This document provides an overview of a presentation on systems thinking and complexity as applied to policing. It discusses how policing deals with "wicked problems" and complexity on a daily basis. It encourages shifting from a problem-solution mindset to understanding the system as a whole before determining solutions. The document presents various concepts including systems thinking, bias, heuristics, limits, and case studies to illustrate how visualizing systems and understanding all influencing factors can provide a richer perspective for determining effective strategies and solutions. The key messages are to seek diverse perspectives, think critically, be aware of biases, and welcome exploring problems as complex systems rather than isolated issues.
The talk I gave at the 2015 IxDA Education Summit about using systems thinking and emergence as a lens to integrate systems thinking/emergence, distributed cognition, Christopher Alexander's pattern languages, scenarios, and lean processes.
Gigamap example by Manuela Aguirre: https://www.slideshare.net/ManuelaAguirre/policy-support-full-presentation
In this presentation you will learn about design tools and techniques to solve wicked problems, using Systems Thinking.
Systems Thinking looks at the whole of a system rather than focusing on its individual parts, to better understand complex phenomena. Systems Thinking contrasts with analytic thinking: you solve problems by going deeper, by looking at the greater whole of a system and the relations between its elements, rather than solving individual problems in a linear way via simple cause and effect explanations.
You can apply Systems Thinking principles in different situations: to understand how large organisations function and design for the enterprise (e.g. when you are trying to revamp a large intranet), but also to solve social problems and issues (e.g. unemployment with disadvantaged youth or mobility in larger cities). So basically whenever there is complexity and conflict (of interest) in your project, Systems Thinking will be helpful.
After an introduction to Systems Thinking and its core concepts, we will first explain and practice a few techniques that you as a designer can apply to better understand complex systems, for example creating a System Map and drawing Connection Circles. In the second part of the workshop, we will introduce techniques that help you shape solutions, for example using Paradoxical Thinking for ideation and writing ‘What-if’ Scenarios.
Presented at EuroIA 2015 with Koen Peters.
This document provides an introduction and background on the Doctus expert system. It discusses Simon's concepts of bounded rationality and programmed vs non-programmed decisions. It also describes the different types of decisions as reflex, routine, and original and how the Doctus system supports each type through deductive reasoning and knowledge bases. The document serves to set up an overview of the lessons learned from 18 years of using the Doctus system to support executives in their decision making.
Beyond the Knowledge Base: Turning Data into Wisdom - an ITSM Academy WebinarKaren Skiles
Many organizations live perceiving Knowledge Management begins and ends with a Knowledge Base. However, a more robust Knowledge Management process exists. The KM process is a pipeline to Continual Service Improvement. This presentation provides insight and methods for developing and implementing a more comprehensive Knowledge Management process leading to improvement throughout the enterprise. This presentation covers design of the KM process, DIKW and its usages, the KM-CSI connection, knowledge repositories and much more.
Measuring Risk - What Doesn’t Work and What DoesJody Keyser
The topics for this webinar include:
The Problem – Why your method may be a “management placebo” and why that is the biggest risk you have Problems that many methods ignore – and problems some methods introduce What Does Work – Studies reveal some methods show consistent, measurable improvements on the forecasts and decisions of managers
Examples of Real Improvements
Overview of Applied Information Economics (AIE) Process Common Objections to quantitative methods and the misconceptions behind them
Questions & Answers
In den letzten fünf Jahren ist das Ökosystem der auf KI basierten Anwendungen explodiert. Die Anwendungen haben jetzt schon einen grösseren Einfluss auf unser Leben, als den meisten Menschen bewusst ist. Mit den neuen Technologien sind Chancen und Risiken verbunden. Im Gegensatz zu den apokalyptischen Szenarien einer auf KI basierten Superintelligenz gibt es ganz reale Probleme mit diesen Systemen. Dieser Vortrag zeigt auf, wo diese Probleme liegen und warum es nötig ist, dass ein Diskurs darüber in der Politik und in der Öffentlichkeit immer dringlicher wird.
This document summarizes Chapter 10 from the textbook "Introduction to Information Technology" by Turban, Rainer and Potter. The chapter discusses managerial support systems, including decision support systems, executive support systems, and intelligent systems like expert systems and artificial neural networks. It describes how these systems can help managers with decision making, capturing expertise, and analyzing large amounts of data.
The talk I gave at the 2015 IxDA Education Summit about using systems thinking and emergence as a lens to integrate systems thinking/emergence, distributed cognition, Christopher Alexander's pattern languages, scenarios, and lean processes.
Gigamap example by Manuela Aguirre: https://www.slideshare.net/ManuelaAguirre/policy-support-full-presentation
In this presentation you will learn about design tools and techniques to solve wicked problems, using Systems Thinking.
Systems Thinking looks at the whole of a system rather than focusing on its individual parts, to better understand complex phenomena. Systems Thinking contrasts with analytic thinking: you solve problems by going deeper, by looking at the greater whole of a system and the relations between its elements, rather than solving individual problems in a linear way via simple cause and effect explanations.
You can apply Systems Thinking principles in different situations: to understand how large organisations function and design for the enterprise (e.g. when you are trying to revamp a large intranet), but also to solve social problems and issues (e.g. unemployment with disadvantaged youth or mobility in larger cities). So basically whenever there is complexity and conflict (of interest) in your project, Systems Thinking will be helpful.
After an introduction to Systems Thinking and its core concepts, we will first explain and practice a few techniques that you as a designer can apply to better understand complex systems, for example creating a System Map and drawing Connection Circles. In the second part of the workshop, we will introduce techniques that help you shape solutions, for example using Paradoxical Thinking for ideation and writing ‘What-if’ Scenarios.
Presented at EuroIA 2015 with Koen Peters.
This document provides an introduction and background on the Doctus expert system. It discusses Simon's concepts of bounded rationality and programmed vs non-programmed decisions. It also describes the different types of decisions as reflex, routine, and original and how the Doctus system supports each type through deductive reasoning and knowledge bases. The document serves to set up an overview of the lessons learned from 18 years of using the Doctus system to support executives in their decision making.
Beyond the Knowledge Base: Turning Data into Wisdom - an ITSM Academy WebinarKaren Skiles
Many organizations live perceiving Knowledge Management begins and ends with a Knowledge Base. However, a more robust Knowledge Management process exists. The KM process is a pipeline to Continual Service Improvement. This presentation provides insight and methods for developing and implementing a more comprehensive Knowledge Management process leading to improvement throughout the enterprise. This presentation covers design of the KM process, DIKW and its usages, the KM-CSI connection, knowledge repositories and much more.
Measuring Risk - What Doesn’t Work and What DoesJody Keyser
The topics for this webinar include:
The Problem – Why your method may be a “management placebo” and why that is the biggest risk you have Problems that many methods ignore – and problems some methods introduce What Does Work – Studies reveal some methods show consistent, measurable improvements on the forecasts and decisions of managers
Examples of Real Improvements
Overview of Applied Information Economics (AIE) Process Common Objections to quantitative methods and the misconceptions behind them
Questions & Answers
In den letzten fünf Jahren ist das Ökosystem der auf KI basierten Anwendungen explodiert. Die Anwendungen haben jetzt schon einen grösseren Einfluss auf unser Leben, als den meisten Menschen bewusst ist. Mit den neuen Technologien sind Chancen und Risiken verbunden. Im Gegensatz zu den apokalyptischen Szenarien einer auf KI basierten Superintelligenz gibt es ganz reale Probleme mit diesen Systemen. Dieser Vortrag zeigt auf, wo diese Probleme liegen und warum es nötig ist, dass ein Diskurs darüber in der Politik und in der Öffentlichkeit immer dringlicher wird.
This document summarizes Chapter 10 from the textbook "Introduction to Information Technology" by Turban, Rainer and Potter. The chapter discusses managerial support systems, including decision support systems, executive support systems, and intelligent systems like expert systems and artificial neural networks. It describes how these systems can help managers with decision making, capturing expertise, and analyzing large amounts of data.
Automated decision making with predictive applications – Big Data BrusselsLars Trieloff
This document discusses automated decision making with big data and predictive applications. It begins by looking at how decisions are currently made, which is often based on qualitative factors rather than data-driven insights. It then examines how predictive applications work by collecting and analyzing data to build models that can make decisions and be tested and optimized. The document argues that predictive applications can help reduce risk and costs while increasing revenue by enabling trends to be estimated, classifications to be made, and events to be predicted to optimize returns. It presents the idea of having a common platform for building, running, and monitoring predictive applications using both internal and external data.
Slides for "Intro to Systems Thinking" workshop. Session details and resources available here: http://pwoessner.wikispaces.com/Introduction+to+Systems+Thinking
Brighttalk outage insurance- what you need to know - finalAndrew White
This document provides an overview of Andrew White's experience in systems monitoring and event management. It discusses his 15 years of experience designing and managing deployment of monitoring software at IBM and other Fortune 100 companies. It also lists some of his previous roles and responsibilities at those organizations, including leading monitoring teams and developing custom solutions.
Systems thinking is a holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems. The document discusses systems thinking approaches like considering causal loops and flows within systems. It provides an example of how applying pesticides to reduce crop damage from one insect can have unintended consequences by disrupting the natural controls on other insect populations. The document advocates using systems modeling and a strategic outlook to better understand complex problems and their systemic causes.
Case Study on Professional Issues of Interactive Mediaguest2bf64e
The document presents a case study about Julian and Margaret McAdam who lost out on purchasing a new house because CreditWorthy, a credit rating company, mistakenly reported that Julian had defaulted on a previous mortgage due to a database error. While some argue the database should be updated to prevent future mistakes, others argue the costs outweigh the benefits given how few people are affected. The document discusses various ethical approaches to the situation such as utilitarianism, common good, and rights.
Cynefin and Complexity: A Gentle IntroductionJocko Selberg
NYC Lean Kanban Meetup - Presentation October 28, 2015 - Jocko Selberg
What do we really mean when we say that a problem is "complex"? Do we simply mean to say that a given problem is extremely complicated, or are complex problems something fundamentally different? We typically assume we are operating in a deterministic, ordered system where we can identify a cause and effect relationship, when in actuality we are often operating in a non-deterministic complex system, where these relationships can not be known in advance, if at all. How can we sense which context we are operating in and how might we act under varying degrees of uncertainty.
Complexity Theory is a term used to describe a field that is focused on the study of complex systems. Complexity science is not a single theory— it encompasses multiple theoretical frameworks, seeking answers to some of the fundamental questions about continuously changing, dynamic systems.
Cynefin is a framework developed by Dave Snowden and Cognitive Edge which seeks to helps us "make sense of the world, such that we can act in it". By understanding the fundamental differences between directed (ordered) systems and emergent (unordered) systems, we can modify our approach to match the context of the problem we are facing. The Cynefin framework takes a science based approach to dealing with critical business issues, drawing from anthropology, neuroscience and complex adaptive systems theory to improve decision making.
Complexity Theory and Cynefin have an undeserved reputation for being difficult to grasp. In this introductory talk we will break down these approaches so that we can effectively use them to help us to better act under conditions of uncertainty.
About Jocko Selberg
Jocko Selberg is currently a Project Manager for The Nielsen Company with over 15 years experience in the interactive industry. He is a non-sectarian agilist and does not own a TV.
ARTIFICIAL INTELLIGENCE, COGNITIVE TECHNOLOGIES AND DIGITAL LABOREmmanuel Gillain
bring a simple and concise summary of what the cognitive technologies enabling “Digital Labor” mean in order to raise the awareness level amongst the non technical people that care about the technology impacts on business, economy and society.
Brighttalk reason 114 for learning math - finalAndrew White
The document discusses using analytics to improve service assurance. It provides background on Andrew White, who has 15 years of experience designing systems monitoring and event management software. It then discusses how analytics can be used by CIOs to deliver better outcomes through techniques like big data analytics, security intelligence, mobile and cloud technologies.
This document discusses systems thinking and key concepts related to systems. It defines systems thinking as the cognitive process of studying and understanding systems of any kind by examining the linkages and interactions between interconnected components. A system is defined as a set of elements organized in a structure that produces characteristic behaviors. Key components of systems include elements, interconnections, and function. The document contrasts System 1 and System 2 thinking and provides examples. It emphasizes that systems thinking is needed to address problems created by more simplistic levels of thinking.
Big data is data that is too large to process with traditional software. As computers get smaller, cheaper, and more powerful, more computing resources can be applied to big data through cloud computing. Machine learning algorithms can analyze big data to build predictive applications that forecast outcomes and optimize decisions. However, enterprises have doubts and concerns about adopting predictive applications due to issues around data availability, predictability, understandability, and ensuring the results can be executed on.
Automated decision making with predictive applications – Big Data AmsterdamLars Trieloff
My slides from tonight's talk at Impact HUB in Amsterdam on big data, machine learning, cognitive biases and how to overcome them with predictive applications.
This seminar report provides an overview of systems thinking and key concepts. It defines systems thinking as viewing problems as parts of an overall system rather than in isolation. A system is a collection of parts integrated to accomplish an overall goal, with inputs, processes, outputs and outcomes, and feedback. Systems can be biological, mechanical, social, or other types and range from simple to complex. Systems theory studies principles that can be applied to all types of systems. Some basic principles of systems thinking discussed are that change is slow but lasting, cause and effect are not always closely linked, and easy answers often do not address complexity. The report also lists examples of systems principles like how a system's behavior depends on its structure and how systems seek
Smartcon 2015 – Automated Decisions in the Supply ChainLars Trieloff
This document discusses the process of automating decisions using predictive applications and machine learning models. It begins by outlining how predictive applications work by collecting and storing data, analyzing correlations, building decision models, and deciding and testing outcomes. The document then discusses challenges like predicting demand and order quantities. It provides an example of using sales forecasts and probability distributions to determine optimal order amounts while minimizing stock-out risks. Finally, it discusses how enterprises adopt predictive applications, addressing concerns around data availability, predictability, understandability, and executability, and outlines the potential financial impacts.
An overview of Systems Thinking, and how to apply the ideas of Complexity Theory to management of systems, with the results being called "Complexity Thinking".
This presentation is part of the Management 3.0 course created by Jurgen Appelo.
http://www.management30.com/course-introduction/
System Thinking - Affect on Decision MakingMuhammad Awais
The document discusses systems thinking and its impact on decision making. It begins with introductions to systems concepts and definitions of systems thinking. It describes the difference between system 1 and system 2 thinking, with system 1 being fast, automatic thinking and system 2 being slower, effortful thinking. It emphasizes that in today's complex and interconnected world, systems thinking is needed to understand complex problems and avoid unintended consequences of decisions. Systems thinking provides a holistic view rather than a narrow, reductionist view to help make better decisions. The document provides examples of applying systems thinking in various domains and argues it is a new way of thinking needed to address challenges of the current century.
General observations about managerial accounting informationSanTelmo Carrefour
This document discusses several key points about managerial accounting information:
1) Accounting numbers are intended for different purposes and require different approaches, so the same terms can mean different things depending on the context. This causes confusion if not properly understood.
2) Accounting numbers are approximations, especially estimates for future planning, so their accuracy varies. Users must understand the degree of approximation.
3) Management problems often involve incomplete data, so decisions must be made with the information available. Obtaining missing vital information is important, but action cannot always be delayed.
4) Accounting provides only a partial view, as important factors cannot always be quantified. Both solely numerical analysis and relying only on intuition are flawed
The Problem with dots: A critique of the Lessig and Murray modelsmrleiser
My presentation to the Information Technology Law students of the LSE on regulatory theory of the Internet. We touch on Lessig, Murray, rationality, pathetic dots, network communitarianism and big data.
On Analyzing Self-Driving Networks: A Systems Thinking Approach Junaid Qadir
This document provides an overview of systems thinking approaches for analyzing self-driving networks. It discusses the problems with conventional non-systems thinking, such as mental models and reductionism. It then defines key concepts in systems thinking like feedback loops, leverage points, and archetypes. The document applies these concepts to challenges in internet architecture like spam, privacy, and quality of service. It also discusses ethical and policy challenges for self-driving networks, like who will make ethical decisions. The document concludes that systems thinking is needed to understand complex interactions in self-driving networks and their effects on stakeholders.
This document discusses strengths-based assessment, design, and implementation approaches as alternatives to traditional approaches. It notes that traditional implementation attempts often fail between 80-90% of the time. Strengths-based approaches focus on identifying existing strengths and assets within a system rather than focusing only on needs or deficiencies. The document contrasts traditional deficit-based consulting models with potential strengths-based consulting models that engage stakeholders and leverage existing resources.
ACCOUNT WRITING Past Papers Inside. Online assignment writing service.Lorri Bynes
This document provides instructions for requesting and completing an assignment writing request on the HelpWriting.net website. It outlines a 5-step process: 1) Create an account with an email and password. 2) Complete a 10-minute order form providing instructions, sources, and deadline. 3) Review bids from writers and choose one based on qualifications. 4) Review the completed paper and authorize payment. 5) Request revisions until satisfied with the work. The document stresses that original, high-quality work is guaranteed or a full refund will be provided.
Automated decision making with predictive applications – Big Data BrusselsLars Trieloff
This document discusses automated decision making with big data and predictive applications. It begins by looking at how decisions are currently made, which is often based on qualitative factors rather than data-driven insights. It then examines how predictive applications work by collecting and analyzing data to build models that can make decisions and be tested and optimized. The document argues that predictive applications can help reduce risk and costs while increasing revenue by enabling trends to be estimated, classifications to be made, and events to be predicted to optimize returns. It presents the idea of having a common platform for building, running, and monitoring predictive applications using both internal and external data.
Slides for "Intro to Systems Thinking" workshop. Session details and resources available here: http://pwoessner.wikispaces.com/Introduction+to+Systems+Thinking
Brighttalk outage insurance- what you need to know - finalAndrew White
This document provides an overview of Andrew White's experience in systems monitoring and event management. It discusses his 15 years of experience designing and managing deployment of monitoring software at IBM and other Fortune 100 companies. It also lists some of his previous roles and responsibilities at those organizations, including leading monitoring teams and developing custom solutions.
Systems thinking is a holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems. The document discusses systems thinking approaches like considering causal loops and flows within systems. It provides an example of how applying pesticides to reduce crop damage from one insect can have unintended consequences by disrupting the natural controls on other insect populations. The document advocates using systems modeling and a strategic outlook to better understand complex problems and their systemic causes.
Case Study on Professional Issues of Interactive Mediaguest2bf64e
The document presents a case study about Julian and Margaret McAdam who lost out on purchasing a new house because CreditWorthy, a credit rating company, mistakenly reported that Julian had defaulted on a previous mortgage due to a database error. While some argue the database should be updated to prevent future mistakes, others argue the costs outweigh the benefits given how few people are affected. The document discusses various ethical approaches to the situation such as utilitarianism, common good, and rights.
Cynefin and Complexity: A Gentle IntroductionJocko Selberg
NYC Lean Kanban Meetup - Presentation October 28, 2015 - Jocko Selberg
What do we really mean when we say that a problem is "complex"? Do we simply mean to say that a given problem is extremely complicated, or are complex problems something fundamentally different? We typically assume we are operating in a deterministic, ordered system where we can identify a cause and effect relationship, when in actuality we are often operating in a non-deterministic complex system, where these relationships can not be known in advance, if at all. How can we sense which context we are operating in and how might we act under varying degrees of uncertainty.
Complexity Theory is a term used to describe a field that is focused on the study of complex systems. Complexity science is not a single theory— it encompasses multiple theoretical frameworks, seeking answers to some of the fundamental questions about continuously changing, dynamic systems.
Cynefin is a framework developed by Dave Snowden and Cognitive Edge which seeks to helps us "make sense of the world, such that we can act in it". By understanding the fundamental differences between directed (ordered) systems and emergent (unordered) systems, we can modify our approach to match the context of the problem we are facing. The Cynefin framework takes a science based approach to dealing with critical business issues, drawing from anthropology, neuroscience and complex adaptive systems theory to improve decision making.
Complexity Theory and Cynefin have an undeserved reputation for being difficult to grasp. In this introductory talk we will break down these approaches so that we can effectively use them to help us to better act under conditions of uncertainty.
About Jocko Selberg
Jocko Selberg is currently a Project Manager for The Nielsen Company with over 15 years experience in the interactive industry. He is a non-sectarian agilist and does not own a TV.
ARTIFICIAL INTELLIGENCE, COGNITIVE TECHNOLOGIES AND DIGITAL LABOREmmanuel Gillain
bring a simple and concise summary of what the cognitive technologies enabling “Digital Labor” mean in order to raise the awareness level amongst the non technical people that care about the technology impacts on business, economy and society.
Brighttalk reason 114 for learning math - finalAndrew White
The document discusses using analytics to improve service assurance. It provides background on Andrew White, who has 15 years of experience designing systems monitoring and event management software. It then discusses how analytics can be used by CIOs to deliver better outcomes through techniques like big data analytics, security intelligence, mobile and cloud technologies.
This document discusses systems thinking and key concepts related to systems. It defines systems thinking as the cognitive process of studying and understanding systems of any kind by examining the linkages and interactions between interconnected components. A system is defined as a set of elements organized in a structure that produces characteristic behaviors. Key components of systems include elements, interconnections, and function. The document contrasts System 1 and System 2 thinking and provides examples. It emphasizes that systems thinking is needed to address problems created by more simplistic levels of thinking.
Big data is data that is too large to process with traditional software. As computers get smaller, cheaper, and more powerful, more computing resources can be applied to big data through cloud computing. Machine learning algorithms can analyze big data to build predictive applications that forecast outcomes and optimize decisions. However, enterprises have doubts and concerns about adopting predictive applications due to issues around data availability, predictability, understandability, and ensuring the results can be executed on.
Automated decision making with predictive applications – Big Data AmsterdamLars Trieloff
My slides from tonight's talk at Impact HUB in Amsterdam on big data, machine learning, cognitive biases and how to overcome them with predictive applications.
This seminar report provides an overview of systems thinking and key concepts. It defines systems thinking as viewing problems as parts of an overall system rather than in isolation. A system is a collection of parts integrated to accomplish an overall goal, with inputs, processes, outputs and outcomes, and feedback. Systems can be biological, mechanical, social, or other types and range from simple to complex. Systems theory studies principles that can be applied to all types of systems. Some basic principles of systems thinking discussed are that change is slow but lasting, cause and effect are not always closely linked, and easy answers often do not address complexity. The report also lists examples of systems principles like how a system's behavior depends on its structure and how systems seek
Smartcon 2015 – Automated Decisions in the Supply ChainLars Trieloff
This document discusses the process of automating decisions using predictive applications and machine learning models. It begins by outlining how predictive applications work by collecting and storing data, analyzing correlations, building decision models, and deciding and testing outcomes. The document then discusses challenges like predicting demand and order quantities. It provides an example of using sales forecasts and probability distributions to determine optimal order amounts while minimizing stock-out risks. Finally, it discusses how enterprises adopt predictive applications, addressing concerns around data availability, predictability, understandability, and executability, and outlines the potential financial impacts.
An overview of Systems Thinking, and how to apply the ideas of Complexity Theory to management of systems, with the results being called "Complexity Thinking".
This presentation is part of the Management 3.0 course created by Jurgen Appelo.
http://www.management30.com/course-introduction/
System Thinking - Affect on Decision MakingMuhammad Awais
The document discusses systems thinking and its impact on decision making. It begins with introductions to systems concepts and definitions of systems thinking. It describes the difference between system 1 and system 2 thinking, with system 1 being fast, automatic thinking and system 2 being slower, effortful thinking. It emphasizes that in today's complex and interconnected world, systems thinking is needed to understand complex problems and avoid unintended consequences of decisions. Systems thinking provides a holistic view rather than a narrow, reductionist view to help make better decisions. The document provides examples of applying systems thinking in various domains and argues it is a new way of thinking needed to address challenges of the current century.
General observations about managerial accounting informationSanTelmo Carrefour
This document discusses several key points about managerial accounting information:
1) Accounting numbers are intended for different purposes and require different approaches, so the same terms can mean different things depending on the context. This causes confusion if not properly understood.
2) Accounting numbers are approximations, especially estimates for future planning, so their accuracy varies. Users must understand the degree of approximation.
3) Management problems often involve incomplete data, so decisions must be made with the information available. Obtaining missing vital information is important, but action cannot always be delayed.
4) Accounting provides only a partial view, as important factors cannot always be quantified. Both solely numerical analysis and relying only on intuition are flawed
The Problem with dots: A critique of the Lessig and Murray modelsmrleiser
My presentation to the Information Technology Law students of the LSE on regulatory theory of the Internet. We touch on Lessig, Murray, rationality, pathetic dots, network communitarianism and big data.
On Analyzing Self-Driving Networks: A Systems Thinking Approach Junaid Qadir
This document provides an overview of systems thinking approaches for analyzing self-driving networks. It discusses the problems with conventional non-systems thinking, such as mental models and reductionism. It then defines key concepts in systems thinking like feedback loops, leverage points, and archetypes. The document applies these concepts to challenges in internet architecture like spam, privacy, and quality of service. It also discusses ethical and policy challenges for self-driving networks, like who will make ethical decisions. The document concludes that systems thinking is needed to understand complex interactions in self-driving networks and their effects on stakeholders.
This document discusses strengths-based assessment, design, and implementation approaches as alternatives to traditional approaches. It notes that traditional implementation attempts often fail between 80-90% of the time. Strengths-based approaches focus on identifying existing strengths and assets within a system rather than focusing only on needs or deficiencies. The document contrasts traditional deficit-based consulting models with potential strengths-based consulting models that engage stakeholders and leverage existing resources.
ACCOUNT WRITING Past Papers Inside. Online assignment writing service.Lorri Bynes
This document provides instructions for requesting and completing an assignment writing request on the HelpWriting.net website. It outlines a 5-step process: 1) Create an account with an email and password. 2) Complete a 10-minute order form providing instructions, sources, and deadline. 3) Review bids from writers and choose one based on qualifications. 4) Review the completed paper and authorize payment. 5) Request revisions until satisfied with the work. The document stresses that original, high-quality work is guaranteed or a full refund will be provided.
We love Superheroes. But Dan Heath’s Upstream is about putting Superheroes out of business. It is about the mindset and efforts required to prevent problems; it’s about systems thinking and moving upstream - making interventions there - to attain massive long-term good.
DOMAIN-DRIVEN DESIGN AND SOFT SYSTEMS METHODOLOGY AS A FRAMEWORK TO AVOID SOF...Panagiotis Papaioannou
A crisis is considered to be an issue concerning complex systems like societies, organizations or even families. It can be defined as the situation in which the system functions poorly, the causes of the dysfunction are not immediately identified and immediate decisions need to be made.
The type and duration of a crisis may require different kinds of decision making. In a long-term crisis, when system changes may be required, the active participation of the affected people may be more important than the power and dynamics of the leadership. Software crises, in their contemporary form as organizational malfunctions, can still affect the viability of any organization.
In this paper, we highlight the systemic aspects of a crisis, the complexity behind that and the role of systemic methodologies to explore its root causes and to design effective interventions. Our focus is on modelling as a means to simplify the complexity of the regarded phenomena and to build a knowledge consensus among stakeholders. Domain-Driven Design comes from software as an approach to deal with complex projects. It is based on models exploration in a creative collaboration between domain practitioners and solution providers. SSM is an established methodology for dealing with wicked situations. It incorporates the use of models and, along with Domain-Driven Design and other systemic methodologies can be employed to develop a common perception of the situation and a common language between interested parties in a crisis situation.
The beer game - a production distribution simulationTristan Wiggill
A presentation by Michael D. Ford CFPIM, CSCP, CQA, CRE, CQE, Principal, TQM Works Consulting, USA delivered during the 38th annual SAPICS event for supply chain professionals in Sun City, South Africa.
The Beer Game was developed by Jay Forrester at MIT’s Sloan business school in the early 1960s. It is a simple yet realistic simulator of the supply chain and is used as a teaching tool for systems dynamics. It has been played all over the world by thousands of people ranging from high school students to chief executive officers and government officials. Each participant plays a role in the production and distribution of a product, in this case “beer”.
Scenario-building enables managers to invent and then consider in depth several varied stories of equally plausible futures. They can then make strategic decisions that will be sound for all plausible futures. No matter what future takes place, one is more likely to be ready for and influential in it if one has thought seriously about scenarios. Scenario planning challenges mental models about the world and lifts the blinders that limit our creativity and resourcefulness.
Systems thinking examines how elements within a system influence each other and looks at relationships, patterns, and root causes rather than isolated problems. The iceberg model shows that most of an iceberg's mass is underwater and influences its above-water behavior, just as underlying factors greatly influence global issues. Stocks represent system conditions while flows are activities that change stock levels; intervening close to events has less leverage than addressing underlying factors. Mental models and assumptions must be challenged through tools like simulations to test theories and identify more effective solutions.
This document discusses a system for navigating design-by-committee projects. It provides a 6 step process: 1) Identify the committee's objective. 2) Identify the fundamental function. 3) Identify current challenges. 4) Brainstorm solutions. 5) Select optimal solutions. 6) Evaluate solutions through the design process. Best meeting practices are also outlined, including having an agenda, introductions, check-ins, and check-outs. The document is authored by experience designer GK Rowe, who works to infuse creative solutions and experience design into business.
Biases are nonconscious drivers — cognitive quirks — that influence how people see the world. They appear to be universal in most of humanity, perhaps hardwired into the brain as part of our genetic or cultural heritage, and they exert their influence outside conscious awareness.
On the whole, biases are helpful and adaptive. They enable people to make quick, efficient judgments and decisions with minimal cognitive effort. But they can also blind a person to new information, or inhibit someone from considering valuable options when making an important decision.
All of these biases, and others, lead many great companies and institutions to make disastrous and dysfunctional decisions.
There are two Discussion Boards and a Reflection Discussion for a .docxrandymartin91030
There are two Discussion Boards and a Reflection Discussion for a total of three things to complete, must be answered thoroughly. Must be APA format, answer thoroughly, must have at least 1-2 verifiable legitimate sources per discussion post and reflection discussion.250+ words needed per discussion and reflection post answering thoroughly. Due Thursday November 7, 2019. By8 AM EST. 36 hours. Plagiarism Free.
Discussion #1
Describe how you believe a "problem-solving culture" is established in a public safety organization.
Discussion #2
Read:
http://patimes.org/considerations-public-administrators-rainbow/
Blessett states "Whatever your reason is for being drawn to this profession, please consider that the work you do does not just affect you, but informs the interactions, impressions and expectations of public servants overall."
How do we reflect this goal in the day-to-day administration of a public safety organization?
#3
Program Outcome Two Reflection Discussion
Discussion Topic
The Program Outcome Reflections project requires you to reflect on each of the five Public Safety Administration Program Outcomes demonstrating a comprehension of the concept(s), and indicating how the PSAD curriculum provided you the knowledge and skills (process or application of knowledge) to master the outcome.
You will address each outcome individually in a 250-word reflection posted as a discussion topic. You should respond to the postings of at least two fellow students. Reflections on the individual program outcomes will include:
· Your understanding of the concept;
· How you feel the curriculum provided you with the knowledge and skills to meet the outcome;
· What courses and activities in the curriculum addressed the concepts of the outcome.
The outcome for this assignment is:
· Use informed decision making, goal orientation, teamwork, ethical behavior, enhanced technology, and communications to ensure effective leadership in public safety administration.
Class Material
"Problem Solving and Decision Making" http://www.studygs.net/problem/
· "Defining the Problem/Gathering Information" http://www.studygs.net/problem/problemsolvingv1.htm
· "Identifying and Structuring Problems" http://www.skillsyouneed.com/ips/problem-solving2.html
Module 2: Identify Issues or Challenges
Each public safety administrator needs to evaluate his or her environment to determine the major issues. Once identified, each issue must be analyzed, recommendations determined, and solutions implemented and reviewed. Your comprehensive case study capstone project will focus on each area.
Your first paper is an individual project where you will identify an issue or challenge. We have looked at issues facing public safety leaders. The most important point is to identify an issue or problem before it becomes an even bigger problem.
Many problems can be solved on an individual basis. For example, let's say the fire station doors are leaking. Possible solutions include patching the lea.
The document discusses different types of problems including 'tame', 'messy', and 'wicked' problems and how their complexity relates to approaches for risk management. It also examines the differences between management and leadership strategies for addressing uncertainty and ambiguity depending on the problem type. Effective risk management requires qualitative approaches for 'wicked' problems with high behavioral complexity and ambiguity.
1) The document discusses the importance of scenario planning given that our knowledge is about the past but decisions are about the future. It notes that most of what we need to know to make good decisions is outside our comprehension.
2) It then discusses how change, uncertainty, chaos and complexity are the new normal due to our ignorance. It also maps out the types of ignorance organizations face including uncertainty, complexity, ambiguity and equivocality.
3) The document concludes by explaining that scenario planning allows companies to embrace uncertainty by exploring alternative futures and navigate complexity by using stories to help organize information. It is an important tool to help address the gaps in understanding the future.
Slides from a Complexity, Change and Wellbeing workshop I ran at Northumbria University to demystify complexity, provide some tools for working with complexity and provide participants with an interactive experience of working with a challenging issue.
The application of the ‘New Sciences’ to Risk and Project ManagementDr David Hancock
This document provides an overview of an article from the May 2010 issue of PM World Today titled "The application of the ‘New Sciences’ to Risk and Project Management" by Dr. David Hancock. The article discusses how project risk management has traditionally relied on numerical and statistical approaches but could benefit from incorporating insights from chaos theory and considering projects as complex systems. It argues that most projects should be viewed as "deterministic chaotic systems" rather than predictable problems. The article also examines different types of problems like "tame," "messes," and "wicked" problems and how their complexities impact risk management. It concludes that risk professionals need new approaches like "risk leadership" to address uncertainties and complexities rather than relying solely on quantitative
The Social Side of Behavioural EconomicsDavid Perrott
Understanding how deeply hardwired our brains are to be social gives us a better understand of how we make judgments and decisions, creating the right foundation for new forms of communication and design.
The document provides an overview of issue management and outlines the key steps in the issue management process. It discusses identifying issues, analyzing them, developing response plans with goals and strategies, executing the plans, and evaluating the results. The document also covers types of issues, who creates issues, the typical lifecycle of issues, and dimensions to consider when analyzing issues.
http://home.ubalt.edu/ntsbarsh/business-stat/opre/partIX.htm
Tools for Decision Analysis: Analysis of Risky Decisions
If you will begin with certainties, you shall end in doubts, but if you will content to begin with doubts, you shall end in almost certainties. -- Francis Bacon
Making decisions is certainly the most important task of a manager and it is often a very difficult one. This site offers a decision making procedure for solving complex problems step by step.It presents the decision-analysis process for both public and private decision-making, using different decision criteria, different types of information, and information of varying quality. It describes the elements in the analysis of decision alternatives and choices, as well as the goals and objectives that guide decision-making. The key issues related to a decision-maker's preferences regarding alternatives, criteria for choice, and choice modes, together with the risk assessment tools are also presented.
Professor Hossein Arsham
MENU
1. Introduction & Summary
2. Probabilistic Modeling: From Data to a Decisive Knowledge
3. Decision Analysis: Making Justifiable, Defensible Decisions
4. Elements of Decision Analysis Models
5. Decision Making Under Pure Uncertainty: Materials are presented in the context of Financial Portfolio Selections.
6. Limitations of Decision Making under Pure Uncertainty
7. Coping with Uncertainties
8. Decision Making Under Risk: Presentation is in the context of Financial Portfolio Selections under risk.
9. Making a Better Decision by Buying Reliable Information: Applications are drawn from Marketing a New Product.
10. Decision Tree and Influence Diagram
11. Why Managers Seek the Advice From Consulting Firms
12. Revising Your Expectation and its Risk
13. Determination of the Decision-Maker's Utility
14. Utility Function Representations with Applications
15. A Classification of Decision Maker's Relative Attitudes Toward Risk and Its Impact
16. The Discovery and Management of Losses
17. Risk: The Four Letters Word
18. Decision's Factors-Prioritization & Stability Analysis
19. Optimal Decision Making Process
20. JavaScript E-labs Learning Objects
21. A Critical Panoramic View of Classical Decision Analysis
22. Exercise Your Knowledge to Enhance What You Have Learned (PDF)
23. Appendex: A Collection of Keywords and Phrases
Companion Sites:
· Business Statistics
· Success Science
· Leadership Decision Making
· Linear Programming (LP) and Goal-Seeking Strategy
· Linear Optimization Software to Download
· Artificial-variable Free LP
Solution
Algorithms
· Integer Optimization and the Network Models
· Tools for LP Modeling Validation
· The Classical Simplex Method
· Zero-Sum Games with Applications
· Computer-assisted Learning Concepts and Techniques
· Linear Algebra and LP Connections
· From Linear to Nonlinear Optimization with Business Applications
· Construction of the Sensitivity Region for LP Models
· Zero Sagas in Four Dimensions
· Systems Simulation
· B.
Summary Perception and Individual Decision MakingDeni Triyanto
This document discusses perception and individual decision making. It defines perception as how individuals interpret their sensory impressions to understand their environment. Perception is influenced by factors in the perceiver, target, and situation. Attribution theory is explained as how we judge behaviors as internally or externally caused based on distinctiveness, consensus, and consistency. There is a link between perception and decision making, as perception affects how information is interpreted and evaluated in the decision process. Common biases that influence decision making are also outlined, along with individual differences and organizational constraints.
Similar to IPICD 2019 (the value of a systems perspective) (20)
Food safety, prepare for the unexpected - So what can be done in order to be ready to address food safety, food Consumers, food producers and manufacturers, food transporters, food businesses, food retailers can ...
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
RFP for Reno's Community Assistance CenterThis Is Reno
Property appraisals completed in May for downtown Reno’s Community Assistance and Triage Centers (CAC) reveal that repairing the buildings to bring them back into service would cost an estimated $10.1 million—nearly four times the amount previously reported by city staff.
Combined Illegal, Unregulated and Unreported (IUU) Vessel List.Christina Parmionova
The best available, up-to-date information on all fishing and related vessels that appear on the illegal, unregulated, and unreported (IUU) fishing vessel lists published by Regional Fisheries Management Organisations (RFMOs) and related organisations. The aim of the site is to improve the effectiveness of the original IUU lists as a tool for a wide variety of stakeholders to better understand and combat illegal fishing and broader fisheries crime.
To date, the following regional organisations maintain or share lists of vessels that have been found to carry out or support IUU fishing within their own or adjacent convention areas and/or species of competence:
Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR)
Commission for the Conservation of Southern Bluefin Tuna (CCSBT)
General Fisheries Commission for the Mediterranean (GFCM)
Inter-American Tropical Tuna Commission (IATTC)
International Commission for the Conservation of Atlantic Tunas (ICCAT)
Indian Ocean Tuna Commission (IOTC)
Northwest Atlantic Fisheries Organisation (NAFO)
North East Atlantic Fisheries Commission (NEAFC)
North Pacific Fisheries Commission (NPFC)
South East Atlantic Fisheries Organisation (SEAFO)
South Pacific Regional Fisheries Management Organisation (SPRFMO)
Southern Indian Ocean Fisheries Agreement (SIOFA)
Western and Central Pacific Fisheries Commission (WCPFC)
The Combined IUU Fishing Vessel List merges all these sources into one list that provides a single reference point to identify whether a vessel is currently IUU listed. Vessels that have been IUU listed in the past and subsequently delisted (for example because of a change in ownership, or because the vessel is no longer in service) are also retained on the site, so that the site contains a full historic record of IUU listed fishing vessels.
Unlike the IUU lists published on individual RFMO websites, which may update vessel details infrequently or not at all, the Combined IUU Fishing Vessel List is kept up to date with the best available information regarding changes to vessel identity, flag state, ownership, location, and operations.
United Nations World Oceans Day 2024; June 8th " Awaken new dephts".Christina Parmionova
The program will expand our perspectives and appreciation for our blue planet, build new foundations for our relationship to the ocean, and ignite a wave of action toward necessary change.
34. Address:
915 SW Rimrock Way;
Ste 201-403
Redmond, OR 97756
Contact Number:
(+01) 503.707.5107
Email Address:
johnblack@aragonnational.com
ThankYou
39
“In the emerging paradigm…something new is
happening…
in place of individual efforts, the problem-solving process
is now clearly social; in place of basing decisions on
(just) facts, we base them on stories that give us a more
coherent sense of meaning.
In place of finding the ‘right answer’, we seek to gain a
shared understanding of possible solutions (Christensen,
2009).”
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University, Minneapolis, MN. Available from ProQuest Dissertation & Theses
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Washington County Sheriff's Office. Oregon, USA.
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Psychology, 62(1), 451-482. doi: 10.1146/annurev-psych-120709-145346
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Editor's Notes
Intro;
Thank you, I know what is like and for those in the field, you have my thanks, appreciation and ongoing support.
I can appreciate it because I spent 23 yrs. in LE and also 30 years in the military (unconventional warfare/special operations), often living in both worlds at the same time. Went up the ranks in both arenas, became an expert witness…and kept seeing the same thing…
What I saw was a world of its interconnections and the ripple effects of actions/consequences…
That understanding a situation is often more important then how we act on it…
And that we often underestimate the effects and influence of the connections and intertwined effects in a problem we are dealing with, the ripples..
So, I went back to school and got my doctorate, focusing on research in how insight (understanding) shifts to decision making, and how we might become better at this thing called insightdecision. What I found was that a systems approach is needed for many of the problems you are dealing with…
Some housekeeping,
this will go quick-I am available to discuss any/all
Some slides will be slightly different—this was to allow for a better presentation. 95% are the same, the concept and ideas are still there.
3MIN
Our current and past thinking is primarily from a linear perspective and dealt with what was, referred to as tame problems. Yet, today we are more interconnected than ever and we live in an ecosystem of systems within systems. Because of this our thinking must change and evolve.
I served 30 years in the military, all of which was with in the special operations community, and was continuously involved in different cultures, the interrelationships of decisions as well as how one moves from tactical to strategic thought. I was a senior instructor the military as well as taught leadership in these areas. Additionally, and law enforcement are started in patrol, and evolve my way through training, operations, made in executive management, corrections, as well as currently am a recognized expert witness in both federal and state courts on police practices, officer involved shootings, and training.
Yet throughout all of these experiences, I’ve come to recognize that the way humans make decisions, is that we are more like than we are different and we must evolve our thought processes and framing in order to adapt future changes.
Take a moment to think about the effect of an incident in a limited geographical area now as compared to 20 years ago… Everything affects and is connected to everything else. We are a world of complexity, connections and are better represented visually by the idea of a web that we are of the old hierarchal or linear view of the world. As shown by Lima, we are now a web of belief and knowledge as compared to hierarchal tree of knowledge and constantly forming new connections and finding the similarity in patterns versus the older model of step down in linear connections.
The human systems, the sociological aspects, now present us with problems that are managed but not solved. We prescribed treatments, similar to medicine, to the problem and observe the effects and then modify the treatment/solution… if this is the evolution should not the idea of understanding become the primary focus and similar to medicine the idea of first do no harm versus a constant focus on the one solution.
For those martial artists in the audience, a similar analogy would be the choice between trying to achieve the best possible position knowing ultimately that it will result in an advantage and a potential win on the mat as compared to simply looking for the finishing move… often a strategy that results in a loss.
If all things are interconnected, and if you push on one and it ripples out throughout the system, the search for a single thing to fix to cure the ills of the system will most likely fail. Yet, it is not uncommon for management to seek the single reductionist item to solve in the illusion of fixing the problems within the system. Policing is never ending, under resourced, time pressured, and rewards the immediate and tactical thinker while often punishing the strategic thinker/critical thinker. Yet system problems require understanding first (which means slowing down, taking additional time, and critically and brutally examining ones own leanings) prior to the decision whenever possible.
Ultimately, a systems approach is a question of focus…. If the getting to the solution (the ends) is first as the goal (Solution-centric, hierarchal, linear, end state, explore only to the minimum needed), then only the min understanding necessary. Creates..
Defensiveness vs shared ownership *caution collaboration is not consensus
This can causes another set of problems because the understanding aspect or exploration aspect is then over/door shut and instead the focus rapidly shifts into solutions. This mindset can cause defensiveness.
Exploration & Learning VS Elimination/Solve/Move on
Additionally, once decision-makers think they have understood the problem they often shift into the problem-solving, too soon and it limits the possibilities for understanding and solutions.
STAY and SWIM in the problem understanding space a little longer…
Ultimately, the goal is to give you an alternative perspective… A different way of looking at things, and the permission to not be immediate in your solution. Research has shown (Doerner) that when a human imposes their solution on a complex system they have it best of 50/50 chance of making it better. Our goal should be to build the mindset and team that is ready to solve the next problem knowing that today solution will always evolve into the next problem. This is not a 1/0 ultimatum…
The construction of a model is a long and costly process. It can’t be justified if there are other more simple ways of obtaining the same results. There are essentially two other ways - statistics and intuition. –
Intuition has got you where you are today, so don’t underestimate it. For many problems, intuition provides the right answers, drawing on our experience and knowledge. Intuition is cheap and fast. Keep using it as often as possible.
Martín García PhD, Juan. System Dynamics Fast Guide: A basic tutorial with examples for modeling, analysis and simulate the complexity of business and environmental systems. (System Thinking Book 2019) (Page 17). INNOVA BOOKS. Kindle Edition.
Think of a swimming pool, pipes and valves, inflows out flows, what is effecting the rate of flow (external) what can we do about it (adjust valves, pipe sizes, build a new pipe, circumvent the pipes, how do we know (feedback loops, gauges, etc.) are feedback lops accurate, do they measure reality, is there an unseen loop or one we don’t want to see/admit…
EBO handbook, 2006 (Give a real example from COP world next
A systems thinking or approach is now accepted practice in such fields as management/decision-making, medicine, and engineering. It is also found in the after action reviews or “murder boards” in the same industries.
It is interconnected, therefore it often cannot be reduced to a single cause but instead a series of interrelated causes and effects that constantly interact with each other. Interconnected systems, especially social systems such as criminal justice, mental health, or things that involve people naturally have weird, and unanticipated things occur within them… This is the idea of emergence and part of complexity theory.
As a solution is applied against the system, the system adapts… Think of the human body and modifying medications over time, or how criminal tactics react to police intervention… In short the system is always dynamic and the problem is always changing therefore one must always monitor their last perspective the problem as well as ask the question what is my current perspective of the situation of today's problem.
EBO handbook, 2006 (Give a real example from COP world next
A systems thinking or approach is now accepted practice in such fields as management/decision-making, medicine, and engineering. It is also found in the after action reviews or “murder boards” in the same industries.
It is interconnected, therefore it often cannot be reduced to a single cause but instead a series of interrelated causes and effects that constantly interact with each other. Interconnected systems, especially social systems such as criminal justice, mental health, or things that involve people naturally have weird, and unanticipated things occur within them… This is the idea of emergence and part of complexity theory.
As a solution is applied against the system, the system adapts… Think of the human body and modifying medications over time, or how criminal tactics react to police intervention… In short the system is always dynamic and the problem is always changing therefore one must always monitor their last perspective the problem as well as ask the question what is my current perspective of the situation of today's problem.
1 There is no definitive formulation of a wicked problem. It’s not possible to write a well-defined statement of the problem, as can be done with an ordinary problem.
2 Wicked problems have no stopping rule. You can tell when cornucopia you’ve reached a solution with an ordinary problem. With a wicked problem, the search for solutions never stops.
3 Solutions to wicked problems are not true or false, but good or bad. Ordinary problems have solutions that can be objectively evaluated as right or wrong. Choosing a solution to a wicked problem is largely a matter of judgment.
4 There is no immediate and no ultimate test of a solution to a wicked problem. It’s possible to determine right away if a solution to an ordinary problem is working. But solutions to wicked problems generate unexpected consequences over time, making it difficult to measure their effectiveness.
5 Every solution to a wicked problem is a “one-shot” operation; because there is no opportunity to learn by trial and error, every attempt counts significantly. Solutions to ordinary problems can be easily tried and abandoned. With wicked problems, every implemented solution has consequences that cannot be undone.
6 Wicked problems do not have an exhaustively describable set of potential solutions, nor is there a well-described set of permissible operations that may be incorporated into the plan. Ordinary problems come with a limited set of potential solutions, by contrast.
7 Every wicked problem is essentially unique. An ordinary problem belongs to a class of similar problems that are all solved in the same way. A wicked problem is substantially without precedent; experience does not help you address it.
8 Every wicked problem can be considered to be a symptom of another problem. While an ordinary problem is self-contained, a wicked problem is entwined with other problems. However, those problems don’t have one root cause.
9 The existence of a discrepancy representing a wicked problem can be explained in numerous ways. A wicked problem involves many stakeholders, who all will have different ideas about what the problem really is and what its causes are.
10 The planner has no right to be wrong. Problem solvers dealing with a wicked issue are held liable for the consequences of any actions they take, because those actions will have such a large impact and are hard to justify.
Heuristics/Biases are often made/created from:
Experience ≠ reality (and often has the bias of hindsight or anchoring)
May be created from another story (culture of the workplace, urban legend, poor training, etc. and also not a true picture of reality
Locked in time ≠ and yet things may have changed ( subject to the concept of fossilization)
Biases can be managed by awareness, elimination of bias is unrealistic and not necessarily desirable…
Heuristics/Biases are often made/created from:
Experience ≠ reality (and often has the bias of hindsight or anchoring)
May be created from another story (culture of the workplace, urban legend, poor training, etc. and also not a true picture of reality
Locked in time ≠ and yet things may have changed ( subject to the concept of fossilization)
Example is the concept of control…can we control/influence without the need for domination? Do we need to evolve what we mean by control?
Heuristics/Biases are often made/created from:
Experience ≠ reality (and often has the bias of hindsight or anchoring)
May be created from another story (culture of the workplace, urban legend, poor training, etc. and also not a true picture of reality
Locked in time ≠ and yet things may have changed ( subject to the concept of fossilization)
Social = BHL will be present
Action bias: when faced with ambiguity (creative fuzzy-front-end) favoring doing something or anything without any prior analysis even if it is counterproductive: “I have to do something, even if I don’t know what to do”. Team members can feel that they need to take action regardless of whether it is a good idea or not. This can be an issue when under time pressure in strict design sprint workshops for example.
Actor Observer Bias The way we perceive others and how we attribute their actions hinges on a variety of variables, but it can be heavily influenced by whether we are the actor or the observer in a situation. When it comes to our own actions, we are often far too likely to attribute things to external influences. You might complain that you botched an important meeting because you had jet lag or that you failed an exam because the teacher posed too many trick questions. When it comes to explaining other people’s actions, however, we are far more likely to attribute their behaviors to internal causes.
Ambiguity bias: favoring options where the outcome is more knowable over those which it is not. This bias has dire impacts innovation outcomes because the process is fundamentally risky and unknown process.
Anchoring Bias We also tend to be overly influenced by the first piece of information that we hear, a phenomenon referred to as the anchoring bias or anchoring effect.
Authority bias: favoring authority figure opinions ideas within innovation teams. This means that innovative ideas coming from senior team members trump or better all others, even if other concepts, ideas, and inputs could be more creative and relevant to problem-solving.
Availability Heuristic After seeing several news reports of car thefts in your neighborhood, you might start to believe that such crimes are more common than they are. This tendency to estimate the probability of something happening based on how many examples readily come to mind is known as the availability heuristic.
Baader-Meinhof Phenomenon is the phenomenon where something you recently learned suddenly appears 'everywhere'. Also called Frequency Bias (or Illusion), the Baader-Meinhof Phenomenon is the seeming appearance of a newly-learned (or paid attention to) concept in unexpected places. Confirmation Bias The confirmation bias is based on finding that people tend to listen more often to information that confirms the beliefs they already have. Through this bias, people tend to favor information that confirms their previously held beliefs.
Conformity bias: choices of mass populations influence how we think, even if against independent personal judgments. This can result in poor decision making and lead to groupthink which is particularly detrimental to creativity as outside opinions can become suppressed leading to self-censorship and loss of independent thought.
The Dunning-Kruger Effect: This is when people believe that they are smarter and more capable than they really are when they can't recognize their own incompetence.
False-Consensus Effect People also have a surprising tendency to overestimate how much other people agree with their own beliefs, behaviors, attitudes, and values, an inclination known as the false consensus effect. This can lead people not only to incorrectly think that everyone else agrees with them—it can sometimes lead them to overvalue their own opinions.
Framing bias: being influenced by the way in which information is presented rather than the information itself. People will avoid risk if presented well and seek risk if presented poorly meaning that decision making logic can easily be skewed.
Halo Effect Researchers have found that students tend to rate good-looking teachers as smarter, kinder, and funnier than less attractive instructors. This tendency for our initial impression of a person to influence what we think of them overall is known as the halo effect.
Hindsight Bias The hindsight bias is a common cognitive bias that involved the tendency of people to see events, even random ones, as more predictable than they are.
Loss-aversion bias: once a decision has been made, sticking to it rather than taking risks due to the fear of losing what you gained in starting something and wishing to see it finished. We also attach more value to something once we have made an emotional investment in it. A consequence of effort, time and energy put into creative thinking, team members can become biased and become emotionally attached to their outcomes. To remedy this, the 11th commandment: “thou shalt not fall in love with thy solutions”.
Misinformation Effect Our memories of particular events also tend to be heavily influenced by things that happened after the actual event itself, a phenomenon known as the misinformation effect. A person who witnesses a car accident or crime might believe that their recollection is crystal clear, but researchers have found that memory is surprisingly susceptible to even very subtle influences.
Optimism Bias Another cognitive bias that has its roots in the availability heuristic is known as the optimism bias. Essentially, we tend to be too optimistic for our own good. We overestimate the likelihood that good things will happen to us while underestimating the probability that negative events will impact our lives.
Self-Serving Bias Another tricky cognitive bias that distorts your thinking is known as the self-serving bias. Basically, people tend to give themselves credit for successes but lay the blame for failures on outside causes.
Loss-aversion bias: once a decision has been made, sticking to it rather than taking risks due to the fear of losing what you gained in starting something and wishing to see it finished. We also attach more value to something once we have made an emotional investment in it. A consequence of effort, time and anybody that moved energy, put into creative thinking, team members can become biased and become emotionally attached to their outcomes. To remedy this, the 11th commandment: “thou shalt not fall in love with thy solutions”.
Approach 1 = looking inwards; awareness
Approach 2 = Expand the context; change the frame = expand ones awareness
Bullet two…from the Bias class on Monday…
Procedure/Process
(+) A linear process is a proven way to move from point A to point B and get things done… In short it offers a blueprint.
(-) Linear processes tend to close one aspect and then move to the next; not designed to evolve an understanding but instead focus on getting to the end of the process.
(+/-) Adherence to a process can help to ensure objectivity and completeness. Conversely, adherence to a process may inaccurately address the inherent uniqueness of each situation.
People
Management has a blueprint to accomplish a task which helps to ensure the task is completed to a standard. Conversely, management can easily become more focused on adherence to the blueprint and deadlines then understanding and creating insight.
Line officers may simply become part of the process, implying that the process is more important than the people involved or the actual event attempting to be understood and investigated.
The media has a blueprint which is often beneficial when it comes to “feeding the beast”. Conversely, the media may attempt to shoehorn in each and every event, even if the blueprint does not fit.
The public and the community have a standard/procedure that may evolve into an expectation.
Yet, loss of confidence, especially from the public, is often facilitated by a lack of understanding.
Suggested, is that taking additional time in gaining insight and then communicating it, as compared to executing the linear blueprint, might result in greater empathy from both sides.
Relate all the above statements to an officer involved shooting, police culture, and the investigation of the officer involved shooting.
Link and go to Vensim
Often the worst thing you can do with a difficult question is to try to answer it too quickly. When the mind is coming up with What If possibilities, these fresh, new ideas can take time to percolate and form. They often result from connecting existing ideas in unusual and interesting ways. Einstein was an early believer in this form of “combinatorial thinking”; today it is widely accepted as one of the primary sources of creativity. Since this type of thinking involves both connections and questions,
Go to ScB aid
Add Joubert, don’t take away the idea that …
debating a question being better than not in many instances – but not all. There are many questions that come up in everyday management that are not mission critical and the consequences of a wrong decision are not serious. In those cases, a quick decision is useful and appropriate so that the mission can be carried out. Everyone has limited time and resources, and it is important to recognize that not everything is a wicked problem deserving of this level of analysis. Sometimes you just have to make a snap decision about whether to have the chicken or shredded beef – in either case lunch is unlikely to be a catastrophe.