to go on an aggressive mitigation strategy at the cost of development which has yet to cover all of its people. However, a low carbon development vision would definitely mitigate emissions and achieve sustainable development. As India’s geography, cultures, ecosystems, agro ecological zones are very diverse it is almost impossible to have one strategy that fits all. To have bottom up development planning and integrating it with the top down climate change vision is a challenge. India has developed State level Action Plans on Climate Change and also has City Resilience Plans which are to get integrated with City Development Plans and Master Plans. Results, however, will only be visible in the future. India does have policies in place but to implement it and achieve the desired results at scale has been a problem. Mathur feels India’s greatest strength is its network of villages and if sustainable development is achieved in the country’s six lakh villages then the country could achieve its development and climate goals with much ease. Along with India’s focus on smart cities, it is important that the villages are not left out as they form the base of the country’s pyramid.
Models of a city that he has put together reveal that the quality of life in cities is going to deteriorate very soon (in some places it already has) mainly due to rising environmental pollution. While many of them may continue to choose to live in cities with a deteriorating quality of life, there would come a tipping point where cities become unattractive and people would start searching for other places to relocate. “I have heard of such discussions already taking place among people living in big metropolises,” Mathur says.
Thus, he hopes that through his modelling work someday he will be able to develop tools to enable effective decision making (at the government or global level) for climate change planning.
Climate change, in 20 words is
Non normal variations in rainfall and temperatures with shift in seasons and increase in frequency of extreme weather events