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Thinking is how we build meaning for the information. Being aware of how we think and how the world works is called Systems Thinking.

Mental model is knowledge. The mental models you build are powerful thing because it determine how you feel and how you act. We use 4 simple patterns of systems thinking to build all of our mental models. DISTINCTION, we organize things into SYSTEMS (systems of part and wholes). We identify RELATIONSHIPS with actions and reaction or cause and effect. We take PERSPECTIVES from a point to a view.

How it can be used? :

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Systems Thinking: A Little Film About a Big Idea | Introduction to Cabrera Research Lab

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How it can be used? :

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Systems thinking has been described as a language for talking about the complex, interdependent issues managers face every day. Within that framework, causal loop diagrams can be thought of as sentences that are constructed by identifying the key variables in a system (the "nouns") and indicating the causal relationships between them via links (the "verbs"). By linking together several loops, you can create a concise story about a particular problem or issue.

A causal loop diagram consists of four basic elements: the variables, the links between them, the signs on the links (which show how the variables are interconnected), and the sign of the loop (which shows what type of behavior the system will produce). By representing a problem or issue from a causal perspective, you can become more aware of the structural forces that produce puzzling behavior.

By linking together several loops, you can create a concise story about a particular problem or issue.

Take the example of an HR team that has been responsible for integrating a Total Quality approach in an organization. In the beginning, there was much enthusiasm around the program, and demand for training was high. There were also some well-publicized successes in several local line teams. But over time, the TQM programs seemed to produce diminishing results, and interest in TQM activities slacked. What happened?

1. Create Variable Names

The first step in creating a causal "story" is to identify the nouns-or variables-that are important to the issue. Remember, a variable is something that can vary over time. In the TQM example, "TQM Activities" and demand for TQM Training" are important elements of the story. Upon further conversation, the team also agreed that the "Perceived Threat" of the new program was an important element, as was the "Resistance by Middle Managers" and their willingness to change.

2. Draw the Links

Once you have identified the variables, the next step is to fill in the "verbs," by linking the variables together and determining how one variable affects the other. In the language of systems thinking, links are labeled with either an "s" or an "o."

If variable B moves in the same direction as variable A, the link from variable A to B would be labeled with an "s"(or "+"). In the TQM story, the team noticed that in the beginning, TQM activities generated demand for TQM training-as activities went up, training went up (indicated by an "s" link). Similarly, as training increased, it generated even more TQM activities-another "s" link.

However, as TQM activities increased, the perceived threat of these activities also increased (another "s" link), which led to resistance by middle managers (another "s" link).

If variable B changes in a direction opposite of A (i.e., as A increases, B decreases), the link from A to B should be labeled with an "o" (or "-"). For example, the HR team noticed that, as the resistance by middle managers increased, the number of TQM activities decreased, which would be indicated by an "o."

At this point, the causal "story" consists of two causal loops that are linked through the common variable "TQM Activities."
3. Label the Loop
Once you have completed all of the links in the loop, you want to determine what type of behavior it will produce. In systems thinking, there are two basic types of causal loops: reinforcing and balancing. In a reinforcing loop, change in one direction is compounded by more change. For example, money in a savings account generates interest, which increases the balance in the savings account and earns more interest.

Balancing loops, in contrast, counter change in one direction with change in the opposite direction. Balancing processes attempt to bring things to a desired state and keep them there, much as a thermostat regulates the temperature in a house. For example, when we are hungry, our body sends a signal to our brain that it's time to eat, which appeases the hunger.

To determine if a loop is reinforcing or balancing, one quick method is to count the number of "o's." If there are an even number of "o's" (or none are present), the loop is reinforcing. If there are an odd number of "o's," it is a balancing loop. You should always double-check this method by walking through the loop to make sure the links are labeled correctly. In the TQM story, the "TQM Training" loop (which has two "s" links) is a reinforcing loop (labeled with an "R"), while the "Resistance by Middle Managers" loop (which has one "o" link) describes a balancing process that seeks to "balance" the growth in TQM activities (labeled with a "B").
TIP: Another way to double-check the expected type of loop is to draw the behavior of the system over time. A reinforcing loop shows exponential growth (or decay); a balancing loop tends to produce oscillation or movement toward equilibrium.
4. Talk Through the Loop

Once you have completed the causal loop diagram, it is wise to walk through the loops and "tell the story," to be sure the loops capture the behavior being described. In the TQM example, the loops tell the following story: "Initial TQM activities led to an increase in TQM training, which led to more TQM activities throughout the company. However, as the number of activities increased, the perceived threat also increased, which led to increased resistance by middle managers, and a decrease in overall TQM activities."

Storytelling

By using causal loop diagrams to create stories about complex issues, we can make our understanding of the interrelationships within a system's structure more explicit. The resulting diagrams also provide a visual representation that can be used to communicate that understanding with others. With practice, we can become more adept at telling systems stories that help us recognize the multiple, interdependent effects of our actions.
Colleen P. Lannon is co-founder of Pegasus Communications, Inc.

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Causal Loop Construction: The Basics - The Systems Thinker

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ystems thinking has been described as a language for talking about the complex, interdependent issues managers face every day. Within that framework, causal loop diagrams can be thought of as sentences that are constructed by identifying the key variables in a system (the "nouns") and indicating the causal relationships between them via links (the "verbs").

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Interconnectedness

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The convergence of the digital and the physical in the industrial world is a profound transformation that is far from fully appreciated. A connected device or machine becomes something entirely new. A smart phone, for example, still performs its original function; it allows you to make and receive telephone calls. But interconnectedness has rendered this a secondary function. The smart phone has new ways to make us more connected and informed (video chat, social networks, e-reader, and news and weather alerts). It is our concierge (restaurant reviews and bookings, taxi caller, online shopper). It is our entertainment system (music, TV, and games). It controls our thermostats, alarm systems, cars and more. A smart phone today is a fundamentally different object.

Cars are undergoing a similar transformation. Self-driving cars are already a reality. They can guide us on the most efficient route through web-enabled navigation systems and find the nearest gas station or restaurant; thanks to sensors, they can watch out for us, warning us if we stray from our lane, if we are about to turn when someone is in our blind spot, if we are at risk of hitting a pedestrian. In a Tesla, some technical problems can be fixed remotely by a technician at a computer hundreds of miles away. A car today is a fundamentally different object.

In a similar way, a company producing interconnected industrial devices becomes a fundamentally different company.

We have argued in previous work that the Industrial Internet and Advanced Manufacturing are not only transforming individual machines and systems, but they are also changing the nature of economies of scale, transforming the economic landscape and blurring the lines between manufacturing and services. In a similar way, industrial companies that combine the digital and the physical open entirely new dimensions in the way they operate and in the value they can provide to customers and shareholders.

Connecting the digital world of research, design, engineering and manufacturing enables a company to drastically reduce the time to introduce new products, leading to faster responses to customer needs and higher engineering productivity. Translating real-time factory and supply chain data into insights makes those factories and supply chains able to respond much faster to shifts in customer needs and external shocks. Linking engineering, supply chain operations, and services data through the cloud means operators can optimize factories and products in real time and continuously improve them throughout their lifecycle. As a result, machine uptime, throughput, and inventory turnovers increase. Higher responsiveness leads to higher sales.

Combining deep expertise in both digital technology and industrial machines is not easy. Both fields require complex and sophisticated domain expertise, and are experiencing fast-paced innovation. To be successful, a digital-industrial company must keep ahead of the curve on both fronts and be able to merge them seamlessly in a way that maximizes value. Just like innovation, design and manufacturing need to be closely intertwined to learn from each other and adapt to each other, so digital technologies and industrial manufacturing need to be melded to learn from each other and spur each other to reach higher levels of performance. Software development must be guided by the industrial machines' purpose, potential and limitations-and vice versa.

GE has achieved this combination by establishing a new Software Center of Excellence (COE) in San Ramon, Calif. With an investment of $1 billion in software and analytics over three years, GE has become one of the major software companies in the world with the San Ramon Center and regional software centers in Europe and China. GE now employs 14,000 software engineers.

More than 1,000 of these software and data science experts are concentrated in the San Ramon COE, working seamlessly with their counterparts in the company's industrial divisions from Oil & Gas to Transportation, from Aviation to Healthcare. Combining the software skills of the COE's experts with the sectoral experience of data scientists and data engineers in the industrial businesses is essential- both to maximize the joint value of digital and physical as well as to ensure the compatibility and adaptability of software solutions across industries.
Creating value: The platform and Industrial Internet solutions
Platforms are essential to enable and monetize the value of interconnectedness. Interconnectedness is all about communication, collaboration and compatibility, including for big industrial equipment, and it all starts with platforms. The power of platforms has been abundantly demonstrated in the digital world; just think of the burgeoning range of increasingly powerful apps on our smartphones.

A powerful platform can facilitate the compatibility of applications, delivering a number of benefits:

i. collecting and analyzing data from a larger set of different industrial assets, creating a deeper and more informative information set that delivers more effective insights;
ii. enabling the interoperability of a wider range of assets within an industrial operation or system, boosting operations optimization;
iii. allowing applications to be adapted and adopted across different industrial sectors;
iv. making it easier for developers, engineers and data scientists to collaborate on a wider range of industrial solutions, leveraging the Global Brain to the maximum effect.

Most engineering and manufacturing system design tools, as well as factories and supply chains, have a plethora of data sources that are often neither connected nor integrated. To unleash the power of data integration and systems-level analytics and optimization in manufacturing, it is critical to ensure interoperability between data sources.

Much effort has recently been expended in integrating the data of design, product engineering, and manufacturing engineering through product lifecycle management (PLM) tools. But we have yet to reach the stage where a change in design automatically propagates through all virtual validation tools, such as robot and controls emulation, throughput and process simulation, and productibility and model-based manufacturing tools.

In factories and supply chains, it is not uncommon to find 20 or more separate data collection systems, from Enterprise Resource Planning (ERP) to Manufacturing Execution Systems (MES) to energy management and homegrown quality systems. In fact, from a data collection perspective, every machine or controller might generate megabytes of data that often are not used to their fullest extent.

Integrating and fusing those data into one interoperable platform allows engineering, factory and supply chain leaders to gain visibility over their functions and to understand the system-level trade-offs of their decisions. Furthermore, the interoperability platform enables the development and implementation of generic engineering, factory, and supply chain tools that require only minor customization for different businesses and plants. These tools will unleash the power of analytics, simulation, and optimization providing leaders with (1) visualization of key performance integrators, (2) real-time decision support, and in some cases, (3) optimization and automation of decisions allowing them to focus on strategy and 'exception management' rather than day-to-day operations.

Platforms will play a key role in accelerating the growth and unleashing the value of the Industrial Internet, and the Future of Work more broadly. GE has developed Predix, our proprietary software platform for the Industrial Internet. Predix is designed specifically to meet the requirements and characteristics of industrial systems: it guarantees data security as well as mobility, it is optimized for machine-to-machine communication, and it supports distributed computing and big data analytics. Predix will support the rapid development of a growing number of applications for asset and operations optimization for a wide range of industrial sectors.

See how GE can give you the edge: gesoftware.com.

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Why Interconnectedness Matters for Industrial Companies - SPONSOR CONTENT INSIGHT FROM GE

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Networks

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Without Paul Volcker, T. Boone Pickens, and Michael Milken, we wouldn’t even be talking about a new economy.

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Tools, concepts of ST

How it can be used:

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Tools for Systems Thinkers: The 6 Fundamental Concepts of Systems Thinking

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In this series on systems thinking, I share the key insights and tools needed to develop and advance a systems mindset for dealing with…

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unclocking systems thinking

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Unlocking the Power of Systems Thinking — LEYLA ACAROGLU

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I have long been a fan of showing how problem solving desperately needs systems thinking . If you are familiar with my work, you may have already seen the series I wrote on Systems Thinking , but let me share the personal experience in how I came to uncover the power of thinking in systems , the

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CATS - interconnectdness moment of surprise - rats

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Systems thinking: a cautionary tale (cats in Borneo)

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"Is it always better to manage by design than by default"

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"Is it always better to manage by design than by default"

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Systems thinking: a cautionary tale (cats in Borneo)

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"Information alone isn't enough to solve problems, thats where thinking comes in"

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"Information alone isn't enough to solve problems, thats where thinking comes in"

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Saw this on Facebook feed and thought about this assignment

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confidence is the willingness to try - Mel Robins

with the competence goes confidence

thoughts:

confidence is a skill like any other skills and you need to practice on it to be better in it and to know how to use it the right way. Step by step, little by little like Grace mentioned in the video about GYM example. Person should stick to ones promises and start somewhere where the discomfort is not so overwhelmig like roll out a gym mat somewhere in the corner of the gym, and day by day get closer to the center floor to use GYM benefits freely and without a stress factor.

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How To Be Confident In 20 Minutes: A No BS Guide

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Systems Thinking | 6 mental models to add to your thinking toolbox

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Control Your Calendar (Not Your To-Do List) and Success Will Follow

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Our society celebrates getting things done. Long hours, overflowing inboxes, and maxed-out calendars become badges of honor. But this relentless pursuit of output can leave us feeling drained, disconnected, and unfulfilled. We neglect the things that truly matter to us—family, personal growth, health—because tasks, not our values, dictate our schedules.