Warm Data Lab Host Certification 2part Training, London, UK Dec 10-12 & Feb 8-10 

by Nora Bateson, President International Bateson Institute

Warm Data Lab Certification from Nora Bateson & the International Bateson Institute:

“Nora has the ability to hold the attention of groups with her deep-rooted insights into the way our natural world works. Her seminars are enlightening, highly enjoyable and challenging, and having attended, you may well come away reflecting on your own personal worldview.

Warm Data Lab Process

For the past couple of hundred years, we have been enticed into seeing the world through mechanistic metaphors which include the delusions of individuality and control, and the Cartesian view that the world can be divided into parts. The Warm Data Lab, which Nora Bateson has introduced to the world, is a grounded approach that enables us to experience how everything, including our institutions, concepts, thoughts and interactions, is interdependent and interrelated. The Warm Data exists in the space in between concepts and people. It enables groups to work with their complex challenges by perceiving the multiple perspectives that inevitably exist.” Eric Lynn -CultureQ’s

This training session offered by Nora Bateson offers certification for those who wish to complete the training to host Warm Data Labs with groups internationally. The Warm Data Lab process is an inviting and seemingly simple way to bring a group of people into dialogue around complex issues. Anyone, of any age or profession can participate in a Warm Data Lab. From school children to executives, families and companies the Warm Data lab is an open forum of learning, discussing, and discovery. It is not based on prior knowledge, or skill, but will increase both in an atmosphere of mutual learning.

Hosting a Warm Data lab is another story. The host of a Warm Data Lab must have a strong base in the many theoretical foundations that underpin the process. An effective Warm Data Lab experience requires a prepared and organized host. In contrast to the appearance of the simple openness of the Warm Data Lab, the rigor in which the group is held is critical.

A good Warm Data Lab is an artful balance of both holding open the group’s horizon of learning, and generating conditions for a rigorous and multi faceted discovery to take place. The magic of the process is in the participants’ own connection and learning, which cannot be forced or funneled into any particular “knowing”, but must instead be invited to make new associations, linkages and perceptions – as individuals in mutual learning.

Once you have completed the course of training you will be certified by the International Bateson Institute to host groups who are interested in using Warm Data to facilitate their work on complex issues. You will not however be certified to train others in becoming Warm Data lab hosts.

What the training and certification entails:
1. A sound understanding of the structure, timing and form of the Warm
Data Lab Process. This includes trouble shooting guidelines of “what
not to do.”
2. Practice setting up, hosting and holding the group through the
process.
a. Prep: How to set up the questions and contexts
b. Process : How to support the group during the Lab
c. What next? After the session, how to hold the discussion of
practical application.
d. Follow up. We have a growing group now of WDL practitioners that meet to discuss and explore furthur learning in this emerging field.

  1. A firm grasp of the theory involved. See list below.

Theory: There are several theories at work within this process. I will list a
few of them in category form, but not define the theories. All of the theory below threads through the concept and usage of abductive process within the WDL.
1. Patterns that connect (Bateson)
2. Bertrand Russell’s Logical Levels
3. Difference that makes a difference (Bateson)
4. Multiple description (Bateson)
5. Mutual learning and calibration (Symmathesy)
6. Iterative multi-modal learning (Symmathesy)
7. Autopoeisis (Varella and Maturana)
8. Mind (G. Bateson)
9. Systems and Complexity Theory (Multiple theorists)
10. Ecology of communication (Bateson & others)
11. Double Bind (Bateson)
12. Conscious Purpose (Bateson)
13. Epistemological frames
14. Change in complex systems (Meadows)
15. Interdependency

What is a Warm Data Lab?
Most people who are interested in the training and certification session will have likely already been participants in a Warm Data Lab and discovered for themselves how the process facilitates their working practice. For those who
have not personally been a part of a Warm Data group, here is a brief description:

Developed by Nora Bateson, this is an exercise for use with groups who are interested in strengthening and further practicing their collective ability to perceive, discuss and research complex issues. By shifting perspectives, the
Warm Data Lab process increases ability to respond to difficult or “wicked” issues. Because so many of the challenges that we face now are complex, we need approaches to meeting that complexity. Although there is a desire to reframe these complex issues in simple terms that might lend themselves to easy solutions, this usually leads to the dangers of unintended consequences of reductionism… and further problems.

But, thinking in complexity requires the ability to perceive across multiple perspectives and contexts. This is not a muscle that has been trained into us in school or in the work world. It is a skill acutely needed in this era to meet our personal, professional and collective need to respond to crisis, and to improve our lives.

The Warm Data lab is a living kaleidoscope of conversation in which information and formulation of cross contextual knowing is generated. The conversational process is designed to seamlessly engage multiple theoretical principals in a practical format. The process relies on using two concepts: Transcontextual Interaction, and Symmathesy.

Transcontextual interaction is the recognition that complex systems do not exist in single contexts but rather are formed between multiple contexts that overlap in living communication.

Symmathesy: The ways in which systemic interdependency form is through contextual interaction and mutual learning. Symmathesy is the concept of mutual learning that encourages us to concentrate on how these contextual interactions inform one another, and generate learning.

“Biology, culture, and society are dependent at all levels upon the vitality of interaction they produce both internally and externally. A body, a family, a forest or a city can each be described as a buzzing hive of communication between and within its living, interacting ‘parts.’ Together the organs of your body allow you to make sense of the world around you. A jungle can be understood best as a conversation among its flora and fauna, including the insects, the fungi of decay, and contact with humanity. Interaction is what creates and vitalizes the integrity
of the living world. Over time, the ongoing survival of the organisms in their environments requires that there be learning, and learning to learn, together. Gregory Bateson said, “The evolution is in the context.” So why don’t we have a word for those bodies, families, forests and other buzzing hives of communication—and for the mutual learning that takes place within those livingcontexts?”

– From Symmathesy, a word in progress Nora Bateson 2016

 

Timings:

Dec 10 7pm-9:30pm

Dec 11 10am-1pm 2pm-5pm

Dec 12 10am-5pm

&

Feb 8 7pm-9:30pm

Feb 9 10am-5pm

Feb 10 10am -5pm

Organizer of Warm Data Lab Host Certification 2part Training London Dec 10-12 & Feb 8-10

Nora Bateson, is an award-winning filmmaker, research designer, writer and educator, as well as President of the International Bateson Institute based in Sweden.

Nora created and refined the Warm Data Lab process over the last 6 years.

More than 100 Warm Data Labs have been held internationally.

Where:

  • Harvard (including participants from Deloitte, NASA, US Army, Cigna, and more),
  • Singapore (including participants that represent women in the Islamic community, Addiction specialists, Muslim leaders, minister of security, and family therapists).
  • San Francisco: on addiction with Dr. Howard Kornfeld,
  • Stockholm: Immigration, Education, Health, Future of Work,
  • London: Health, (with doctors and politicians concerned with the NHS troubles)
  • EU Parliament: With a group of 80 youth from 50 countries on Democracy and Equality
  • Warm Data Labs have also been held in: Finland, US, Mexico, Canada, Denmark, Norway, and with many organizations.

Nora’s work asks the question “How can we improve our perception of the complexity we live within, so we may improve our interaction with the world?” An international lecturer, researcher and writer, Nora wrote, directed and produced the award-winning documentary, An Ecology of Mind, a portrait of her father, Gregory Bateson. Her work brings the fields of biology, cognition, art, anthropology, psychology, and information technology together into a study of the patterns in ecology of living systems. Her book, Small Arcs of Larger Circles released by Triarchy Press, UK, 2016 is a revolutionary personal approach to the study of systems and complexity.

The International Bateson Institute directs research projects that require multiple contexts of research. Nora coined the term “Transcontextual Research” to describe this, and called the corresponding new form of information “Warm Data”. A group process created by Nora, called the “Warm Data Lab” has been the public outreach model of this research. Over 100 groups around the world have participated in Warm Data Labs to assist in developing the ability to perceive complexity, including the Harvard LILA program.

Memberships and awards: Chair and founder of the International Bateson Institute. Board Member: Human Systems Journal of Systemic Practice, Tomorrow Makers, Fellow of Lindisfarne Foundation, Bateson Idea Group (BIG), Full member of The Club of Rome, World Academy of Arts & Sciences, Great Transition Foundation, Human Potential Foundation, Ecological Leadership, General Thinkers. Associate of The Taos Institute Awards: Sustainable Thompkins Ecology Award, Winner Spokane Film Festival, Winner Santa Cruz Film Festival, Media Ecology Award.

Source: Warm Data Lab Host Certification 2part Training London Dec 10-12 & Feb 8-10 Tickets, Multiple Dates | Eventbrite

Mechanisms for Inclusive Governance – Ison and Wallis

Mechanisms for Inclusive Governance
  • DOI:  10.1007/978-3-319-43350-9_9
  • In book: Freshwater Governance for the 21st Century
Abstract and figures
How mechanisms for inclusive governance are understood is built on the framing choices that are made about governance and that which is being governed. This chapter unpacks how governance can be understood and considers different historical and contemporary framings of water governance. A framing of “governance as praxis” is developed as a central element in the chapter. What makes governance inclusive is explored, drawing on theoretical, practical and institutional aspects before elucidating some of the different mechanisms currently used or proposed for creating inclusive water governance (though we argue against praxis based on simple mechanism). Finally, the factors that either constrain or enable inclusive water governance are explored with a focus on systemic concepts of learning and feedback.

Source:  Mechanisms for Inclusive Governance | Request PDF

2005/10 Negotiated Order and Network Form Organizations – Parhankangas, Ing, Hawk, Dane, and Kosits

2005/10 Negotiated Order and Network Form Organizations

Authors

Annaleena Parhankangas, David Ing, David L. Hawk, Gosia Dane, and Marianne Kosits

Abstract

Throughout the 20th century, the industrial age roots of hierarchical top-down planning and command-and-control supervision have been the foundations for management thinking. At the beginning of the 21st century, many futurists and systems thinkers have widely declared that businesses must equip themselves to be more responsive to rapidly changing environments. Dynamic, knowledge-based businesses require that rigid forms of business governance give way to networked forms.

Since many successful businesses have shifted from autonomous independent enterprises to building alliances and inter-organizational relationships, we advocate a renewed examination of negotiated order and a focus on the fluidity enabled by it. The traditional advantages of legal order are being outweighed by its inherent rigidity. Under conditions of rapid change, maintaining an internally consistent set of rules, essential to legal order, is inefficient and relatively ineffective.

Systems of negotiated order are characterized by situational coordination of interests, flexible definitions of desired end states, and spontaneous initiatives by interested stakeholders. We examine the development of the Linux community and its negotiated system of self-governance, and offer three additional business examples that suggest how negotiated order may provide a platform for stakeholders to innovatively leverage the dynamics of the contemporary environment.

Citation

Annaleena Parhankangas, David Ing, David L. Hawk, Gosia Dane, and Marianne Kosits, “Negotiated Order and Network Form Organizations”, in Systems Research and Behavioral Science, Volume 22, Number 5, (October 2005), pp. 431-452.

Content

Source: 2005/10 Negotiated Order and Network Form Organizations | Coevolving Innovations

‘the core protocols v.3.02’ from ‘the McCarthy Show’

[A nice example of a set of collaborative governance rules which look to boundary positions and (arguably) some emergent behaviours. These came up in the very live discussion about ‘governance’ of the facebook group ‘the ecology of systems thinking’, and I present them here as a nice example of the kind of organising approach where governance is built into the rules framework for all participants to access. I know nothing more about their context or creation other than the OP referred to them as rules for ‘high performing teams’]

From ‘the McCarthy show’

THE CORE PROTOCOLS V.3.02

(The Core is distributed under the terms of the GNU-PL. For exact terms see http://www.gnu.org/licenses/gpl.txt. The Core is considered as source code under that agreement. You are free to use and distribute this work or any derivations you care to make, provided you also distribute this source document in its entirety, including this paragraph.)

The following Core Protocols are made up of both commitments and protocols.

The Core Protocols

  • Pass (Unpass)
  • Check In
  • Check Out
  • Ask For Help
  • Protocol Check
  • Intention Check
  • Decider
  • Resolution
  • Perfection Game
  • Personal Alignment
  • Investigate

The Core Commitments

  • I commit to engage when present.
  • To know and disclose
  • what I want,
  • what I think, and
  • what I feel.
  • To always seek effective help.
  • To decline to offer and refuse to accept incoherent emotional transmissions.
  • When I have or hear a better idea than the currently prevailing idea, I will immediately either
  • propose it for decisive acceptance or rejection, and/or
  • explicitly seek its improvement.
  • I will personally support the best idea
  • regardless of its source,
  • however much I hope an even better idea may later arise, and
  • when I have no superior alternative idea.
  • I will seek to perceive more than I seek to be perceived.
  • I will use teams, especially when undertaking difficult tasks.
  • I will speak always and only when I believe it will improve the general results/effort ratio.
  • I will offer and accept only rational, results-oriented behavior and communication.
  • I will disengage from less productive situations
  • When I cannot keep these commitments,
  • When it is more important that I engage elsewhere.
  • I will do now what must be done eventually and can effectively be done now.
  • I will seek to move forward toward a particular goal, by biasing my behavior toward action.
  • I will use the Core Protocols (or better) when applicable.
  • I will offer and accept timely and proper use of the Protocol Check protocol without prejudice.
  • I will neither harm—nor tolerate the harming of—anyone for his or her fidelity to these commitments.
  • I will never do anything dumb on purpose.

Pass (Unpass)

The Pass protocol is how you decline to participate in something. Use it anytime you don’t want to participate in an activity.

Steps

  • When you’ve decided not to participate, say “I pass. ”
  • Unpass any time you desire. Unpass as soon as you know you want to participate again by saying “I unpass. ”

Commitments

  • Hold reasons for passing private.
  • Pass on something as soon as you are aware you are going to pass.
  • Respect the right of others to pass without explanation.
  • Support those who pass by not discussing them or their pass.
  • Do not judge, shame, hassle, interrogate or punish anyone who passes.

Notes

  • In general, you will not be in good standing with your Core Commitments if you pass most of the time.
  • You can pass on any activity; however, if you have adopted the Core Commitments, you cannot pass on a Decider vote and you must say “I’m in” when checking in.
  • You can pass even though you have already started something.

Check In

Use Check In to begin meetings or anytime an individual or group Check In would add more value to the current team interactions.

Steps

  • Speaker says “I feel [one or more of MAD, SAD, GLAD, AFRAID].” Speaker may provide a brief explanation. Or if others have already checked in, the speaker may say “I pass.” (See the Pass protocol.)
  • Speaker says “I’m in.” This signifies that Speaker intends to behave according to the Core Commitments.
  • Listeners respond, “Welcome.”

Commitments

  • State feelings without qualification.
  • State feelings only as they pertain to yourself.
  • Be silent during another’s Check In.
  • Do not refer to another’s Check In disclosures without explicitly granted permission from him or her.

Notes

  • In the context of the Core Protocols, all emotions are expressed through combinations of MAD, SAD, GLAD, or AFRAID. For example, “excited” may be a combination of GLAD and AFRAID.
  • Check In as deeply as possible. Checking in with two or more emotions is the norm. The depth of a group’s Check In translates directly to the quality of the group’s results.
  • Do not do anything to diminish your emotional state. Do not describe yourself as a “little” mad, sad, glad, or afraid or say “I’m mad, but I’m still glad.”
  • Except in large groups, if more than one person checks in, it is recommended that all do so.
  • HAPPY may be substituted for GLAD, and SCARED may be substituted for AFRAID.

Check Out

Check Out requires that your physical presence always signifies your engagement. You must Check Out when you are aware that you cannot maintain the Core Commitments or whenever it would be better for you to be elsewhere.

Steps

  • Say “I’m checking out.”
  • Physically leave the group until you’re ready to Check In once again.
  • Optionally, if it is known and relevant, you can say when you believe you’ll return.
  • Those who are present for the CheckOut may not follow the person, talk to or about the person checking out or otherwise chase him or her.

Commitments

  • Return as soon as you can and are able to keep the Core Commitments.
  • Return and Check In without unduly calling attention to your return.
  • Do not judge, shame, hassle, interrogate, or punish anyone who checks out.

Notes

  • When you CheckOut do it as calmly and gracefully as possible so as to cause minimal disruption to others.
  • Check Out if your emotional state is hindering your success, if your receptivity to new information is too low, or if you do not know what you want.
  • Check Out is an admission that you are unable to contribute at the present time.

Ask For Help

The Ask For Help protocol allows you to efficiently make use of the skills and knowledge of others. Ask For Help is the act that catalyzes connection and shared vision. Use it continuously, before and during the pursuit of any result.

Steps

  • Asker inquires of another, “[Helper’s name], will you X?”
  • Asker expresses any specifics or restrictions of the request.
  • Helper responds by saying “Yes” or “No” or by offering an alternative form of help.

Commitments

  • Always invoke the Ask For Help Protocol with the phrase “Will you . . .
  • Have a clear understanding of what you want from the Helper or if you do not have a clear understanding of what help you want, signal this by saying “I’m not sure what I need help with, but will you help me?”
  • Assume that all Helpers are always available and trust that any Helper accepts the responsibility to say “No.”
  • Say “No” any time you do not want to help.
  • Accept the answer “No” without any inquiry or emotional drama.
  • Be receptive of the help offered.
  • Offer your best help even if it is not what the asker is expecting.
  • Postpone the help request if you are unable to fully engage.
  • Request more information if you are unclear about the specifics of the help request.
  • Do not apologize for asking for help.

Notes

  • Asking for help is a low-cost undertaking. The worst possible outcome is a “No,” which leaves you no further ahead or behind than when you asked. In the best possible outcome, you reduce the amount of time required to achieve a task and/or learn.
  • Helpers should say “No” if they are not sure if they want to help. They should say nothing else after turning down a request for help.
  • You cannot “over-ask” a given person for help unless he or she has asked you to respect a particular limit.
  • If you don’t understand the value of what is offered, or feel that it wouldn’t be useful, or believe yourself to have considered and rejected the idea offered previously, assume a curious stance instead of executing a knee-jerk “But . . .” rejection. (See the Investigate protocol.)
  • Asking in time of trouble means you waited too long to ask for help. Ask for help when you are doing well.
  • Simply connecting with someone, even if he or she knows nothing of the subject you need help on can help you find answers within yourself, especially if you ask that person to Investigate you.

Protocol Check

Use Protocol Check when you believe a protocol is being used incorrectly in any way or when a Core Commitment is being broken.

Steps

  • Say “Protocol Check.”
  • If you know the correct use of the protocol, state it. If you don’t, ask for help.

Commitments

  • Say “Protocol Check” as soon as you become aware of the incorrect use of a protocol, or of a broken Core Commitment. Do this regardless of the current activity.
  • Be supportive of anyone using Protocol Check.
  • Do not shame or punish anyone using Protocol Check.
  • Ask for help as soon as you realize you are unsure of the correct protocol use.

Intention Check

Use Intention Check to clarify the purpose of your own or another’s behavior. Use it when you aren’t expecting a positive outcome resulting from the current behavior. Intention Check assesses the integrity of your own and another’s intention in a given case.

Steps

  • Ask “What is your/my intention with X?” where X equals some type of actual or pending behavior to the person whose intention you want to know.
  • If it would be helpful, ask “What response or behavior did you want from whom as X?”

Commitments

  • Be aware of your own intention before checking the intention of another.
  • Investigate sufficiently to uncover the intention of the person or his actions.
  • Make sure you have the intention to resolve any possible conflict peacefully before intention checking someone else. If you do not have a peaceful intention, Check Out.
  • Do not be defensive when someone asks you what your intention is. If you can’t do this, Check Out.

Notes

  • If conflict arises that seems irresolvable, Check Out and Ask For Help.

 

 

Decider

Use Decider anytime you want to move a group immediately and unanimously towards results.

Steps

  • Proposer says “I propose [concise, actionable behavior].”
  • Proposer says “1-2-3.”
  • Voters, using either Yes (thumbs up), No (thumbs down), or Support-it (flat hand), vote simultaneously with other voters.
  • Voters who absolutely cannot get in on the proposal declare themselves by saying “I am an absolute no. I won’t get in.” If this occurs, the proposal is withdrawn.
  • Proposer counts the votes.
  • Proposer withdraws the proposal if a combination of outliers (No votes) and Support-it votes is too great or if proposer expects not to successfully conclude Resolution (below). You can approximate “too great” by using the followingheuristics:
  • approximately 50% (or greater) of votes are Support-it, OR
  • the anticipated gain if the proposal passes is less than the likely cost of Resolution effort
  • Proposer uses the Resolution protocol with each outlier to bring him in by asking, “What will it take to get you in?”
  • Proposer declares the proposal carried if all outliers change their votes to Yes or Support-it.
  • The team is now committed to the proposed result.

Commitments

  • Propose no more than one item per proposal.
  • Remain present until the Decider protocol is complete; always remain aware of how your behavior either moves the group forward or slows it down.
  • Give your full attention to a proposal over and above all other activity.
  • Speak only when you are the proposer or are directed to speak by the proposer.
  • Keep the reasons you voted as you did to yourself during the protocol.
  • Reveal immediately when you are an absolute no voter and be ready to propose a better idea.
  • Be personally accountable for achieving the results of a Decider commitment even if it was made in your absence.
  • Keep informed about Decider commitments made in your absence.
  • Do not argue with an absolute no voter. Always ask him or her for a better idea.
  • Actively support the decisions reached.
  • Use your capacity to “stop the show” by declaring you “won’t get in no matter what” with great discretion and as infrequently as possible.
  • Insist at all times that the Decider and Resolution protocols be followed exactly as per specification, regardless of how many times you find yourself doing the insisting.
  • Do not pass during a Decider.
  • Unceasingly work toward forward momentum; have a bias toward action.
  • Do not look at how others are voting to choose your own vote.
  • Avoid using Decider in large groups. Break up into small subgroups to make decisions, and use the large group to report status.

Notes

  • Vote No only when you really believe the contribution to forward momentum you will make to the group after slowing or stopping it in the current vote will greatly outweigh the (usually considerable) costs you are adding by voting No.
  • If you are unsure or confused by a proposal, support it and seek clarification offline after the proposal is resolved. If you have an alternate proposal after receiving more information, you can have faith that your team will support the best idea. (See “The Core Commitments”)
  • Voting No to make minor improvements to an otherwise acceptable proposal slows momentum and should be avoided. Instead, offer an additional proposal after the current one passes or, better yet, involve yourself in the implementation to make sure your idea gets in.
  • Withdraw weak proposals. If a proposal receives less than seventy percent (approximately) Yes votes, it is a weak proposal and should be withdrawn by the proposer. This decision is, however, at the discretion of the proposer.
  • Think of yourself as a potential solo outlier every time you vote No.
  • Vote Absolute No only when you are convinced you have a significant contribution to make to the direction or leadership of the group, or when integrity absolutely requires it of you.

Resolution

When a Decider vote yields a small minority of outliers, the proposer quickly leads the team, in a highly structured fashion, to deal with the outliers. The Resolution protocol promotes forward momentum by focusing on bringing outliers in at least cost.

Steps

  • Proposer asks outlier “What will it take to get you in?”
  • Outlier states in a single, short, declarative sentence the precise modification required to be in.
  • Proposer offers to adopt the outlier’s changes or withdraws the proposal.

Notes

  • If the outlier’s changes are simple, a simple Eye Check is performed to determine if everyone is still in.
  • If the outlier’s changes are complex, the proposer must withdraw the current proposal and then submit a new proposal that incorporates the outlier’s changes.
  • If the outlier begins to say why he voted No or to explain anything other than what it will take to get him in, the proposer must interrupt the outlier with “What will it take to get you in?”

 

 

Perfection Game

The Perfection Game protocol will support you in your desire to aggregate the best ideas. Use it whenever you desire to improve something you’ve created.

Steps

  • Perfectee performs an act or presents an object for perfection, optionally saying “Begin” and “End” to notify the Perfector of the start and end of the performance.
  • Perfector rates the value of the performance or object on a scale of 1 to 10 based on how much value the Perfector believes he or she can add.
  • Perfector says “What I liked about the performance or object was X,” and proceeds to list the qualities of the object the Perfector thought were of high quality or should be amplified.
  • Perfector offers the improvements to the performance or object required for it to be rated a 10 by saying “To make it a ten, you would have to do X.”

Commitments

  • Accept perfecting without argument.
  • Give only positive comments: what you like and what it would take to “give it a 10.”
  • Abstain from mentioning what you don’t like or being negative in other ways.
  • Withhold points only if you can think of improvements.
  • Use ratings that reflect a scale of improvement rather than a scale of how much you liked the object.
  • If you cannot say something you liked about the object or specifically say how to make the object better, you must give it a 10.

Notes

  • A rating of 10 means you are unable to add value, and a rating of 5 means you will specifically describe how to make the object at least twice as good.
  • The important information to transmit in the Perfection Game protocol improves the performance or object. For example, “The ideal sound of a finger snap for me is one that is crisp, has sufficient volume, and startles me somewhat. To get a 10, you would have to increase your crispness.”
  • As a perfectee, you may only ask questions to clarify or gather more information for improvement. If you disagree with the ideas given to you, simply don’t include them.

Personal Alignment

The Personal Alignment protocol helps you penetrate deeply into your desires and find what’s blocking you from getting what you want. Use it to discover, articulate, and achieve what you want. The quality of your alignment will be equal to the quality of your results.

Steps

  • Want. Answer the question: “What specifically do I want?”
  • Block. Ask yourself, “What is blocking me from having what I want?”
  • Virtue. Figure out what would remove this block by asking yourself “What virtue—if I had it— would shatter this block of mine?”
  • Shift. Pretend the virtue you identified is actually what you want.
  • Again. Repeat steps 2 to 4 until this process consistently yields a virtue that is powerful enough to shatter your blocks and get you what you originally thought you wanted.
  • Done. Now write down a personal alignment statement in the form “I want [virtue].” For example, “I want courage.”
  • Signal/Response/Assignment. Create a signal to let others know when you are practicing your alignment, and provide a response they can give you to demonstrate support. For example, “When I say/do ‘X,’ will you say/do ‘Y’?” Optionally, turn it into an assignment by saying you will do X a certain number of times per day, where X equals an activity that requires you to practice living your alignment.
  • Evidence. Write, in specific and measurable terms, the long-term evidence of practicing this alignment.
  • Help. Ask each member of your group for help. They help by giving the response you would like when you give your signal that you are practicing your alignment.

Commitments

  • Identify an alignment that will result in your personal change and require no change from any other person.
  • Identify blocks and wants that are specific and personal.
  • Identify blocks that, if solved, would radically increase your effectiveness in life, work, and play.
  • Choose a virtue that is about you and preferably one word long. For example: integrity, passion, self-care, peace, fun.
  • Ask for help from people who know you and/or know alignments.
  • Identify evidence that is measurable by an objective third party.

Notes

  • The most popular personal alignments are “I want (Integrity, Courage, Passion, Peace, Self-Awareness or Self-Care)”.
  • If you are struggling with figuring out what you want, adopt the alignment “I want self-awareness.” There is no case where increased self-awareness would not be beneficial.
  • A personal block is something you find within yourself. It does not refer to circumstances or other people. Assume that you could have had what you want by now, that your block is a myth that somehow deprives you of your full potential.
  • Ideally, identify both immediate and long-term evidence of your alignment. Write down results that start now (or very soon), as well as results you’ll see at least five or more years in the future.
  • As a default signal, tell your teammates or others who are close to you that you are working on your alignment when you are practicing it. If they don’t know the protocol, just tell them what virtue you are working on and ask for their help.
  • When members of a team are completing their personal alignments together (asking each other for help), the final step of the process is most powerful if done as a ceremony.

Investigate

Investigate allows you to learn about a phenomenon that occurs in someone else. Use it when an idea or behavior someone is presenting seems poor, confusing, or simply interesting.

Steps

  • Act as if you were a detached but fascinated inquirer, asking questions until your curiosity is satisfied or you no longer want to ask questions.

Commitments

  • Ask well-formed questions.
  • Ask only questions that will increase your understanding.
  • Ask questions only if the subject is engaged and appears ready to answer more.
  • Refrain from offering opinions.
  • Do not ask leading questions where you think you know how he or she will answer.
  • If you cannot remain a detached, curious investigator with no agenda, stop using the protocol until you can come back to it and keep these commitments.

Notes

  • Do not theorize about the subject or provide any sort of diagnosis.
  • Consider using the following forms for your questions:
  • What about X makes you Y Z?
  • Would you explain a specific example?
  • How does X go when it happens?
  • What is the one thing you want most from solving X?
  • What is the biggest problem you see regarding X now?
  • What is the most important thing you could do right now to help you with X?
  • Ineffective queries include the following:
  • Questions that lead or reflect an agenda.
  • Questions that attempt to hide an answer you believe is true.
  • Questions that invite stories.
  • Questions that begin with “Why.”
  • Stick to your intention of gathering more information.
  • If you feel that you will explode if you can’t say what’s on your mind, you shouldn’t speak at all. Consider checking your intention or Check Out.

Source: Online « The McCarthy Show

Design for a self-regenerating organisation – Geoghegan and Pangaro (Semantic Scholar)

Design for a self-regenerating organisation

Ashby’s 1952 work Design for a Brain comprises a formal description of the necessary and sufficient conditions for a system to act ‘like a brain,’ that is, to learn in order to remain viable in a changing environment, and to ‘get what it wants’. Remarkably, Ashby gives a complete, formal specification of such a system without any dependency on how the system is implemented. Here the authors argue how Ashby’s formalisms can be applied to human organizations. In business terms, this provides the ability to initiate specific investments and to track convergence on desired business outcomes. No other methodology for organizational change known to the authors has the formal logic or prescriptive power as this application of Ashby’s work. Through such interpretations—as rigorous as the application of Design for a Brain to mechanical systems—Ashby’s formalism enables the derivation of the necessary and sufficient conditions for a corporation to remain viable in a changing market. The authors claim that the only means for an organization to change from the inside and by design is through the creation and protection of processes that recognize the limits of present language and engender the continual introduction of new ones

Source: Design for a self-regenerating organisation – Semantic Scholar

Complexity Theory and Organization Science – Semantic Scholar

Complexity Theory and Organization Science

Complex organizations exhibit surprising, nonlinear behavior. Although organization scientists have studied complex organizations for many years, a developing set of conceptual and computational tools makes possible new approaches to modeling nonlinear interactions within and between organizations. Complex adaptive system models represent a genuinely new way of simplifying the complex. They are characterized by four key elements: agents with schemata, self-organizing networks sustained by importing energy, coevolution to the edge of chaos, and system evolution based on recombination. New types of models that incorporate these elements will push organization science forward by merging empirical observation with computational agent-based simulation. Applying complex adaptive systems models to strategic management leads to an emphasis on building systems that can rapidly evolve effective adaptive solutions. Strategic direction of complex organizations consists of establishing and modifying environments within which effective, improvised, self-organized solutions can evolve. Managers influence strategic behavior by altering the fitness landscape for local agents and reconfiguring the organizational architecture within which agents adapt. (Complexity Theory; Organizational Evolution; Strategic Management) Since the open-systems view of organizations began to diffuse in the 1960s, comnplexity has been a central construct in the vocabulary of organization scientists. Open systems are open because they exchange resources with the environment, and they are systems because they consist of interconnected components that work together. In his classic discussion of hierarchy in 1962, Simon defined a complex system as one made up of a large number of parts that have many interactions (Simon 1996). Thompson (1967, p. 6) described a complex organization as a set of interdependent parts, which together make up a whole that is interdependent with some larger environment. Organization theory has treated complexity as a structural variable that characterizes both organizations and their environments. With respect to organizations, Daft (1992, p. 15) equates complexity with the number of activities or subsystems within the organization, noting that it can be measured along three dimensions. Vertical complexity is the number of levels in an organizational hierarchy, horizontal complexity is the number of job titles or departments across the organization, and spatial complexity is the number of geographical locations. With respect to environments, complexity is equated with the number of different items or elements that must be dealt with simultaneously by the organization (Scott 1992, p. 230). Organization design tries to match the complexity of an organization’s structure with the complexity of its environment and technology (Galbraith 1982). The very first article ever published in Organization Science suggested that it is inappropriate for organization studies to settle prematurely into a normal science mindset, because organizations are enormously complex (Daft and Lewin 1990). What Daft and Lewin meant is that the behavior of complex systems is surprising and is hard to 1047-7039/99/1003/0216/$05.OO ORGANIZATION SCIENCE/Vol. 10, No. 3, May-June 1999 Copyright ? 1999, Institute for Operations Research pp. 216-232 and the Management Sciences PHILIP ANDERSON Complexity Theory and Organization Science predict, because it is nonlinear (Casti 1994). In nonlinear systems, intervening to change one or two parameters a small amount can drastically change the behavior of the whole system, and the whole can be very different from the sum of the parts. Complex systems change inputs to outputs in a nonlinear way because their components interact with one another via a web of feedback loops. Gell-Mann (1994a) defines complexity as the length of the schema needed to describe and predict the properties of an incoming data stream by identifying its regularities. Nonlinear systems can difficult to compress into a parsimonious description: this is what makes them complex (Casti 1994). According to Simon (1996, p. 1), the central task of a natural science is to show that complexity, correctly viewed, is only a mask for simplicity. Both social scientists and people in organizations reduce a complex description of a system to a simpler one by abstracting out what is unnecessary or minor. To build a model is to encode a natural system into a formal system, compressing a longer description into a shorter one that is easier to grasp. Modeling the nonlinear outcomes of many interacting components has been so difficult that both social and natural scientists have tended to select more analytically tractable problems (Casti 1994). Simple boxes-andarrows causal models are inadequate for modeling systems with complex interconnections and feedback loops, even when nonlinear relations between dependent and independent variables are introduced by means of exponents, logarithms, or interaction terms. How else might we compress complex behavior so we can comprehend it? For Perrow (1967), the more complex an organization is, the less knowable it is and the more deeply ambiguous is its operation. Modem complexity theory suggests that some systems with many interactions among highly differentiated parts can produce surprisingly simple, predictable behavior, while others generate behavior that is impossible to forecast, though they feature simple laws and few actors. As Cohen and Stewart (1994) point out, normal science shows how complex effects can be understood from simple laws; chaos theory demonstrates that simple laws can have complicated, unpredictable consequences; and complexity theory describes how complex causes can produce simple effects. Since the mid-1980s, new approaches to modeling complex systems have been emerging from an interdisciplinary invisible college, anchored on the Santa Fe Institute (see Waldrop 1992 for a historical perspective). The agenda of these scholars includes identifying deep principles underlying a wide variety of complex systems, be they physical, biological, or social (Fontana and Ballati 1999). Despite somewhat frequent declarations that a new paradigm has emerged, it is still premature to declare that a science of complexity, or even a unified theory of complex systems, exists (Horgan 1995). Holland and Miller (1991) have likened the present situation to that of evolutionary theory before Fisher developed a mathematical theory of genetic selection. This essay is not a review of the emerging body of research in complex systems, because that has been ably reviewed many times, in ways accessible to both scholars and managers. Table 1 describes a number of recent, prominent books and articles that inform this literature; Heylighen (1997) provides an excellent introductory bibliography, with a more comprehensive version available on the Internet at http://pespmcl.vub.ac.be/ Evocobib. html. Organization science has passed the point where we can regard as novel a summary of these ideas or an assertion that an empirical phenomenon is consistent with them (see Browning et al. 1995 for a pathbreaking example). Six important insights, explained at length in the works cited in Table 1, should be regarded as well-established scientifically. First, many dynamical systems (whose state at time t determines their state at time t + 1) do not reach either a fixed-point or a cyclical equilibrium (see Dooley and Van de Ven’s paper in this issue). Second, processes that appear to be random may be chaotic, revolving around identifiable types of attractors in a deterministic way that seldom if ever return to the same state. An attractor is a limited area in a system’s state space that it never departs. Chaotic systems revolve around “strange attractors,” fractal objects that constrain the system to a small area of its state space, which it explores in a neverending series that does not repeat in a finite amount of time. Tests exist that can establish whether a given process is random or chaotic (Koput 1997, Ott 1993). Similarly, time series that appear to be random walks may actually be fractals with self-reinforcing trends (Bar-Yam 1997). Third, the behavior of complex processes can be quite sensitive to small differences in initial conditions, so that two entities with very similar initial states can follow radically divergent paths over time. Consequently, historical accidents may “tip” outcomes strongly in a particular direction (Arthur 1989). Fourth, complex systems resist simple reductionist analyses, because interconnections and feedback loops preclude holding some subsystems constant in order to study others in isolation. Because descriptions at multiple scales are necessary to identify how emergent properties are produced (Bar-Yam 1997), reductionism and holism are complementary strategies in analyzing such systems (Fontana and Ballati ORGANIZATION SCIENCE/Vol. 10, No. 3, May-June 1999 217 PHILIP ANDERSON Complexity Theory and Organization Science Table 1 Selected Resources that Provide an Overview of Complexity Theory Allison and Kelly, 1999 Written for managers, this book provides an overview of major themes in complexity theory and discusses practical applications rooted in-experiences at firms such as Citicorp. Bar-Yam, 1997 A very comprehensive introduction for mathematically sophisticated readers, the book discusses the major computational techniques used to analyze complex systems, including spin-glass models, cellular automata, simulation methodologies, and fractal analysis. Models are developed to describe neural networks, protein folding, developmental biology, and the evolution of human civilization…

Source: Complexity Theory and Organization Science – Semantic Scholar

Cybernetics and Second-Order Cybernetics – Francis Heylighen (Semantic Scholar)

Cybernetics and Second-Order Cybernetics

It seems ‘semantic scholar’ is a bit of a treasure trove – full pdfs available

Source: Cybernetics and Second-Order Cybernetics – Semantic Scholar