what nature can teach us about building great teams · pdf filewhat nature can teach us about...

Tom Perry

Dhaval Panchal

What Nature Can Teach Us About

Building Great Teams

Introductions� Tom Perry

� Dhaval Panchal

What Nature Can Teach Us About Building Great Teams2

Tom Perry

What Nature Can Teach Us About Building Great Teams

� Scrum Master with CyberSource

� Lead, facilitated, and followed many agile teams in a diverse array of industries

� Background in psychology, software development, project management (PMP), Big Game Hunting

Blog: agiletools.wordpress.comTwitter: tlperryEmail: [email protected]

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Dhaval Panchal� Agile consulting team at SolutionsIQ� Certified Scrum Trainer� Background in Development, Business and Functional Analysis, Organizational Change, Project Management and Business Intelligence

� Trained and coached Scrum project teams during enterprise rollouts from Fortune 10 to mid-sized product companies

Blog: http://dhavalpanchal.gettingagile.comTwitter: dhavalpanchalEmail: [email protected]

4What Nature Can Teach Us About Building Great Teams

The Back Story


Linda Rising - Are Agilists the Bonobos

of Software Development?


The Other BonabeauEric Bonabeau

� Swarm Intelligence: A Whole New Way to Think About Business, Harvard Business Review


Swarming – The Birds and the Bees

and Agile

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James SurowieckiThe Wisdom of (Agile) Crowds


Our Ideas Have Evolved!

Business WorldBusiness WorldBusiness WorldBusiness World Natural WorldNatural WorldNatural WorldNatural World

� Time Frame: ~200 years

� Population: Humans

� Rate of Change: Relatively Fast

� Millions of years

� All species

� Slow (punctuated by rapid changes)

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Our mission� Find Common Patterns in Great Teams in Nature

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Themes� Self Organization

� Emergence

� Decision Making

� Maturity


Self Organization

Self Organization – a Definition

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“Self-organization is a dynamical and adaptive process where systems acquire and maintain structure themselves, without external control.”

Tom De Wolf and Tom Holvoet,

“Emergence Versus Self-organization: Different Concepts but Promising When Combined”

What Nature Can Teach Us About Building Great Teams

The Goose Suit


The Cow Suit


Geese� Collective Leadership

� One Way Transfer of Information


One Way Transfer of Information� Opportunities

� Threats


One Way Group Broadcast� Characteristics of Pheromone Signaling (Thompson):

� Broadcast and Individual� 1 Way� Whole Species (permission free)� Simple Vocabulary (LOL)� Intra & Interspecies (bogus messages)� Robust Delivery� Low Energy� Longevity Potential� Message Range (rings)� Multi-Channel (redundancy)� Quick & Slow response (releaser/primer)� Anonymity of Sender� Location Information


Human One Way Transfer of

Information


Commands vs. Information Bursts� Commands often take longer to assemble

� Commands often require additional context

� Commands often require a reply

� “Roger” vs. “Wilco”


Team Vital Signs� Identify the threats and opportunities for the team

� Use these items to help the team recognize important signals


Team Tools: The Working Agreement


� Shared team values

� Threats/Opportunities

� List of rules the team agrees to work by

� Supports negative feedback

Macaques� Transfer of learning

� Monkey see, Monkey do…


Good Teams Need both Strong and

Weak Ties

� Teams with strong ties are generally good at getting things done (strong intra team connections), but not so good at listening to other teams

� Teams with weak ties are good at creating “Hubs” of connections, technical, social and organizational. However they are not so good at getting things done…


My Smiling Chimps


What Works for Chimpanzees

� Strict Hierarchy

� Constantly reinforcingsocial networks (i.e. grooming, etc.)

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The Wily Wapiti


Wapiti Wisdom� One Way Communication

� Democracy

� Herd Defense


Self Organizing Teams are Driven…� Self-organizing teams depend on a participants ability to discover an attractive subject that they are passionate about. Something they are so passionate about that they want to share it with others.


Summary� Collective Leadership

� One way transfer of information

� Transfer of Learning

� Reinforcing networks


Emergence

My Creative Rats


What is a CAS?A Complex Adaptive System (CAS) is a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents.

-John H. Holland


Examples of CAS:� Stock Exchanges

� The Immune System

� Cities

� Consciousness

� Swarms!


Properties of CAS (Swarms)� There are properties of CAS that impact swarming behavior. These properties include:1. Aggregation

2. Tagging

3. Non-Linearity

4. Flows(feedback loops)

5. Diversity

6. Models

7. Building Blocks

-John H. Holland


TaggingThere are three kinds of recognition in nature:

� Species recognition

� Kin recognition

� Individual recognition


Slime Mold


Slime Mold Life Cycle


Headline: Slime Solves Maze!


The Slimy Solution


Ants


Foraging LogicHow do ants find the shortest path to the best food source?Argentine ants (Linepithema humile)Simple Rules:Lay pheromone (chemical substance).Follow trail of others.Emergent Behavior:Colony is able to find the shortest path to food source.Ants forage out of nest for food source, marking their trails with pheromone. The ant that took the shorter path returns first and its trail will be marked with twice as much pheromone. Other ants in the nest will be attracted to the shorter path because of higher concentration of pheromone. As more and more ants take that route, they too lay pheromone, further amplifying the attractiveness of the shorter trail.Suggested s/w dev application: Use frequency of successful builds as indicator to progress towards further addition of features.


The Down Side of Pheromones: The

Circular Mill


SpecializationHow do ants allocate workers to different tasks?Red harvester Ants (Pogonomyrmex barbatus) in Arizona Desert.

Colony calculates each morning how many workers to send out foraging for food. The number can change, depending on conditions. Have foragers recently discovered a bonanza of tasty seeds? More ants may be needed to haul the bounty home. Was the nest damaged by a storm last night? Additional maintenance workers may be held back to make repairs.Simple rules:

When one ant bumps into another ant, it sniffs with its antenna to find out if the other belongs to the same nest; AND where it has been working. (Ants communicate by touch and smell. Ants that work outside the nest smell different from those that work inside.) Use rate of encounter with patrollers to tell if its safe to go out.


Summary� CAS

� Tags

� Foraging

� Pheromone Communication

� Specialization


Decision Making

The Laughing Zebra & The Hat


The Lesson� Tom is dumber than a Zebra


Bees


How the Hive Mind WorksIn late spring, when a hive gets too crowded, a colony normally splits, and the queen, some drones, and about half the workers fly a short distance to cluster on a tree branch. There the bees bivouac while a small percentage of them (scouts) go searching for new real estate.

Simple Rules:Seek diversity of optionsEncourage a free competition among ideasUse an effective mechanism to narrow choices

Emergent Behavior:

Scout bees search for nesting site. When they return to the swarm, each performs a waggle dance urging other scouts to take a look. (These dances include a code giving directions to a box's location.) The strength of each dance reflects the scout's enthusiasm for the site. After a while, dozens of scouts are dancing their little feet off, some for one site, some for another, and a small cloud of bees is buzzing around each site option.

As soon as the number of scouts visible near a site reaches about 15—a threshold confirmed by experiments—the bees at that box sense that a quorum has been reached, and they return to the swarm with the news.


Swarming is based on Simple Rules

� What simple rules do we have on our teams?


Team Swarming Exercise


� Dynamic Triangle Exercise

You A: Friend B: Enemy

B: EnemyA: Friend

You

S2

S2 DP: In v03 we did not have this exercise. If its okay with you, I'd like to reinstate this slide.SIQ, 7/25/2008

Swarm Intelligence


Critical Factors for Swarm Intelligence*

� Diversity

� Independence

� Decentralization

*James Suroweicki, The Wisdom of Crowds


Swarm Intelligence ProblemsThere are three kinds of problems that Swarm Intelligence addresses:

� Cognition (logical problems that can be solved)

� Coordination (require members of a group to coordinate their behavior)

� Cooperation (getting self-interested, distrustful, people to work together)

James Surowiecki, The Wisdom of Crowds


Winners and Losers…

“…what makes a system successful is its ability to generate lots of losers and then to recognize them as such and kill them off.”

-James Surowiecki, 2004, p. 29


Winners and Losers…

1/8/201158What Nature Can Teach Us About Building Great Teams

ORGANIC Team Behaviors� Outgoing – get to know your team colleagues

� Recruit – look out for new external partners to strengthen the team’s network

� Go! – network widely outside the team

� Ask – constantly ask for, and offer help to other team members

� Note – keep aware/abreast of issues of “team intelligence”

� Investigate – when you see something interesting, investigate it for the team

� Collaborate – join at least one team workgroup as an active member, don’t just be a “reviewer”

* Taken from “Bioteams” by Ken Thompson


Summary� Use one way group broadcast

� Take advantage of swarm intelligence

� Decentralize decision making

� Generate LOTS of winners and losers

� Use ORGANIC team behaviors


Maturity

Aggregation: The Lifecycle of a Swarm

� Ant Colonies show evidence of ‘maturity’� The average lifespan of a colony is 15 years

� The behavior of the colony changes over the lifespan of the colony� Early in the life of the colony, there are more conflicts with other ant colonies

� Later in the life of the colony, there are fewer fights with other colonies

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The Life Cycle of Nature’s Teams1. Founding- creating the right blend of team members to

survive/thrive

2. Ergonomic – focused on growth

3. Reproductive – spawning new teams

4. Terminal – “for most kinds of ants, old colonies die so that new colonies can be safely born.” - E.O. Wilson


Aggregation: The Lifecycle of a

Development Team

� The Tuckman model of team development suggests there are 4 canonical stages of team growth:� Forming

� Storming

� Norming

� Performing

� What other indicators are there of a team’s maturity?

Forming

Storming

Norming

Performing


Scaling Teams� The life cycle pattern suggests a similar pattern for agile adoption and scaling practices


Bee Hives Have Specific Events that

Initiate Swarming Behavior

� The birth of a new queen serves as a trigger for a swarming event

� What are the triggers for swarming behavior on development teams?� Project Initiation?

� Sprint Planning?

� High Priority Bugs?


Summary� Maturity affects the behavior of teams

� Teams have a life cycle

� Scaling teams can follow natural models


Conclusion

How Can We Apply This To Our Teams?1. Stop controlling – communicate information, not orders

2. Team Intelligence/Broadcast – Mobilize everyone to look for and manage team threats and opportunities

3. Grant Permission – Achieve accountability through transparency, not permission

4. Always on – Provide 24/7 instant message hotlines for all team members

5. Cluster – Nurture the teams internal and external networks

6. Swarm – Develop consistent autonomous team member behavior

7. Emerge – Scale naturally through nature’s universal growth and decay cycles

*Ken Thompson


Resources� The Wisdom of Crowds – James Suroweicki� Bioteams – Ken Thompson� Emergence – Steven Johnson� Micromotives and Macro Behavior –Thomas Schelling� The Starfish and the Spider: The Unstoppable Power of Leaderless Organizations – Ori Brafman and Rod Beckstrom

� Swarm Creativity – Peter Gloor� Swarm Intelligence: A Whole New Way to Think about Business – Eric Bonabeau and Christopher Meyer


Online Resourceshttp://www.bioteams.com/

http://www.systems-thinking.org/

http://www.calresco.org/themes.htm#pap

http://www.cenizal.com/?p=14

http://grant.robinson.name/projects/cellularAutomata/

http://ngm.nationalgeographic.com/ngm/0707/feature5/index.html

http://en.wikipedia.org/wiki/Swarm

http://www.jimhighsmith.com/pubs.html

http://www.mgtaylor.com/mgtaylor/jotm/spring97/flock.htm

http://www.openspaceworld.org/

http://mitpress.mit.edu/books/FLAOH/cbnhtml/slides.html

http://www.red3d.com/cwr/boids/

http://courses.washington.edu/gis203/index.html

http://developer.mugshot.org/wiki/Swarm_Effect

http://www.swarmcreativity.net/

http://www.ickn.org/

http://pespmc1.vub.ac.be/COMSELLI.html

http://www.sce.carleton.ca/netmanage/tony/swarm.html

http://www.nytimes.com/2007/11/13/science/13traff.html


Q&A


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