Systems Thinking 101 | Anna Justice | TEDxFurmanU

[Music] hello welcome to systems thinking 101 when i tell people i am a sustainability

science major i'm often met with a head nod followed by a weight what's that now most people understand sustainability as sustainable development and in sustainable

development we are looking at how we can meet the needs of present generations without compromising the ability for future generations to meet their needs now today i'm just going to focus on one

aspect of what i have learned and applied to my daily life and that is systems thinking what is systems thinking well systems thinking is an integrative

way to view a large and complex issue as part of a group or system of elements together as a whole systems thinking requires you to take a step back and look at the big picture to understand

systems thinking you first need to understand systems to understand systems thinking you first need to understand systems now systems refers to how elements

interconnect and work together to form a unified whole examples of systems include the human body the human body has a set of dna

tissues cells muscles and they all rely on one another to function correctly a forest is an example of a system it has plants animals soil water

all to produce that specific type of landscape an economy is a system it has a set of rules behaviors and institutions that govern how a society should exchange

goods and services now systems can also exist within systems for example a city is a larger system that could be broken down into smaller

systems such as local government hospitals schools businesses residents and so on now there are two key takeaways here

systems are everywhere and they exist at various scales now systems have inputs and outputs in linear thinking we can easily see

that input a affects b which affects c which affects d and d is that final output since we can more easily process this and identify the cause and effect or

causal relationship we are more prone to be linear thinkers now what if outputs were also inputs in the same system or another one

well then we'd get something like this you might be wondering where does it begin where does it end well unlike linear thinking and circular thinking

there is no specified end you can see that there is continuous feedback among each element in the examples we are going through today we will be creating these loops

and identifying causal relationships and we are going to constantly be asking these two questions how the elements interacting or the system dynamics

and what is the goal of the system or the desired output a great way to begin systems mapping is through the iceberg model the iceberg model reminds us that what we initially see on the surface

isn't going to tell the whole story now at the top we have event the second layer is patterns and if you view that event over time you can maybe identify patterns

the third layer is structure and structure refers to systemic structures now let's say i bought a shirt last week and i bought it because it was trendy it was

at a good price well if we view this at the top layer there's not much else to it but let's move to the second layer at the second layer we could discuss how

this shirt in a year or maybe even a few months will no longer be trendy and then i might buy a new shirt and then that's going to repeat and generate a pattern

the third level is where we perform systems thinking now we're going to use a causal loop diagram a causal loop diagram is a visual aid to show how elements in a

system are interrelated and we are going to use words and arrows you can think of it like systems thinking art class now while we started with me buying a

new shirt we're going to take a step back and get a bit broader and we're going to identify the overarching system as the clothing industry

and focus on a clothing company now we need to identify the inputs and how they interact in the system so the clothing company has identified

demand there's demand for clothes and they have also found that customers will buy clothes if they're cheaper so then we move to production

the clothing company will make clothes cheaply by outsourcing labor and using cheaper materials this creates a lot of inventory

and in that inventory they want to sell it as much as they can so they can keep creating new products because new products increase customer attractiveness so this will increase marketing

as marketing increases so does the number of customers that buy clothes this generates profit and profit is a signal to the clothing company

to keep making more clothes so we can draw an arrow straight back to production now if you can see the little plus signs next to each arrow

that indicates positive reinforcement or an increase now while there are more variables in real life to complete this process for the sake of today's exercise we want

to keep it simple let's make another causal loop diagram we are going to stay within the same system the clothing industry but we are going to build off customers

so the customer buys clothes and then receives the clothes what's next well we assume that customer is going to wear those clothes so this increases the

clothing use over time and as clothes are more used they have an increased chance of wearing out or going out of style and that's going to indicate to the

customer to throw away the clothes or donate them and both of those options inevitably end up at a landfill now wait a minute

this doesn't look the same as our first example that's okay in systems thinking it can sometimes be hard to figure out that connecting arrow or

what's going to connect the loop can you see where we could draw an arrow from one of the variables back to customer now technically you can make a case for

any of those first three variables but i'm going to add an arrow from throwing away or donating clothes back to customer because typically when we get rid of clothes

we go and buy more and that makes us a customer again for that clothing company now let's take this example and connect it

back to our first example well then we get something like this whoa now looks complicated but guess what

you can now walk someone through this and if you're wondering what this is will you just use systems thinking to break down the complex issue a fast fashion

now fast fashion is a term to clothing industries that use this type of production to produce affordable clothes through the use of cheap materials and what that means is there is a trade-off

by having decreased clothing quality by using cheaper materials these clothes break down faster and they're much harder to recycle therefore we get a lot

of clothing waste in landfills now this is an undesirable result in the system but the clothing company is still meeting their desired output

to make profit by selling clothes let's walk through another example this time we're going to look at industrial agriculture now a bit of background is the goal of

industrial agriculture is to grow food it's to meet growing population demand now in large scale industrial agriculture

they use chemical fertilizers fertilizers are nutrients added to plants and crops to make them grow faster bigger and produce more food in a limited space

however chemical fertilizers in contrast to natural fertilizers are more potent so what happens is they are added in excess meaning we are adding more nutrients

than that plant or soil needs and this leads to soil degradation that soil becomes more acidic it becomes less porous meaning it cannot hold as much water

so now let's try to map this out using a causal loop diagram so we have identified demand there are people we need to feed and so this is going to increase the use

of chemical fertilizers now what do chemical fertilizers do well they increase the amount of food that we grow and harvest or crop yield

now crop yield that is our desired output so we can draw an arrow back to use of chemical fertilizers the increase in craft yield

signals to the farm to continue the use of chemical fertilizers now technically this loop is complete but it doesn't tell the whole story of this system

what did we discover about the use of chemical fertilizers i'm going to draw an arrow from use of chemical fertilizers to a new variable

soil quality we put a minus sign by this arrow to show a negative effect or decrease and if the use of chemical fertilizers is lessening the soil quality

this then lessens the crop yield because crops cannot grow as well and pour soil do you see a conundrum in this system we'd expect that a decrease in soil

quality would signal the farm to use less chemical fertilizers but it actually increases the need why is that

well remember the desired output for this system is food so their focus is growing more food so if they see that soil is struggling and so are the crops

they're just going to add more fertilizer and what can happen over time is as that soil keeps degrading it can be more easily carried away by

wind or washed away by water and what that means is some day in the future we might not have soil to plant crops in now i'm going to stop there but this is

one of my favorite systems examples because while it looks deceivingly simple it has huge implications for so many

other systems to be able to function now today we use systems thinking to look at the system dynamics of fast fashion and industrial

agriculture in both systems we saw undesirable results clothing waste and landfills and soil quality going down

now systems are not inherently right or wrong they have developed over time based on our values and beliefs and ultimately as these systems developed they weren't aware that they might be

creating a problem in another system and systems come with surprises and unintended consequences the next step is what my major is about solutions thinking

we are looking at where we could intervene and change the system this is the equivalent of adding a new arrow or variable

and we hope that we could somehow mitigate any unwanted outputs could we have a clothing system where clothes are never sent to a landfill and are recycled back into

production can we grow enough food to meet current demand while letting our soil rebuild at the same time my hope for you today is not to solve

either of these problems they are very complex and there is no one solution my hope is that you can see the effectiveness of systems thinking and

identifying connections and understanding why any system behaves the way it does what i love about systems thinking is how it has changed my perspective

i see the world differently now because i can identify these connections more easily and i can see the subsequent impacts they have even when it is no longer directly impacting me

when i make decisions i can see that i play a part into larger systems by using systems thinking to understand how

a system is achieving its desired results i can make better informed decisions based on my own individual values i hope i have inspired you to incorporate more systems thinking into

your life and if you're still unsure where to start ask questions have a curiosity to think deeper ask those questions that are going to

make you take a step back and look at the big picture so the next time you're shopping for clothes or buying produce from a grocery store

or even throw something in the trash can i want you to think of all the steps that item went through to get into your hands and then i challenge you to also think

of all the steps that item will go through once it leaves your hands remember that systems are everywhere and you are part of these systems

you have an impact therefore your actions matter thank you for coming to my ted talk