How Principles of Competition and Strategy Can Improve Pinellas Schools

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“You can call any plan or program a strategy, and that’s how most people use the word. But a good strategy, one that will result in superior economic performance, is something else. More simply put, you have found a way to perform better by being different.”–Joan Magretta

 

How Silicon Valley Can Help Pinellas Schools introduced Pinellas County School’s (PSC) fundamental inability to negotiate the accelerating social changes driven by technology.

One of the reasons – for PSC and for Florida and the US as well – is a misunderstanding of the concepts ‘competition’ and ‘strategy.’

The misunderstanding is readily apparent by evaluating Superintendent Michael Grego’s initiative to advance the district’s vision of “100% Student Success,” and PSC’s new Strategic Plan.

‘Competition’ according to Michael Porter is a race to be unique, not a race to be “the best.”  As Joan Margretta explaines in Understanding Michael Porter,  (A summary can be found here.) only by competing to be unique can an organization achieve sustained performance.

  • Competition is always a struggle for the biggest share of the value an industry creates. It’s not about who is biggest, but who is most profitable.
  • Competitive advantage is not about what you’re good at. Rather, competitive advantage is derived from having a better value chain and a superior P&L (profit and loss) than others.
  • Focusing on being unique is a healthy way to think about competition because it means competition is going to be multidimensional and more complex than doing just one thing well.
  • The best way to achieve and maintain a competitive advantage is to work towards being different from your rivals. Build your value chain around a unique configuration of activities and then work toward capturing the maximum amount of created value that you can.

‘Strategy’ in practical terms is the antidote to competition. Great strategies are defined by their ability to pass five tests:

  1. Do you offer customers unique value?
  2. Do you perform activities differently?
  3. Have you made smart tradeoffs?
  4. Is what you do a good fit with your organization?
  5. Is there continuity and consistency in what you do?

The 10 practical implications which come from revisiting Michael Porter’s works are:

1. Vying to be the best in your industry is an intuitive approach to competition but it always ends up being self-destructive over the long haul.

2. Size or growth in and of themselves are meaningless because they are profitless. The whole aim of competing is to be profitable, not to maximize your market share.

3. Gaining competitive advantage is not really about beating your rivals. Rather, it’s about how you create and deliver unique value to your customers. If you have a competitive advantage, it will show up in your P&L.

4. A distinctive value proposition is essential for strategy, but strategy is more than just marketing. If your value proposition doesn’t require a specialized value chain to deliver it, it will have no real strategic relevance.

5. It isn’t necessary or even feasible that you “delight” every potential customer that exists. In practice the sign of a good strategy is that you deliberately make some customers unhappy.

6. No strategy means much until you make clear what your organization will not do. Making these trade-offs is the linchpin that makes competitive advantage feasible and also sustainable.

7. Never underestimate nor overestimate the importance of good execution. Executing well is unlikely to be the source of a sustainable advantage but without it, even the most brilliant strategy imaginable will fail to produce superior performance.

8. Good strategies always depend on many choices rather than just one, and on the connections among them. A core competence in and of itself will rarely generate a sustainable competitive advantage.

9. While flexibility in the face of uncertainty sounds good, the reality is an organization which stands for nothing will never excel at anything. Too much change can be just as dangerous for strategy as too little.

10. Committing to a strategy does not require that you make heroic predictions about the future. Instead, making a commitment improves your ability to innovate and ultimately your capacity to adapt to turbulence.

 


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How Silicon Valley Can Help Pinellas Schools

silicon-valley-asia

 

The contest for Pinellas County School Board Member in District 6, incumbent Linda Lerner, 71, against challenger Maureen Ahern, 54, focuses on their differing viewpoints on various education related issues.  (The issues are highlighted in two articles, one in The Tampa Bay Times by Lisa Gartner and the other by Anastasia Dawson in The St. Petersburg Tribune.)  There are, however, more fundamental issues that deserve our, and the School Board’s, attention, where Silicon Valley can help.

Lerner is the longest-serving School Board member in Pinellas County history, first elected to the board in 1990. She is seeking her seventh term and a 28-year tenure.  She says most Pinellas schools are doing well and that the district is moving in the right direction. The successful reforms she has championed while on the board as well as her goals for the school system reflect my own education-related beliefs.

But I also sympathize with Lerner’s challenger, Maureen Ahern, a former newspaper journalist who believes that “Our children don’t have more time; they only get one childhood education.”  The school district has spent years battling a large achievement gap between black and white students, and she feels it’s time to “figure out what to do and just do it, not keep talking about it.”

Technology is driving social change at an ever  increasing pace.   Organizations of all types and functions, especially schools, must respond or become irrelevant.  To help appreciate the magnitude and speed of social change watch the PBS TV program “The American Experience: Silicon Valley”  (Transcript), then read Decoding the Contradictory Culture of Silicon Valley, by Jeanne G. Harris and Iris Junglas.

Keeping Silicone Valley’s culture in mind, review SPCs recently approved comprehensive strategic plan, the district’s vision of “100% Student Success,” and Pinellas Innovates.

PSC  is like the Red Queen in Alice’s Adventures in Wonderland.  It has to run as fast as it can just to keep up.   How can SPC evolve new thinking and practices in time to help this generation of students?  Several observations present themselves:

  1. While the district may be, in Lerner’s words, ‘moving in the right direction,’ that gives us neither an idea of what the goals are nor sense of what it will take to reach them, not to mention to answer the question  of whose goals are they anyway?   The district needs to articulate a coherent, meaningful vision of its goals in the eyes of students, a so-called “value proposition.”   Developing its value proposition is one of the first steps in the process of re-imagining PSC’s strategic plan using  Michael Porter’s concept of competitive advantage,   A summary can be found here.
  2. Superintendent Michael Grego’s initiative to advance the district’s vision of “100% Student Success,”   however admirable it may be, is misdirected.  Vying to be the best is an intuitive approach to competition but it always ends up being self-destructive over the long haul.  Competition is a race to be unique.   Trying to be “the best” is competition in the most destructive sense. Only by competing to be unique can an organization achieve sustained performance. 
  3. Silicon Valley’s successful companies, Intel, for example, feature ‘flat’ rather than hierarchical, top-down management structures.   Collaboration is expected.  The Pinellas School System (as well as state and national education departments),  is a top down, bureaucratic, hierarchical  organization that allows little or no input from citizens on policies that affect themselves and their children.  A remedy for this condition is to establish democratic schools where parents, teachers, superintendents and other stakeholders can participate in the decision making process.
  4. The school system continually imagines itself as a factory producing watches.   It employs rigorous micromanagement to make sure the watches ‘work’ as expected.   Educating children is not like assembling watches; it is neither simple like a thermostat nor complicated like an airplane. It is complex like the weather.  Our appreciation of how complex systems work is growing.  We are beginning to understand how to intervene to change complex systems in the way we desire.

 

We will examine other ways to address these observations in future posts.

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New St. Petersburg Business Incubators Not Enough

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When up and running in a year or so, St. Petersburg’s leaders expect two new business incubators,  one slated to be located just south of downtown near the USF-St. Petersburg campus, in walking distance of All Children’s and Bay Front Hospitals, and a smaller incubator already planned for downtown St. Pete by St. Petersburg College, to jump start the evolution of a national and international health and wellness technology cluster in the Tampa Bay area.

It will take more than two  new business incubators to transform St. Petersburg and the Tampa Bay area, however.

Clusters are geographic concentrations of companies, suppliers, related industries, and specialized institutions such as academic programs –think Silicon Valley (technology), or Hollywood (entertainment). Clusters are prominent features of all successful and growing economies, and a crucial driver of entrepreneurship, technology, competitiveness and new business growth.

Clusters and the higher productivity that fosters them result not from the inputs an area has per se, but from how well a location uses local assets and institutions to produce valuable goods and services.

Policy makers and executives through their choices create a business environment that affects how areas evolve economically.

In fact there are many examples of societies that were technologically superior but not able to advance economically: China in 1400, the Arab World at about the same time, or in the case of firms, General Motors in the 1970s.

According to Michael Porter, a globally recognized expert on business competition and competitiveness, entrepreneurship is just one of a variety of inputs that are necessary for developing higher productivity.

Also needed is a social/political/cultural/legal environment that fosters its application.  The environment consists of, for instance, good public education, health care, and physical infrastructure, clean water, fair competition laws, management and organization of people, transparency, research and development, as well as many others.

There are many motivations for starting a company, but one of the most common threads is that company founders believe they can do better than the status quo. A good part of that is probably curiosity and ego – but a bigger part of that is an honest, analytical look at what’s going on and not being satisfied with it.

Local leaders have made significant strides in bringing about St. Petersburg’s transformation.  Without realizing that the environment is all important in developing a city (or county, or state) St. Petersburg may change, but will likely emulate those societies that had the means but not the ability to advance.

To get an idea of the job ahead and the time frame view the American Experience episode   “Silicon Valley”.  (Transcript)

Fast forward fifty-some years and consider how our Public Education System has adapted; our Healthcare System; our Public Safety System; our Political System; and our Economic System.    The questions remain; where do we want to go as a city (or county, or state) and how do we get there?

Here are some references to start the dialogue:

Decoding the Contradictory Culture of Silicon Valley,By Jeanne G. Harris and Iris Junglas;

Silicon Valley Tech Innovation Ecosystem–Silicon Valley’s greatest innovation – how companies evolve from ideas to successful enterprises;

Inside Silicon Valley – Podcast

The Lean Start-Up – Eric Ries

Why Eric Ries Likes Management

California Dreaming

Insight Silicon Valley

Lessons From Silicon Valley

For Honda, Waigaya Is The Way

 

 

 

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Using Complexity to Design Intelligent Social Systems

 


‘Complexity’

“Complexity thinkers define ‘intelligence’ in terms of exploring a range of possible actions and selecting ones that are well-suited to the immediate outcome…” – Davis and Sumara

“There’s more than one way to skin a cat.” – American aphorism.

 

‘Intelligence’ is not necessarily about a rational or comprehensive consideration of immediate circumstances. Instead, in complexity terms, the intelligent unity is the one that generates a diversity of possibilities and that has a mechanism for critically debating the merits of those possibilities. So understood, intelligence is a sort of ‘scouting’ of possible responses.

This paper, then, is a ‘scouting report;’ a guide for evaluating possible choices for managers and policy-makers in choosing when, where and how to engage the complex social challenges that we face today, not only in the proposed South Side St. Petersburg CRA, but in greater St. Petersburg, Pinellas County and Florida as well. This report can be a useful resource in developing revitalization initiatives for growing people, businesses and institutions in a society capable of engaging the serious social challenges that we face today.

Introduction

It has become abundantly clear that the current ideas and initiatives that have been advanced as solutions for the social problems we are facing today in the South Side St. Petersburg CRA, (e.g. substandard living conditions, poor health and education systems, diminished or absent political voice; lack of physical security and environmental degradation), have been ineffective. Moreover, there is a growing understanding that the causes of the problematic social conditions do not reside within one physical area, one segment of society, one institution or even within one ideology. The origins of the social problems are complex and interventions must deal with interdependent causes and navigate nonlinear and often unpredictable change processes involving a diverse range of stakeholders.

Unfortunately, when tackling complex social problems, people’s tendency is always to employ convenient ways of intervening; to break problems into discrete, understandable, component effects and causes, while at the same time realizing it is necessary to find ways to motivate society as a whole – but not understanding how to make that happen.

In the light of the challenges complex problems pose, people could be forgiven for becoming cynical about chances of being able to tackle issues or achieve economic or social goals. Many policies fail to address the problems they are designed to combat. In particular, it might seem that “knowledge” is less useful to the policy process than was initially supposed, as the “rational” model of policy-making, which is centered around intentionally guiding institutions towards achieving common goals, begins to look like not just an unrealistic description of the policy process but also in fact an irrelevant ideal.

Fortunately, in recent years the complexity sciences have improved our understanding of complex problems, and have provided concepts and ideas which incorporate both old and new insights to present alternative theories for change, greater understandings of underlying processes and crucially, better approaches for tackling them in a strategic and direct manner.

The central contention of this paper is that the main problem is not intractable problems, or poor application of the right tools, but rather use of the wrong tool for the job. The complexity sciences are beginning to give us alternative theories for change, greater understandings of underlying processes and, crucially, better approaches for tackling them.

It is vital that actors charged with implementing policies and programs in the face of complexity take responsibility for choosing an appropriate approach.

 

Complex Problems and the Challenges They Pose

Why do complex problems present big challenges for traditional approaches to implementation?

  1. The capacities to tackle complex problems are often distributed among actors. Problems manifest themselves in different ways and at different levels, and rather than one organization or hierarchy being fully in control of meeting a particular objective, action may rely on differing degrees of collaboration from a variety of actors.
  2. Complex problems are difficult to predict. Many social, political and economic problems are not amenable to detailed forecasting. Where causality is not well understood success may rely on adaptation and flexibility to emerging insights, rather than trying to completely fix the shape of policy responses in advance.
  3. Complex problems often involve conflicting goals. There may be many divergent but equally plausible interpretations of a policy issue, with different groups approaching it from different starting points or assumptions. Implementation cannot be technocratic, but requires a negotiated understanding and synthesis through communicative processes.

Consequently, the ways in which policy draws on available knowledge becomes one of the central determinants of its success. The difference is that, rather than working in a linear fashion, policymakers must be mindful of constraints and opportunities as to where, when and how knowledge and decision-making can best be linked.

Where

Implementing agencies need to work in a collaborative mold, facilitating decentralized action and self-organization:

  • Decentralization and autonomy: One key priority is decentralizing policy-making and implementation, distributing power in decision-making and allowing increased autonomy for units lower down the hierarchy.
  • Engaging local institutions and anchoring interventions: Implementing agencies may need to work with and through local organizations addressing an issue at different scales; this may be best done through co-management and power sharing.
  • Convening and boundary management: Agencies may be able to play a unique role in facilitating processes that build trust and collaboration between key stakeholders. They must act as trustworthy stewards of these processes, including the provision of transparent mechanisms for conflict resolution.
  • Building adaptive capacity: Capacity building is likely to be central to efforts to enable actors to capitalize on any autonomy for addressing problems. Supporting adaptive capacity networks is shown to be a central priority for stimulating emergent responses.
  • Remove the barriers to self-organization: There may be different types of barriers and systemic issues which are preventing actors from adapting to emerging problems: these could be related to national legislation or political systems, or issues of power, discourse and social capital.
  • Supporting networked governance: Agencies must approach the delivery of their mandate with a networked approach to policy and governance. Accountability structures can usefully focus on holding units accountable for their mission or role description. Relationship management concern and participatory processes should be central focuses.
  • Leadership and facilitation: Even where the capacity to act is distributed, leadership emerges as a critical variable in the success of collaborative responses. However, in the face of complex problems this leadership must be facilitative and enabling, working through attraction rather than coercion.
  • Incremental intervention: Where a central agency does need to intervene, it should be approached in an incremental manner, starting from existing networks and taking an evolutionary approach to support, looking to ‘seed’ decentralized action and support emerging responses rather than implementing idealistic blueprints.

When

Implementing agencies need to deliver adaptive responses to problems, building space for interventions to be flexible to emerging lessons. This can be done in the following ways:

  • Appropriate planning: Systems around ex ante analysis should be light and flexible, and focus on providing utility, for example by enhancing awareness of the key risks or lessons. Accountability can be tied to clear principles for action rather than to unpredictable results or inflexible activity plans, and rules for the adjustment of plans can be established in advance.
  • Iterative impact-oriented monitoring: Continual monitoring of the effects an intervention is having will be critical to its success – and this should be done in order to check and revise understandings of how change can be achieved, rather than simply recording progress. It is therefore imperative to make any evaluation as utilization-focused as possible, to ensure the requisite feedback is received to allow for timely adaptation.
  • Stimulating autonomous learning: In the face of complex problems, evidence shows that actors are more likely to be responsive to emerging evidence where it emerges in the context of trust and ownership. Monitoring and evaluation functions must be embedded throughout implementation chains, and the autonomy to shape M&E frameworks should be devolved.
  • Implementation as an evolutionary learning process: Experimentation through intervention may need to become the central driver of learning. This could be put center-stage in an evolutionary implementation process, revolving around variation, where a number of different options are pursued, and also through selection, where based on feedback from the environment, some are deemed a greater success and replicated.
  • Creating short, cost-effective feedback loops: Judicious use of participatory M&E and transparency may be important because who carries out the monitoring has proven a crucial determinant of effective adaptation. There are a number of local-level methods for citizen involvement in the governance of implementation available, including emerging innovation in systems for beneficiary feedback, and transparency and accountability initiatives.
  • Accountability for learning: Measures may need to be taken to ensure policies place explicit value on learning as well as delivery: intervention must be seen as an expression of hypotheses and complex tasks may require learning objectives rather than performance goals. Promoting innovation in service delivery may require valuing redundancy and variety.

How

Implementation systems and processes must draw on an eclectic mix of sources of knowledge at many different levels and junctures. Of particular importance are tools, which allow for the negotiation between and synthesis of multiple perspectives, for example:

 

  • Decisions from deliberation: Carefully managed and structured processes of deliberation have proven to have wide benefits on both decisions made and their subsequent implementation. These must be embedded in inclusive, face-to-face fora, focusing on eliciting reasoned and legitimate inputs to action.
  • Focusing on how change happens: Implementation processes must tie together analytical and management efforts with explicit questions as to how change happens in their context. Ideas and assumptions underlying implementation must be made explicit in order to allow them to be purposefully tested; planning tools such as ‘theory of change’ and theory-based evaluation may assist.
  • Realistic foresight: Foresight and futures techniques can be used to provide broad and realistic forward-looking analysis and fix shared structures for ongoing implementation. Tools such as scenario planning have proven invaluable in enabling organizations to be both resilient and nimble, so long as a broad range of perspectives are taken into account.
  • Peer-to-peer learning: Rather than focusing on technocratic knowledge-transfer processes, adaptation and learning may often work more effectively through peer networks, such as through study tours or ‘peer review’. Research on communities of practice has shown how the informal dynamics of linkages can be the driver of creativity and reflection.
  • Broadening dialogues: Processes of contestation and argument may be important for informing and improving the foundations of policy and action, and implementation should look to build and work with critical voices, rather than avoiding them. Promoting reflexive research is important as is building the capacity of disadvantaged stakeholders to fully articulate their position.
  • Sense making for common ground: A shared vision of the problem at hand is often a prerequisite for progress on complex issues. Key stakeholders must jointly negotiate concepts and models, and boundary objects such as shared models or standards can play a key role in anchoring collective action.
  • Facilitation and mediation: Efforts to combine different sources of knowledge must tread carefully, and policy-makers must become adept in managing power in the knowledge-policy interface. Power should be shared in both analytical and decision-making processes, with space made for critical reflection and the consensual resolution of impasses and conflicts.

 

So where are the approaches most relevant? In some sectors, ‘complex’ models of implementation are well-established and proven effective; in other areas, persistent and well-recognized issues with implementation seem to bear the hallmarks of the negative side-effects of traditional tools applied to complex problems. This research has not attempted to specify what problems should be considered ‘complex’, but to give readers the tools to decide for themselves whether an issue faced is complex, and to provide guidance on what to do if it is. The extent to which any one challenge exhibits the characteristics of these three dimensions is likely to be a matter of degrees, and the relevance of the principles and priorities set out above will vary accordingly. Implementation will likely require a mixture of these principles with more traditional approaches and similarly the tools presented above have a domain of appropriate application, and need to be applied well and with sensitivity to context.

What is clear, however, is that complexity can no longer be swept under the carpet. While there is not yet one comprehensive framework, there is a growing collection of models, tools, and approaches to effectively develop interventions in the face of these multifaceted problems. These will allow those charged with implementing policies and programs to be able to more explicitly, systematically and rationally deal with the challenges that are presented. However, taking responsibility for complexity is a double-edged sword. On the one hand, there are a new set of tools to use, and/or more legitimacy given to approaches not previously seen as ‘scientific’ or ‘rigorous’. But on the other hand, this will make areas of practice previously hidden from sight more visible, and actors will find themselves held accountable for aspects of their work which may have previously slipped under the radar. This shift may therefore represent an uncomfortable or unattractive transition. However, what is clear is that it is an essential transition in order to achieve results in the face of complexity.

 

 

 

 

Appendix I

Key concepts of complexity theory

These first three concepts relate to the features of systems that can be described as complex:

1. Systems characterized by interconnected and interdependent elements and dimensions are a key starting point for understanding complexity science.

2. Feedback processes crucially shape how change happens within a complex system.

3. Emergence describes how the behavior of systems emerges – often unpredictably – from the interaction of the parts, such that the whole is different to the sum of the parts.

Complexity and change

The next four concepts relate to phenomena through which complexity manifests itself:

4. Within complex systems, relationships between dimensions are frequently nonlinear, i.e., when change happens, it is frequently disproportionate and unpredictable.

5. Sensitivity to initial conditions highlights how small differences in the initial state of a system can lead to massive differences later; butterfly effects and bifurcations are two ways in which complex systems can change drastically over time.

6. Phase space helps to build a picture of the dimensions of a system, and how they change over time. This enables understanding of how systems move and evolve over time.

7. Chaos and edge of chaos describe the order underlying the seemingly random behaviors exhibited by certain complex systems.

Complexity and agency

The final three concepts relate to the notion of adaptive agents, and how their behaviors are manifested in complex systems:

8. Adaptive agents react to the system and to each other, leading to a number of phenomena.

9. Self-organization characterizes a particular form of emergent property that can occur in systems of adaptive agents.

10. Co-evolution describes how, within a system of adaptive agents, co-evolution occurs, such that the overall system and the agents within it evolve together, or co-evolve, over time.

Source: Ramalingam and Jones (2008).

 

Complex systems have features that are also complicated and may act in patterned ways, but whose interactions are constantly changing. An air traffic control system is complex because its functioning depends on many variables that keep varying, such as weather, aircraft downtime, peak loading, etc.

With complicated systems, one can usually predict outcomes by knowing the design (or having a detailed engineering manual at hand). In contrast, depending on the interplay of the elements in the system, complex systems may produce highly divergent outcomes.

It is impossible to predict the way a complex system will respond with sufficient accuracy. One is limited to establishing the conditions characteristic of a complex system that lead to emergence, then working creatively at leverage points to change the configuration of the system until the desired ends are produced.

 

Appendix II

Technical vs Adaptive or ‘Wicked’ Social Problems

Examples of adaptive or ‘wicked’ problems include reforming public education, restoring wet land environments, and improving community health. In these cases, reaching an effective solution requires learning by the stakeholders involved in the problem, who must then change their own behavior in order to create a solution.

Technical vs Adaptive problems:

  • The problem is well defined vs complex;
  • The answer is known in advance vs the answer is not known;
  • One or a few organizations have the ability to implement the solutions vs no single entity has the resources or authority to bring about the necessary change.

Characteristics of wicked problems:

  • There is no definitive formulation of an wicked problem that provides the problem solver with all the information needed to formulate the problem, break it into manageable chunks and solve it;
  • Wicked problems have no stopping rule. You can’t say you have solved an adaptive problem;
  • Solutions to wicked problems are not true-or-false, but good-or-bad;
  • There is no immediate and no ultimate test of a solution to an wicked problem;
  • Every solution to an wicked problem is a ‘one-shot operation’ because there is no opportunity to learn by trial and error. The consequences of intervention cannot be undone. History matters and provides the context for the next intervention;
  • Wicked problems do not have an exhaustively describable set of potential solutions, nor is there a well-documented set of permissible operations that may be incorporated into the plan;
  • Every wicked problem is essentially unique; solutions are not transferable;
  • Every wicked problem can be considered to be a symptom of another problem;
  • The existence of a discrepancy representing an wicked problem can be explained in numerous ways; each stakeholder will have their own perspective on the nature of the problem and the solution;
  • No single entity has the resources or authority to bring about the necessary change.

 

 

 


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Facilitating Socio-Economic Development – Institutions

Related ecosystems (ECO)

“Jobs liked to tell the story- and he did so to his team that day- about how everything that he had done correctly had required a moment when he hit the rewind button. In each case he had to rework something that he discovered was not perfect. He talked about doing it on Toy Story, when the character of Woody had evolved into being a jerk, and on a couple of occasions with the original Macintosh. “If something isn’t right, you can’t just ignore it and say you’ll fix it later,” he said. “That’s what other companies do.”
Walter Isaacson, Steve Jobs

 

Developing St. Petersburg, the previous post, outlined the history of the Southside St. Petersburg CRA and posed the question about the effectiveness of the underlying economic development policies and practices employed, as well as the goals, theories and assumptions on which they are based.

One of the most important considerations is an appreciation of the roles of institutions in the development and maintenance of economic progress.   The Workshop Toolkit, including the Institutional Analysis and Development (IAD) Framework, developed by the Ostroms and others, enables development aid providers to elucidate how the less-than-satisfactory local social and economic outcomes arise from the perverse incentives that are the result of the way the social and economic institutions,  including the aid system itself, ‘The System,’ are organized.

In addition, employing the IAD framework suggests possible methods to further guide the design and implementation of urban redevelopment policies and projects by applying the knowledge gained from empiric research of the design and management of common-pool resources and community-based resource management.

The Institutional Analysis and Development (IAD) Framework lays the theoretical groundwork that can be used to design a successful redevelopment initiative. This post explains key terms of the IAD Framework and relates them to overall goals of sustainability and ownership, setting the stage to make recommendations on priorities, principles and tools for shaping policy and program implementation.

Five Key Terms of The IAD Framework

Institutions

Institutions are the rules used by individuals in a wide diversity of repeated situations that they confront in life; they help or hinder the efforts of individuals to be optimally productive in the activities they undertake with others. Institutions key aspect is their shared rules regarding what actions individuals must take, must not take, or are permitted to take in particular situations. By constraining behavior, institutions increase order and predictability.

E.g.: baseball; the interstate highway system; commercial airplane operation; Starbucks and innovation.

It is now widely accepted that the main development problem is “missing institutions” or “perverse institutions” instead of “missing money.” No matter how well-intentioned those providing assistance are, or how many resources are transferred, development will occur only if political and economic institutions generate incentives that facilitate individuals’ achievement of development goals.

Incentives

In the IAF, the term incentive means the rewards and punishments that individuals believe to be related to their actions and those of others. Perceived rewards and punishments can motivate individuals to take actions that are productive for all involved. Perverse incentives, on the other hand, lead individuals to avoid engaging in mutually productive outcomes or to take actions that are generally harmful for others.

Citizens often face incentives that make it difficult to invest in economic activities, to provide public goods, to manage common pool resources and generally to arrive at mutually beneficial day-to-day arrangements. Thus, a core problem of development assistance is to understand the structure of the incentives generated within these situations.

Where people themselves cannot change incentives, government policies potentially can. However, incentives at the policy level may obstruct institutional reforms needed to improve economic, social, and political conditions.

Development

Meaningful progress or development implies not only the progressive meeting of basic material requirements of all, but also the conditions and institutions consistent with respect for basic human rights.

According to Sida, development can be defined as those actions taken by donors and recipients intended to further two distinct outcomes:

  • Poverty reduction, and
  • Freedom.

There are six political priorities:

  1. Democracy;
  2. Human rights;
  3. Gender equality and
  4. Women’s role in development;
  5. Environmental sustainability;
  6. Climate change. (Sida Development Assistance – A Presentation)

Well-being

The process of development is one in which individuals increase their well-being by solving more collective-action problems more effectively through the design and use of institutions
at many scales.

A key message of the Commission on the Measurement of Economic Performance and Social Progress is that we should shift our emphasis from measuring economic production to measuring people’s well-being. Well-being is multi-dimensional. The key dimensions that should be taken into account simultaneously are:

  1. Material living standards (income, consumption and wealth);
  2. Health;
  3. Education;
  4. Personal activities including work;
  5. Political voice and governance;
  6. Social connections and relationships;
  7. Environment (present and future conditions);
  8. Security, of an economic as well as physical nature.

Information relevant to valuing quality of life includes measures of people’s “functionings” and freedoms. In effect, what really matters are the capabilities of people, that is, the extent of their opportunity set and of their freedom to choose among this set, the life they value. There is a consensus that quality of life depends on people’s health and education, their everyday activities (that include the right to a decent job and housing), their participation in the political process, the social and natural environment in which they live, and the factors shaping their personal and economic security.

Collective-action situations

Collective-action situations lie at the center of development. A collective-action situation a desired joint outcome requires the input of several individuals. Almost all productive relationships involve some form of collective action. For example, while one person can produce agricultural products from a single, small agricultural plot, the amount of agricultural product per amount of input is greatly enhanced by creating diverse forms of teamwork through family, community, or corporate arrangements to increase the size of the enterprise. Similar benefits of increasing the number of participants who bring different skills and resources occur in almost all manufacturing or service activities. Collective-action situations become collective-action problems whenever a lack of motivation and/or missing or asymmetric information generates incentives that prevents individuals from resolving a collective action situation. In other words, in order to achieve a benefit that helps the members of the group, some portion of these people must accept a risk of paying extra for a benefit shared by all. Simply creating a public bureaucracy to provide public goods or protect natural resources doesn’t automatically solve the collective-action problem.

Rather than think about linkages among action situations involved in development assistance as a “chain of aid delivery,” we believe it is more advantageous to think about a set of nested situations that may take on any of a variety of productive or unproductive relationships. The chain-like fashion of aid delivery does not fully reveal the varied institutional contexts within which the actors in their situations are connected.

Ownership

The concept of “development” as a goal has become “sustainable development.” Sustainable development focuses on the two concepts of sustainability AND ownership.

Sustainability refers to the longevity of development aid’s effects, rather than the existence of particular projects or activities.

Ownership requires greater participation and responsibility on the part of aid recipients and a decrease in a donor’s authority over their own aid packages.

To be effective and sustainable, an intervention should incorporate the local knowledge about the needs, preferences, and problems of target beneficiaries that only they themselves possess. Access to this localized knowledge requires active beneficiary ownership – meaning a role in all four aspects of ownership – rather than just the consumption of whatever is produced. By making investment in these processes, beneficiaries are not simply consumers of someone else’s largesse. They have had to articulate their own preferences and allocate their own resources.

Four dimensions of ownership have been identified:

  1. Enunciating demand: Participation in provision by articulating what asset, project, or program is needed and deciding how resources should be mobilized.
  2. Making a tangible contribution: Participation in production by making tangible contributions. Time, effort, and other resources contributed to production are a costly signal that beneficiaries expect to derive benefits from a project.
  3. Obtaining benefits: Participation in consumption of the benefits if the project is successful and in a share of responsibility if the project fails.
  4. Sharing responsibility for long-term continuation or non-continuation of a project: Participation in decisions related to the alienation of the rights to a project (the decision to continue or not continue a project once it has been initiated).

     

Institutional Analysis

Many institutions foster incentives that undermine their goal of sustainable development. Some options that may help development agencies ameliorate some of the perverse incentives are:

  1. Awareness of the role of incentives in underpinning aid effectiveness and sustainability.
    1. Most individuals with experience in development cooperation realize that incentives underpin aid effectiveness and sustainability.
    2. A more explicit and systematic understanding of institutions and the incentives that emerge within particular organizational structures, as well as mechanisms for transmitting that knowledge, are crucial to improve an aid agency’s effectiveness.
    3. The only way that an understanding of incentives will lead to better development assistance is through the determination of an agency’s own staff to create rules that promote “good” incentives.
  2. The Nature of the Good
    1. A development agency should understand the wider incentives involved in the underlying core good as well as the more narrowly focused incentives related to its activities.
    2. Such an understanding, coupled with a desire for sustainable results, would most likely exclude most projects that primarily involve infrastructure provision and move the agency toward institution building.
  3. Ownership and Sustainability
    1. Many agencies now voice a strong concern for the sustainability of development cooperation. A long-term positive change is a better investment of resources than more temporary results.
    2. Such agencies seek to improve the outcomes related to its efforts in development cooperation by giving ownership of aid to recipients. Including recipients and beneficiaries in true ownership can help solve some of the severe information and motivational problems in development.
    3. But this is not a sufficient condition to ensure sustainability. Motivational and information problems in aid are very deeply embedded and no type of development cooperation is free from powerful perverse incentives.
    4. Given aid’s complexity regarding relationships and incentives, it is important that an essential first step is that all participants involved in an aid project to understand what the terms ownership and sustainability mean in practice. Aid agencies need to allow sufficient opportunities for the owner(s) to contribute to the design, implementation and mid-course corrections of the project/program.
    5. A final step is to allow the owner full participation in the final evaluation of a project/program. Beneficiary owners need to (1) enunciate a demand for an aid, (2) allocate at least some of their own and other actor’s assets to the project or program so that they have a real stake in the way their own and other actor’s assets are used, (3) obtain real net benefits, and (4) have clear-cut responsibilities and be able to participate in decisions regarding continuance or ending of a project.
    6. We recommend that aid agencies focus on the concepts of responsibility and accountability as they relate to ownership. An agency should make clear what is intended to be sustainable, how development assistance helps produce sustainability, what time frame is being used, and how sustainability will be measured. Project planning documents should clearly identify the intended owners and include an analysis of the anticipated impact that this designation of ownership will have on sustainability.
  4. Encouraging Learning at the Individual and Organizational Levels
    1. Most development agency employees generally accountable for producing sustainable results.
    2. Evaluators should be instructed to examine the level of ownership in a project or program and the impact of ownership on sustainability should be seriously discussed.
  5. Putting Beneficiaries First
    1. Effective and sustainable development assistance must center on beneficiaries and the problems they face.
    2. Beneficiaries should take ownership of the developmental projects in all four senses of that term.
    3. To be sustainable, aid should address how beneficiaries relate to each other in dealing with diverse collective action situations.
    4. Without this deeper analysis and programs focused on institutional change to facilitate the long-term improvement in the lives of beneficiaries, aid is likely to provide only short-term benefits.

We are now in a position to begin making recommendations on priorities, principles and tools for shaping development policy and program implementation, the subject of the following post.

References

  1. Ostrom, E., 1990; Governing the Commons – The evolution of Institutions for Collective Action; Cambridge University Press.
  2. Ostrom, E. 2005; Understanding Institutional Diversity; Princeton University Press.
  3. Gibson, C., Andersson, K., et. al., 2005; The Samaritan’s Dilemma: The Political Economy of Development Aid; Oxford University Press.
  4. CSSP.org; Institutional Analysis:
    Organizing Systems to Support Improved Outcomes for Children and Families – Lessons Learned from the Institutional Analysis
  5. Child Welfare Practice – Creating a Successful Climate for Change; Findings and conclusions from an institutional analysis.
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Developing St. Petersburg

A View of the Redeveloped St. Petersburg Waterfront

St. Petersburg

Developing a Florida City’s Reputation

St. Petersburg was recently named as one of the top 52 places in the world to visit in 2014 by The New York Times: “…St. Petersburg is anything but stationary. With a redeveloped waterfront, a stunning Dali Museum, and sophisticated restaurants in place, the downtown energy is now heading up historic Central Avenue…”

This remarkable transformation from a sleepy home for retirees chatting on green benches to an international destination was sparked by the “Intown” Redevelopment Plan.

First adopted by the City Council in 1982, it is the most recent manifestation of the city’s policies that promote rapid development to accommodate an influx of people responding to a seemingly endlessly repeated message of “…the nation’s playground, a southern garden of perpetual well-being.” (Sitler, 2006) The city focused “…on economic development and organizing the city to provide the ideal conditions for consumer consumption and tourist recreation” since the area’s first railroad terminus was located in the city at the junction of 1st Ave South and 9th St. in 1888. (Salmond 2004)

“Intown’s” success contrasts sharply with the stubborn economic depression experienced by the residents living on the south side of St. Petersburg who have effectively been excluded from participating in or benefiting from, not only the current growth in the downtown area, but also from the economic growth of St. Petersburg.

In a belated attempt to address the social and economic problems of the south side of the city, following the approval of Pinellas County Board of Commissioners 2012 Workshop Session: The Economic Impact of Poverty, members of the County Commissioners and St. Petersburg City council began taking steps to authorize the Southside St. Petersburg CRA.

The longstanding economic malaise of the near south side of the city, coupled with the inability of other redevelopment initiatives to reverse their respective areas’ economic ill health, prompts concerns about the ability of the new Southside CRA to stimulate the desired economic changes for its current residents versus gentrification of the area. They also raise questions about the effectiveness of the underlying economic development policies and practices employed, as well as the goals, theories and assumptions on which they are based.

What, then, are the questions  we should consider to evaluate the effectiveness of redevelopment, and, if and when we determine the ‘answers,’ what should we do to achieve it?

That will be the subject of subsequent posts.

 

 

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Leverage Points

Changing the System Part II

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“The definition of lunacy,” Betalden adds, “is to keep doing what you’ve always done and expect different results.”

Now that we understand ‘system,’ how can we change the structure of the economic system to produce more of what we want, economic equality, and less of that which is undesirable, inequality?

One techniques to help understand how to change a system’s structure involves applying interventions at key leverage points, places in the system where a small change could lead to a large shift in behavior.  In “Thinking in Systems,” Donella Meadows enumerates, in ascending order, 12 key leverage points in terms of effect on the system.  Here are the top 6:

6.  Information flow – the structure of who does and does not have access to information.

Missing information flows is one of the most common causes of system malfunction.   Adding or restoring information can be a powerful intervention.  It’s important that the missing feedback be restored to the right place and in compelling form.   There is a systematic tendency on the part of human beings to avoid accountability for their own decisions.   An example is the rapid draining of the Ogallala Aquifir, an underground pool of fresh water that stretches from Northern Texas to Wyoming.  Closely related is the proposed Keystone XL pipeline, originally planned to pass thru areas of the Ogallala Aquifir, that is supposed to transport tar sands oil from Alberta to the oil refineries on the Gulf Coast of the US.

5.  Rules – incentives, punishments, constraints

The rules of the system define its scope, its boundaries, its degrees of freedom.  Constitutions are the strongest examples of social rules.  Laws, punishments, incentives and informal social arrangements are progressively weaker rules.  Rules are high leverage points.  Power over rules is real power.  If you want to understand the deepest malfunctions of systems, pay attention to the rules and who has the power over them.

4.  Self-organization – the power to add, change, evolve system structure

The power of self-organization (emergence) seems so wondrous that we tend to regard it as mysterious, miraculous, heaven sent.   Self-organization is basically a matter of an evolutionary raw material – a highly variable stock of information from which to select possible patterns – and a means for experimentation, for selecting and testing new patterns.  The intervention point here is obvious, but unpopular.  Encouraging variability and experimentation and diversity means “losing control.”  Self-organization produces heterogeneity and unpredictability.   It reqires freedom and experimentation, and a certain amount of disorder.  These conditions that encourage self-organization often can be scary for individuals and threatening to power structures.  As a consequence, education systems may restrict the creative powers of children instead of stimulating those powers.  Economic policies may lean toward supporting established, powerful enterprises rather than upstart, new ones.  And many governments prefer their people not to be too self-organizing.

3.  Goals – the goal or purpose of a system

“Right there, the diversity-destroying consequence of the push for control demonstrates why the goal of a system is a leverage point superior to the self-organizing ability of a system.  If the goal is to bring more and more of the world under the control of one particular central planning system (Wal-Mart), then everything further down the list, physical stocks and flows, feedback loops, information flows, even self-organizing behavior, will be twisted to conform to that goal…

“What is the point of the game?  To grow, to increase market share, to bring the world (customers, suppliers, regulators) more and more under the control of the corporation so that its operations becomes ever more shielded from uncertainty…to engulf everything…It’s the goal of cancer, too…

“That’s what Ronald Reagan did, and we watched it happen.  Not long before he came into office, a president could say “Ask not what government can do for you, ask what you can do for the government,” and no one even laughed.  Reagan said over and over, the goal is not to get the people to help the government and not to get government to help people, but to get government off our backs.  One can argue, and I would, that larger system changes and the rise of corporate power over government let him get away with that.  But the thoroughness with which the public discourse is the United States and even the world has been changed since Ronald Reagan is testimony to the high leverage of articulating, meaning, repeating, standing up for, insisting upon, new system goals.” – Donella Meadows

2.  Paradigms – the mind-set out of which the system – its goals, structures, rules, delays, parameters – arises

Paradigms are the sources of systems.  From them, from shared social agreements about the nature of reality, come system goals and information flows, feedbacks, stocks, flows, and everything else about systems.  You could say paradigms are harder to change than anything else about a system, and therefore this item should be lowest on the list, not second-to-highest.  But there’s nothing physical or expensive or even slow in the process of paradigm change.  In a single individual it can happen in a millisecond.  All it takes is a click in the mind, a falling of scales from the eyes, a new way of seeing.

So how do you change paradigms?  Thomas Kuhn, who wrote the seminal book about the great paradigm shifts of science, has a lot to say about that:

“You keep pointing at the anomalies and failures in the old paradigm.  You keep speaking and acting, loudly and with assurance, from the new one.  You insert people with the new paradigm in places of public visibility and power.  You don’t waste time with reactionaries; rather you work with active change agents and with the vast middle ground of people who are open minded.” – Thomas Kuhn

1.  Transcending paradigms

“There is yet one leverage point that is even higher than changing a paradigm.  That is to keep oneself unattached to the area of paradigms, to stay flexible, to realize that no paradigm is “true,” that every paradigm, including the one that sweetly shapes your own worldview, is a tremendously limited understanding of an immense and amazing universe that is far beyond human comprehension.” – Donella Meadows

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Taking a Systems View

“If a factory is torn down but the rationality which produced it is left standing, then the rationality will simply produce another factory. If a revolution destroys a government, but the systematic patterns of thought that produced that government are left intact, then those patterns will repeat themselves…There’s so much talk about the system. And so little understanding.”—Robert Pirsig, Zen And the Art of Motorcycle Maintenance.

082113_1414_TakingaSyst1.jpg

In Thinking in Systems, Donella Meadows uses a Slinky® to introduce a central concept about systems: that behavior is related to structure the way the elements and interconnections work together to achieve a function or purpose.   Systems aren’t just any old collection of things.  A system is an interconnected set of elements that is coherently organized in a way that achieves something.  For example, the elements of your digestive system include teeth, enzymes, stomach and intestines.  They are interrelated through the physical flow of food, and through an elegant set of regulating chemical signals.  The function of the system is to break down food into the basic nutrients and to transfer those nutrients into the bloodstream (another system) while discarding unusable products.  A school is a system.  So is a city, and a factory, and a corporation, and a national economy.

Systems produce the effects they do because of the way they are structured, the interconnections between elements, and their purposes.  The elements of a system are often the easiest parts of a system to notice because many of them are visible, tangible things.  The elements of a tree are roots, trunk, branches and leaves.   But before going too far in that direction, it’s a good idea to stop dissecting out elements and to start looking for the interconnections, the relationships that hold the elements together…Some interconnections in systems are actual physical flows, such as the water in the tree’s trunk or the students progressing through a university.   Many interconnections are flows of information – signals that go to decision points or action points within a system…

If information-based relationships are hard to see, functions or purposes are even harder.  A system’s function or purpose is not necessarily written or expressed explicitly, except through the operation of the system.  Purposes are deduced from behavior, not from rhetoric or stated goals.

You can understand the relative importance of a system’s elements, interconnections and purposes by imagining them changed one by one.  A tree changes its cells constantly, the leaves every year or so, but it is still essentially the same tree.  If you change the players of a football team performance is usually not significantly affected.  Change the rules of the game from football to basketball and you have, as they say, a whole new ball game.  Changes in purposes can be drastic.  What if you keep the players and the rules but change the purpose – from winning to losing?

 

steoy-behaviour

Systems fool us by presenting themselves – or we fool ourselves by seeing the world – as a series of events.  We are less likely to be surprised if we can see how events accumulate into dynamic patterns of behavior.  Long term behavior provides clues to the underlying systemic structure.

Leverage Points – Places to Intervene in a System

Systems can be complicated and surprising in the way they resist change.  Leverage points, the silver bullet, the trim tab, the miracle cure, are points of power that when engaged can cause changes to the system out of proportion to their relative size.  In descending order of influence:

  1. Transcending Paradigms – That no paradigm is ‘true,’ that every one, including your own, is a tremendously limited understanding of an immense and amazing universe that is far beyond human comprehension.
  2. Paradigms – The shared idea in the minds of society, the great big unstated assumption, constitute that society’s paradigm, or deepest set of beliefs about how the world works. E.g. Growth is good. One can ‘own’ land. The selfish actions of individual players in markets wonderfully accumulate to the common good. Paradigms are the sources of systems.
  3. Goals – The purpose of function of the system. The diversity-destroying consequence of the push for control demonstrates why the goal of a system is a leverage point superior to the self-organizing ability of a system.
  4. Self-Organization – The power to add, change, or evolve system structure. In biological systems that power is called evolution. In human economies it’s called technical advance or social revolution. The genetic code within the DNA that is the basis of all biological evolution contains just four different letters combined into words of three letters each. Intervening here is obvious but unpopular. Encouraging variability and experimentation and diversity means ‘losing control.’
  5. Rules – Incentives, punishments, constraints. As we try to imagine restructured rules and what our behavior would be under them we come to understand the power of rules. They are high leverage points. Power over the rules is real power.
  6. Information Flows – The structure of who does and does not have access to information. Missing information flows is one of the most common causes of system malfunction. Adding or restoring information can be a powerful intervention, usually much easier and cheaper than rebuilding physical infrastructure.

Systems work well because of three characteristics:

  • Resilience – the ability to bounce or spring back into shape, position, etc., after being pressed or stretched. Elasticity. Resilience arises from a rich structure of many feedback loops that can work in different ways to restore a system even after large perturbations. Because resilience is something that is very hard to see without a whole systems view, people often sacrifice resilience for stability or productivity or some more immediately recognizable system property.
  • Self-Organization – The capacity of a system to make its own structure more complex, to learn, diversify, evolve. Like resilience, self-organization is often sacrificed for purposes of short-term productivity and stability, the usual excuses for turning creative human beings into mechanical adjuncts in production processes. Self-organization produces heterogeneity and unpredictability. It requires freedom and experimentation, and a certain amount of disorder. These conditions often can be scary for individuals and threatening to power structures. Out of simple rules of self-organization can grow systems of great complexity.
  • Hierarchy – the arrangement of subsystems aggregated into larger subsystems, aggregated into still larger subsystems. E.g. A cell in your liver is a subsystem of an organ, which is a subsystem of you as an organism. Hierarchies evolve from the lowest level up. When a subsystem’s goals dominate at the expense of the total system’s goals, the resulting behavior is called suboptimization. Too much central control is just as damaging. To be a highly functional system, hierarchy must balance the welfare, freedoms, and responsibilities of the subsystems and total system – there must be enough central control to achieve coordination toward the large-system goal, and enough autonomy to keep all subsystems flourishing, functioning, and self-organizing.
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Simple, Complicated, Complex

http://weirderthanyouthink.files.wordpress.com/2008/11/complexity-pattern-animation.gif?w=500

The creation of complexity from simplicity – Chris Madden

The term complexity was popularized in the mid-20th century by Warren Weaver. Weaver identified three broad categories of systems: simple, complicated, and complex.

Simple systems are made of only a few interacting inert objects like billiard balls or satellites. Complicated systems, like automobiles or airplanes, may have thousands of parts or more. However, once designed and built, even complicated instruments perform in very predictable, mechanical, ways. Bicycles, automobiles, and even robotic systems turn out to be everyday items whose degree of complicatedness we take for granted.

Early scientists –– Galileo, Descartes, and Newton – developed a set of analytic methods to reduce these simple systems to basic laws. Analytic methods were literally understood in terms of cutting apart all objects and all claims to truth to their root causes and assumptions in order to reassemble them into complete explanatory systems. These methods were so effective that by the early 1800s Laplace could assert:

“Given for one instant an intelligence which could comprehend all forces by which nature is animated and the respective situations of the being which compose it – an intelligence sufficiently vast to submit these data to analysis – it would embrace in the same formula the movements of the greatest bodies and those of the lightest atom; for it, nothing would be uncertain and the future, as the past, would be present to its eyes.”

In other words, there are no accidents; everything that is going to happen is determined by what has already happened, and everything that has already happened can be determined from current conditions.

Early in the 1900s, however, belief in analysis and the ability to predict the future and determine the past from present conditions began to be questioned.   French mathematician Henri Poincare’ explained that:

“…it may happen that small differences in the initial conditions produce very great ones in the final phenomenon. A small error in the former will produce an enormous error in the latter. Prediction becomes impossible.”

Complex* systems have features that are also complicated and may act in patterned ways, but whose interactions are constantly changing. An air traffic control system is complex because its functioning depends on many variables that keep varying, such as weather, aircraft downtime, peak loading, etc.

With complicated systems, one can usually predict outcomes by knowing the design (or having a detailed engineering manual at hand). In contrast, depending on the interplay of the elements in the system, complex systems may produce highly divergent outcomes.

It is impossible to predict the way a complex system will respond with sufficient accuracy. One is limited to establishing the conditions characteristic of a complex system that lead to emergence,** then working creatively at leverage points to change the configuration of the system until the desired ends are produced.

*For a system to be classed as complex, it must manifest several necessary qualities:

1. Emergence (self-organization)

Emergence (e.g. ants, birds flocking, human social groups) is a primary quality of a learning system where these collectives develop capacities that can exceed the possibilities of the same group of agents if they were made to work independently; where people that need not have much in common, much less be oriented by a common goal, can join in a collective group that seems to develop a clear purpose.

**The conditions for emergence:

  • Internal diversity—a source of possible responses to emergent circumstances. One cannot specify in advance what sorts of variation will be necessary for appropriately intelligent action.
  • Internal redundancy—the complement to diversity; enables the habituated, moment-to-moment interactivity of the agents that constitute a system.
  • Neighbor interaction—the neighbors that must interact with one another are ideas, hunches, queries, and other manners of representation.
  • Distributed control—one must relinquish any desire to control the structure and outcomes of the collective; one must give up control if complexity is going to happen.
  • Randomness—the structures that define complex social systems maintain a delicate balance between sufficient coherence to orient agents’ actions and sufficient randomness to allow for flexible and varied response.
  • Coherence.

2. Bottom up

Emergence is an example of “bottom up” organization; it does not require a “leader,” per se. Emergence is a paradox: a manifestation of a collective intelligence, but intelligent group action is dependent on the independent actions of diverse individuals. (“Intelligence” is the quality of exploring a range of possible actions and selecting ones that are well suited to the immediate situation; a repertoire of possibilities, and a means to discern the relative effectiveness of each possibility, not unlike creativity.)

  • Non-polarized groups can consistently make better decisions and come up with better answers than most of their members and…often the group outperforms the best member.
  • You do not need a consensus in order…to tap into the wisdom of a crowd, and the search for consensus encourages tepid, lowest-common-denominator solutions which offend no one rather than exciting everyone.
  • The rigidly hierarchical, multilayered corporation…discourages the free flow of information.
  • Decisions about local problems should be made, as much as possible, by people close to the problem…People with local knowledge are often best positioned to come up with a workable and efficient solution.
  • The evidence in favor of decentralization is overwhelming…The more responsibility people have with their own environments, the more engaged they will be.
  • Individual irrationality can add up to collective rationality.
  • Paradoxically, the best way for a group to be smart is for each person to act as independently as possible.

3. Scale-free networks

A so-called scale-free (decentralized) network, which consists of nodes nodding into grander nodes, usually on several levels of organization, is more robust than a centralized network because if a node were to fail, it is unlikely that the whole system will collapse.) A decentralized network will decay into a centralized network under stress. For example, when time is a scarce commodity, the most common organizational strategy is a central network with a leader or teacher as the hub and employees or students at the ends of the spokes. This works against the “intelligence” of the organization by preventing agents from pursuing their own self-interest and obsessions, preventing diversity of experience.

4. Nested organization

An immediate implication of a decentralized architecture is that distinct levels o of organization can emerge.

5. Ambiguously bounded, but organizationally closed systems

  • Complex systems are “open”; that is they are constantly exchanging matter and/or information with their contexts. In a situation where a collective is working on a project, it is rarely a simple matter to discern who has contributed what, especially if the final product is at all sophisticated.
  • Complex systems usually arise from and are part of other complex systems, even while being coherent and discernible unities. Where does an agent stop and a collective begin? The question is sometimes easily answered. After all the distinction between an ant and an anthill seems relatively straightforward. However, if one considers more complex systems, for example, and individuals personality, the situation becomes much more difficult.
  • Distinguishable but intimately intertwined networks can and do exist in the same “spaces.” Consider the relationship between one’s neural system and one’s system of understandings, both of which can be understood in terms of decentralized networks, but neither of which can be collapsed into the other.

6. Structure-determinism

Structured-determined behavior is one of the key characteristics used to distinguish a complex unity from a complicated (mechanical) system. The manner in which a complicated system will respond to a perturbation is generally easy to figure out, simply because its responses are determined by the perturbation. For example, if a block of wood is nudged, its response will be quite different than if you nudge a dog. The response will not be determined by you, but by the dog. What is more, not even experience with nudging will provide an adequate knowledge of what will happen if it is repeated—for two reasons. First, a complex system learns. That is, it is constantly altering its own structure in response to emergent experiences. Secondly, systems that are virtually identical will respond differently to the same perturbation. Hence one cannot generalize the results from one system to another…it problematizes the contemporary desire for “best practices” in education—a notion that what works well in one context should work well in most contexts. That only makes sense when talking about mechanical systems.

7. Far-from-equilibrium

Complex systems do not operate in balance; indeed, a stable equilibrium implies death for a complex system.

8. Short-range relationships

Most of the information is exchanged among close neighbors, meaning that the system’s coherence depends mostly on agents’ immediate interdependencies, not on centralized control or top-down administration. A “win-win logic”; an agent’s situation will likely improve if the situations of his/her/its nearest neighbors improve. A “we” is usually better than an “I” for all involved.

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A Perfectly Designed System

systems-thinking the perfect system

“A system is perfectly designed to get the results it gets.”Paul Batalden

Part III

Over the past 40 years the US economic system has been, and continues to be, systematically altered to funnel more and more of America’s wealth to the already rich, the “have-mores,” and away from the “have-nots.” The shift of wealth is accompanied by a commensurate shift of more and more economic and political power to the already powerful, undermining the foundations of democracy. If we want to live in a society where the people govern themselves, share the same rights and responsibilities, and decide for themselves how the products of the economy are to be distributed, we must learn to work together to define that society and create it.

A sense of progress toward ideals gives meaning to life and makes choice significant. The belief that the future depends on what we do between now and then enhances this quality.

Many of our problems derive from trying to get rid of a dissatisfaction we feel; for instance with the way the car is working , or how much a certain item costs. This is reactive problem solving, an effort to get rid of what we don’t want. We tend to respond more to our dislikes than our likes, more by our hates than by our loves. It often results in unforeseen consequences that may be worse than the original problem. For instance, DDT.

In proactive problem solving we decide what we want and try to create it. It reduces the likelihood that we will overlook the consequences of our solutions. When embedded in proactive planning, designing a future and finding ways to move toward it as effectively as possible is called idealized redesign. But no idealized design can remain ideal for long. The goal then is not an ideal state or system but an ideal-seeking state or system. Its designers need not have all the answers, but they should design into the system the capability of finding them. The redesigning is never complete. It is subject to continual revision in light of newly acquired information, knowledge, understanding, wisdom and imagination.

German philosopher Friedrich von Schiller believed that human development depends on the successful negotiation between contradictory forces of existence; in fact, there is “no other way to develop the manifold aptitudes of man than to bring them in opposition with one another.” For Schiller, these forces could indeed be harmonized in the balance between sensibility and reason that is the aesthetic condition, or what Schiller called the Spieltrieb. The character of Spiel is the will to play, the will to create, also the will to beauty. Creating must be playful, for according to Schiller, it is only in play that humans are really human. The domain of Spiel opens up, it seems, an aesthetic void, where the product created or even the time it takes cannot be scripted.

In the aesthetic condition the process of creativity or innovation can be thought of as knowledge “production;” as an ever-expanding space of possibility that is opened and enlarged simply by exploring the space of what is currently possible. A society for the future might be thought of as being oriented toward creating the as-yet unimagined – indeed, the currently unimaginable. Such a ‘goal’ can only be understood in terms of exploration of the current possibilities. Rather than focusing on perpetuating entrenched habits, society must be principally concerned with ensuring the conditions for the emergence of the as-yet unimagined.

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