Intelligent Swarming Insights Workshop · 2015-11-06 · • People assigned to “swarm team” for one week a month • Five years of experience and many, many iterations on the

11/12/14

© 2014 Consortium for Service Innovation 1

Intelligent Swarming ��Insights Workshop

Greg Oxton and Melissa George Consortium for Service Innovation

www.serviceinnovation.org [email protected]

[email protected]

Workshop Agenda

Intelligent Swarming Insights •  Welcome and objectives •  Intelligent Swarming Overview •  Who is doing Intelligent Swarming? Case Studies •  Is it right for your organization? •  Critical enablers •  Adoption considerations •  Indicators of success and baseline measures •  Summary and close

2 © 2014 Consortium for Service Innovation

Consortium Members

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Consortium’s Work ��The Five Initiatives

Consortium’s Work

KCS v6

Intelligent Swarming

Social Media and Support

Leadership Framework for

Service Excellence

Customer Success Initiative


Introductions

• Name •  Company •  Responsibilities • What is your experience/observations about

collaboration? • What questions do you have about Intelligent

Swarming?


Intelligent Swarming ��Overview

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“Most people work just hard enough not to get fired…

and get paid just enough money not to quit.”

- George Carlin


The Problem/Opportunity:

• 70% of the workforce is “dis-engaged” with the purpose, intent of the businesses they work for (Zuboff, Forbes)

• Companies use less than 40% of the skills they employ (Gallop, StrengthsFinder research)


Intelligent Swarming: Objectives

§  Skills development §  Dynamically create capability and capacity

§  Optimize people’s ability to contribute (create value) §  Increase engagement and loyalty

§  For customers and employees! §  Improve customer success and realized value through

improved problem solving, by increasing: §  Reach (an unbounded network) §  Relevance (based on profiles and reputation) §  Diversity (to increase creativity and innovation)

Every interaction is an opportunity to improve the relevance of the next interaction!


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The Shift…. The Current Model

Streaming

–  Silos and hierarchies –  Directed –  Predefined, linear process –  Escalation based –  Measure activity

The Emerging Model Intelligent Swarming

–  Network –  Opt-in –  Emergent, loopy processes –  Collaboration based –  Measure value creation

Level 1

Level 2

Level 3


•  People naturally collaborate on new issues (swarm)…

•  …often in spite of the support processes and structure.

•  Can we optimize collaboration?

Realization

© 2014 Consortium for Service Innovation

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What’s Different ��About Swarming?

•  Support organization functions as a single team of people with various skills who collaborate on resolving requests –  No level 1/2/3 –  No escalations within support

•  The first person to take the request should be the most likely person to be able to resolve it (intelligent matching)

•  The person who takes the request owns it until it is resolved –  Eliminate queue bouncing –  Improve learning and skills transfer

•  Support Analysts can find the best available person to help •  Support Analysts can see work that is relevant to them •  Measuring the creation of value (not activity) by individuals and

teams •  Managers as coaches – not judges and not “owners” of the teams


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How Does it Work?

•  Variety of ways to facilitate collaboration •  Some common themes:

•  Requires engaged and aligned people •  Incident/case/request ownership is clear •  Best if designed by the people using the process •  Iterating on the process (continuous improvement) •  People profiles and reputations are a key enabler •  Same “taxonomy” for work, people, and content •  Exception detection and management •  Performance assessment: from activity to value


Definition of Collaboration

Collaboration is a process defined by the recursive interaction of knowledge and mutual learning between two or more people who are working together in an intellectual endeavor toward a common goal which is typically creative in nature. Collaboration does not necessarily require leadership and can even bring better results through decentralization and egalitarianism (from Wikipedia) For our purposes – not sure it has to be “intellectual endeavor,” could be a physical endeavor?


A Few Definitions


• The group of people who could benefit from interaction

A Collaboration Group

• Two or more people working to resolve a request

A Swarm

• “Work is work”, efficiently resolving requests is the goal

Work

•  Facilitating the connections between people with increasing relevance over time


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Who is Doing Intelligent Swarming?

Case Studies:��Early Adopter Experience

Early Adopters Implementation Spectrum of Automation

Mostly Manual

Highly Automated

BMC Red Hat Microsoft

and

Cisco PTC

For case studies, visit www.serviceinnovation.org/intelligent-swarming

Sage


Early Adopters: Results

•  Improved Resolution –  Reduction in call backs –  Reduction in time to resolve –  Handled more cases with fewer headcount (through attrition) –  Resolved multi-technology issues more quickly

•  Support Analysts Love It –  Increased employee satisfaction/loyalty/engagement –  Skills growth, accelerated learning –  Backlog down dramatically –  Reduced new hire training time by up to 50%

•  Customers Love It –  Better customer experience, focused on customer success and value

realization –  Dramatically increased customer satisfaction numbers –  A better way to deliver on company’s brand promise


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•  BMC •  Red Hat •  Microsoft •  Cisco •  Sage

BMC

•  One product group – 60 support agents, across multiple locations

•  People assigned to “swarm team” for one week a month •  Five years of experience and many, many iterations on

the process •  Two swarm teams, three people each

–  New case assessment –  Severity 1s (critical situations)

•  Goal of the “swarm” –  Can we solve it quickly – Is it a known issue? –  What additional information is needed? –  Who is the best person to take the lead?


BMC Results

•  Support engineers love it –  “I don’t feel alone anymore!” –  “I am not constantly interrupted with sev 1s!” –  “I have learned more in the past year by swarming

than in my five years prior.” (Level 3 engineer)

•  Backlog down dramatically •  Reduced new hire training time by 50% •  Customers love it

–  Customer sat for this team went from the lowest at BMC to the highest!


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Red Hat

•  S&P 500 Enterprise software company •  Platform, middleware, and cloud product lines

•  Open software support: Linux, Apache….

• Global Support Service operates 24/7 in 16 countries and 9 languages

•  Complex technical questions often consultative in nature


Red Hat - Swarming

Goal: Get the right resources on cases as quickly as possible with as few touches as possible.

•  Solve issues faster •  Remove the overhead of ticket

escalation •  Make it easier for engineers to

collaborate •  Allow people to focus on their

areas of interest and expertise


Red Hat��Old Process: an Escalation Model

Cases

Cases

Cases

•  People could only see cases in the queue(s) they were assigned to

•  Once someone took a case it was not visible to others

•  If Level 1 could not solve the issue, they escalate the case to level 2

•  People worked independently

Level 1

Level 2

Level 3


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Red Hat��Old Process

Cases Cases Cases

Cases Cases

Cases

Cases

Cases

And, cases were managed in product silos.

Product Silos


Red Hat Vision


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Red Hat��New Process: a Collaboration Model

Case

Case Case

Case

•  People can see all the cases relevant to their skills and interests

Owner Assist

•  People take ownership for cases

•  Others can contribute (opt-in) to the resolution of any open case

•  People can request help from others in developing resolutions

•  Exception management

•  People collaborate on solving customer issues


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Red Hat Implementation

Critical functions

•  Views: Knowing what to work on

•  Tags: Enable unique views

• Notifications: Workflow management

•  Service Entitlement: Prioritize work

•  Reports: Is the ship on course?


•  Increase Visibility •  Increased Relevance of

Collaboration •  Nurturing the Technical

Communities •  Outcome: •  Faster resolution, which

drives CSAT and loyalty •  Skills transfer and

continuous learning

Red Hat��Benefits


Microsoft

•  10,000+ support agents worldwide •  Instant messaging system helps agents find known

issues and/or others who can help –  Integrated KB search into IM

•  People profiles: experience, reputation, availability, interests –  Rich and automated, based on the content the individuals has

worked on/used recently (60-90 days) –  Integrated with messaging system and case management

•  System collects feedback from those who receive assistance which updates providers profile


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Cisco – TechZone��“Play Catch, Not Ping Pong”

•  3500 Support Engineers (globally) •  1500 Partner Support Engineers (outsourced) •  Problem solving and collaboration system is designed by

support engineers, for support engineers •  3-4 years of experience •  Engineer skills development is top priority •  “The first person to work on the issue is the person most

likely to resolve it.” •  Robust business rules and people profiles to prioritize and

match work to people –  Match case to best available resource to resolve –  Raise my hand: I need help –  Offer help: visibility to cases relevant to me and offer help


Cisco��Benefits

•  Skills growth, accelerate learning •  Customer success and value realization

•  Better customer experience = 7%+ in customer sat •  A better way to deliver on our brand promise

•  Improved resolution •  27% reduction in call backs •  40% reduction in time to resolve •  Handled 300K more case fewer headcount (attrition)

•  Resolve multi-technology issues more quickly •  Improve employee satisfaction/loyalty/engagement


Sage

•  Starting with 2 pilot groups who where already had a culture of collaboration

•  Enabled collaboration through a status change in workforce management tool and existing Jabber tool

•  Preliminary results, show analysts like it •  Lesson learned: Communicate pilot to those

not involved, especially middle management


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Early Adopters:��Lessons Learned

•  Don’t over engineer the process or the tool –  The people doing collaboration should be the ones to design and

own the process

•  Culture change –  It’s ok to ask for help (Support Analysts, managers) –  Balance of individual outcomes and team outcomes –  1st and 2nd line managers must shift mindset

•  Consistency and communication –  Hearing vs experiencing (internalizing) –  Rate of change made it hard to keep everyone informed

•  Collaboration –  Not all issues are worthy of collaboration: 60-70% issues solved

with initial swarm (the customer and a Support Analyst)


Is Swarming Right ��for Your Organization?

Is Intelligent Swarming ��Right for Your Organization?

Some things to consider: •  Identify a collaboration group (people who would

benefit from shared experiences) •  Size of the collaboration group •  Location of the group members •  Group’s average work minutes to resolve (complexity) •  New vs. Known ratio •  % resolved at each level of support •  % of severity 1 and 2 issues •  Maturity and culture of the group


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Collaboration Health Spectrum��

Transactions Interactions Collaboration Teamwork

Distinguishing Characteristics

Engagement Weak Strong

Learning None Rich

Trust Low High

Structure/Roles Simplistic Dynamic


Tools for Assessing the ��Health of the Network

•  Collaboration Health Survey –  Structure –  Trust –  Conflict –  Commitment –  Accountability –  Results

• ONA (Organizational Network Analysis) –  Network map of who goes to who to solve issues


ONA Survey Questions

1. Please indicate the frequency each person below provides you with information you use to get work done.

Never Seldom Sometimes Often Very often (1-5) 2. I understand this person's skills and areas of expertise.

Strongly disagree Disagree Neutral Agree Strongly agree (1-5) 3. I would be more effective in my work if I were able to communicate with this person more.

Strongly disagree Disagree Neutral Agree Strongly agree (1-5) 4. What is each person's primary physical location in proximity to yours? Online Different country Different city Different building Different floor Same floor (1-6)


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Frequency each person below provides you with information you use to get work done.��


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Critical Enablers

Critical Enablers

Encouraging the Desired Behavior

Process and Policy Changes

Management Mindset

People Profiles

Tools and Integration


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Can Gamification Encourage The Desired Behaviors?

What is Gamification?��

Gamification is the use of game attributes to drive game-like player behavior in a non-game context with predictability

- Dr. Michael Wu, Lithium

Behaviors •  Engagement •  Learning •  Competition •  Awareness • Obsession •  Interaction


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Game Dynamics

•  Patterns of both the game and the players that make the game more enjoyable

•  Effectiveness depends on

the Bartle type –  Killer –  Socializer –  Explorer –  Achiever

•  Examples of Game Dynamics –  Progression

•  Leveling up/Unlocks –  Reinforcement schedule

•  Variable interval –  Appointments and

Countdowns –  Community rediscovery

•  Likes, Diggs, Mentions


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Gaming is Psychology,��Not Technology

•  Fogg’s Behavior Model (FBM) –  BJ Fogg - Persuasive Technology: Using Computers

to Change What We Think and Do.

•  Three Elements must converge at the same moment for a behavior to occur –  Motivation –  Ability –  Trigger


High Motivation

Ability Hard to do Easy to do

Mot

ivat

ion

BJ Fogg – Persuasive Technology: Using Computers to Change What We Think and Do www.behaviorModel.org

Fogg Behavioral Model: Convergence of Motivation,

Ability, and Trigger

Low Motivation


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Triggers fail here

Triggers succeed here

Three Elements Happening Simultaneously�� for Gamification to Drive Behavior

Motivation: Positive feedback, I want to do this, I understand the value Move from extrinsic to intrinsic, from Drive by Daniel Pink

Autonomy (Ownership and Productivity) Mastery (Set Completion, Leveling Up) Purpose (Quest, Meaning, Discovery)

Finding Flow by Mihaly Csikszentmihalyi Balance of challenge and skill = Flow Ability is context dependent, it is not the same for everyone, changes as skills develop

Ability: I can do this, I have access to the resources at the right time

Trigger: Call to action, told to, reminder

Good triggers are carefully timed to activate when the users have the motivation and ability

48 © 2014 Consortium for

Service Innovation

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High

Skill Low High

Cha

lleng

e

From “Finding Flow” By Csikszentmihalyi

Flow: Balance ��of Challenge and Skill


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Apathy

Arousal

Confidence

Anxiety

Relaxation Boredom

Worry

High

Skill Low High

Cha

lleng

e

From “Finding Flow” By Csikszentmihalyi

Flow

Flow . . .��Emotions


50

Example of Gamification to Influence Behaviors

•  Influence behavior towards a common purpose –  Stack Overflow Example

• Pro-Social behaviors –  Badges earned from things that are for the good of others

»  It is in everyone’s best interest to have quality knowledge content

–  Recognize and reward achievements –  No limit to the types and number of badges


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Other Ideas…

•  Create autonomy by giving choices –  Create their own badges and achievements

•  Create social dynamics by giving visibility to all contributors on the content –  Asks for likes –  Asks for mentions


Tenets of Gamification

•  Gaming is psychology, not technology •  Game mechanics are used to solve a problem or drive a behavior •  Game dynamics combine mechanics and player behaviors •  Actions happen when motivation, ability, and trigger converge •  Motivate by moving from extrinsic to intrinsic value •  Value and rewards vary by player and desired behavior •  Feedback is real-time, long-term, and changes over time •  Gamification is more effective and sustainable if:

–  Built on the community values –  Designed by the community –  Transparent to enable self-governance

•  Expect the game to change


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Designing A ��Collaboration Process

Key Questions for the Collaboration Process

• How are we going to get the best person on the request on the first touch? –  Providing visibility to relevant requests?

•  Request help – when someone needs help how do we find the best people to help them?

• Offer help – how do we allow people who can and are willing to help, to help?


Seven Process Scenarios

•  I need help (I have searched KB)

–  On a live call

–  Specific question –  I know who could answer it

•  I need help –  On a live call –  Specific question –  I don’t know who could

answer it

•  I need help –  On a live call –  I have no idea about how to

pursue resolution

•  I need help –  In research mode (off line) –  Don’t know who could help

•  I see a request for help –  How do I know someone is asking

for help in an area relevant to me –  How do I respond?

•  I see an incident/request (someone else has taken ownership for) that I know the answer to

–  How do I find the incident? –  How do I help?

•  How do I find or see open/available requests that are relevant to me?


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Promote or Inhibit Collaboration?

Current Practice Impact: Promote or Inhibit

Process and Policy •  Escalation rules •  Workforce Mgt, time on

queue •  Visibility to work

Structure •  Teams •  Tiers (L1, L2, L3) •  Geography

Measures •  Performance Measures •  Organizational Health •  Customer Focus

Tools •  Peer availability •  Interaction •  Queues •  Session History


Designing ��People Profiles

Why Do We Care About ��People Profiles and Reputation?

•  It is what makes swarming “intelligent” –  Information that enables relevance of interactions –  Learn from each interaction and improve the

relevance of the next interaction

•  Recognition of individual and team’s contribution and capabilities

•  A better way to assess individual and team contribution? (long term)


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Degree of understanding about the problem impacts the size of the potential audience ��

needed to fix it…

Understanding of the problem

Potential audience of relevant content or

people Small, little context

about the issue and requestor Large number of potential helpers

Potential audience

Understanding of the problem

Small number of potential helpers

Large, a lot of context about the issue and requestor

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Thoughts on Design Criteria

•  Support/encourage desirable behaviors and the success of the people doing the work

•  Alignment to the organization's purpose, mission, goals and values –  Purpose, mission, and goals describe what

we are trying to accomplish –  Values describe the boundaries of acceptable

behavior in how we accomplish it

•  For individuals and teams –  Teams should not be limited to the reporting

structure: some teams will be cross-functional and cross-geographical

My Skills & Interests

Company Goals

Magic happens here!


Queues and Tiers

Level 1

Level 3

Level 2

Development Engineering

Support Center

Compartmentalized roles and responsibilities limit people’s ability to contribute.

Queue

s

Tiers

Job


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The Crying Shame ��of Queues and Tiers

Job

A job description: skills and responsibilities. What people are expected and allowed to do.



Job


The scope of skills possessed by multi-talented human beings.

Assertion: standardized job descriptions utilize less than 50% of the talent and skill we employ.



Scope of skills possessed by multi-talented human beings is seldom a perfect fit.

Crazy assertion: standardized job descriptions force people into roles they aren’t good at.

Job



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Unbounded Contribution

Old contribution

Assertion: collaboration with unbounded contribution will yield faster, more creative solutions for new

problems, and happier employees.

Job New contribution


What’s Different?

Level 1

Level 3

Level 2


Support Center

Queue

s

Tiers




Key Questions:�� Implementing People Profiles

•  What would you (Support Analysts) like to know about others that would help you collaborate more effectively?

•  Ultimately … automation is required –  Level of detail required, tedious to maintain manually –  Self-declaration of skills is highly suspect

•  How do we capture “implicit” information about people’s skills and competencies? –  Recognize people for all the key competencies that they are good

at –  Key competencies –  Transferable skills and non-transferable skills

•  How do we capture feedback on the value created?


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Elements of People Profiles

•  My identity (static, explicit) –  Name, contact info, language(s), location

•  Interests (static, explicit) •  Preferences (dynamic, explicit, & implicit)

–  Modes of interaction (phone, email, chat) –  Roles (maven, connector, evangelist (from The Tipping Point) or

Support Analyst, consultant, marketing) –  Relationship – existing and positive, based on past interaction

•  About my competencies/skills (dynamic, explicit, & implicit) –  Subject mater domain expertise –  Soft/transferable skills, KM, CRM, customer interaction

•  Reputation (dynamic, explicit, & implicit) –  History of value created

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Managing Identity and Privacy��The Layers of the Profile

ME

My Identity

Reputation

Skills & Competencies

Interests

Preferences

Explicit

Implicit

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ME

My Identity

Reputation

Skills & Competencies

Interests

Preferences

Boundaries of Visibility Public

Company Team


Managing Identity and Privacy��The Layers of the Profile

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Importance of a ��“Common Taxonomy”

Work

Knowledge

People Offering

Customer Entity

Ability to relate Many to many


74

Importance of a ��“Common Taxonomy”

Market Segments Customer Roles Business Types Products SSB Owner/CEO/GM/President Construc4on & Real Estate Sage Fixed Assets SMB Accountant Farming, Natural Resource Mgmt & Xport Sage HRMS

MMB Office Management Government / Educa4on / Members-‐Community Sage 500 ERP

Controller Hospitality, Food and Beverage Sage ERP X3

CFO/Finance Legal/Insurance/Financial Ins4tu4on & Services Analy4cs

Other Manufacturing Sage 300 Construc4on and Real Estate

Management Other Sage 100 ERP Payroll Services Sage 100 Contractor

IT Transporta4on / Distribu4on Sage BusinessWorks Accoun4ng

Opera4ons Wholesale / Retail Sage 300 ERP

Human Resources Sage BusinessVision Accoun4ng

Sales Sage PFW ERP Others Sage CRM Sage 300 Trade Specialty

Sage Construc4on Anywhere

Sage Pro ERP Sage 50 U.S. EdiGon Sage 50 Canadian Edi4on Sage Timeslips


Importance of a ��Common Taxonomy

•  In how we classify work, cases, knowledge, and people –  A common taxonomy links people to content (for

known issues) and people to people (for new issues)

•  The challenge of how much detail –  How do we decide how much detail to put into

profiles? –  Not enough detail won’t enable the necessary level

of relevance, but too much detail creates unnecessary noise and irrelevant data


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Skill or Competency Levels

• What are the key skills/competencies for support that would facilitate collaboration?

• How many levels for each skill? Three? Five? –  Gold, Silver, Bronze –  Master, Expert, Novice –  Black Belt, Green Belt, Yellow Belt


Transferable and ��Non-Transferable Skills

•  Transferable skills –  Soft skills –  Skills that are valuable independent of the product/

technology being supported

• Non-transferable skills –  Product specific

• How products work

–  Technology specific •  Languages or protocols


Examples of Transferable Skills

•  Customer interaction skills –  Verbal, Written –  Customer empathy

•  Problem solving –  Critical thinking –  Kepner-Tregoe problem solving technique

•  Process and procedures –  Case management –  Knowledge management (KCS Certified)

•  Time management •  Project management


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Examples of Non-Transferable Skills

• Non-transferable skills (product specific) –  Programing languages, reading/writing code (Java,

PHP, C) –  Platforms/OS (Linux, Windows, Mac) –  Protocols and architectures (TCP/IP, FTP, SQL,

HADOOP) –  Product specific

• Product components/functionality


The Challenge of ��How Much Detail?

• How do we decide how much detail to put into profiles? –  Not enough detail won’t enable the necessary level

of relevance, but too much detail creates unnecessary noise and irrelevant data


Indicators of Success

Baseline Measures Progress

Value Creation

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Indicators of Success of Swarming

•  First contact resolution •  Reduced call back rate •  Lower work in progress •  Average time to resolve •  Average handle time (work min) •  Employee sat (ONA, Organization Network

Analysis) •  Fewer customer escalations •  Contact/customer/month


Indicators of Value Creation ��for Individuals Who Are Swarming

•  Frequency of use of analysts expertise (how often do we go to them?) ONA

•  How long to ask for help (case open to raise hand) –  Manual process to track for a period of time?

•  Frequency of requests help from anyone •  Time to respond – how long for individual to respond •  Who responded •  Un-answered requests •  Feedback from recipient of help feedback from

provider of help •  Ask for help from a specific person •  Unsolicited offers of help


Adoption Considerations Assess

Design Implement

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Intelligent Swarming�� Workshop and Design

•  Phase I: Initial Qualification –  Online questionnaire to assess relevance

•  Phase II: Organizational Analysis –  Conference calls, ONA and collaboration health surveys, data

analysis, understanding the brand promise

•  Phase III: Adoption Planning and Design –  3-5 day workshop and design session, onsite, heavy

participation by Support Analysts/engineers

•  Phase IV: Adoption Support –  6-9 months of ongoing support (conference calls)

•  Offered by the Consortium for Service Innovation


Adoption

•  Start with a pilot (identify a collaboration group) –  Collaboration Health Survey –  ONA

•  Let the Support Analysts design the process –  Triggers, ability, motivation for seven scenarios

•  Iterate on the process •  Start with manual process and refine your

requirements based on that experience –  People profiles –  Measures


Technology Considerations

•  Ability to see all incidents/cases/work that are relevant to me –  From any queue –  Owned or available

•  Ability to request help - raise my hand •  Ability to ask a specific person or small group of people

a question •  Ability to join groups •  Ability to see and respond to requests for help that are

relevant to me •  Ability to offer unsolicited help


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Technology Considerations (continued)

•  Ability to see others’ availability, status •  People profiles

–  Reflect my skills, interests, preferences, reputation

•  Ability to see open requests for help and aged requests for help –  Configurable by team

•  Options on how to connect •  Ability to create unique, separate “collaboration

space” for two or more people to work on an issue


Technology Considerations��(continued)

•  To support measurements: –  Time: incident open to request help –  Frequency of requesting help –  Frequency of offering help: unsolicited and requested –  Frequency of being requested (by name) –  Unanswered requests –  Feedback from requestor about the help received –  Feedback from the provider about the requestor –  Who is interacting with who and how often (input to

ONA)


Summary

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Emerging Principles

•  Alignment with the needs of the people doing the work AND alignment with the purpose and goals of the organization –  Sweet spot - Intersection of employee’s skills and interests with the

company goals and objectives •  Promotes collaboration (not competition - I can only win if you lose) •  Recognize diversity of skills/competencies (lots of them), all that are

required to be successful •  Leverage the principles of:

–  Motivation elements of: accomplishment, recognition, interesting work (Hertzberg), mastery, autonomy (“Drive” Pink)

–  Flow: balancing skill and challenge (“Finding Flow” Csikszentmihalyi) •  Develop reputation through implicit means (people's behavior) rather

than by explicit means (surveys and people's feedback) (Marc Smith) •  Based on abundance not scarcity


Critical Success Factors

•  Culture of collaboration •  Engagement in, alignment to the purpose/

brand promise and the values of the company • New indicators of organization health and

value creation •  Transformation of Management’s role

–  1st and 2nd line managers as coaches –  Executive expectations (measures)


A Good Outcome

•  An understanding of Intelligent Swarming concepts •  A summary of case studies

–  Benefits and lessons learned from the early adopters

•  Details on the qualification criteria –  Swarming is not for everybody

•  Insight to the critical key enablers –  Culture shift –  Seven scenarios to consider in designing the process –  Tool functionality and integration requirements –  Change management (especially for 1st & 2nd line managers)

•  Understanding of the measures of success


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For more information, please contact Greg Oxton, Executive Director

Consortium for Service Innovation [email protected]

Melissa Geroge, Program Director [email protected]

•  Drive: The Surprising Truth About What Motivates Us by Daniel Pink

•  Transforming Performance Measurement by Dr. Dean Spitzer

•  The Five Dysfunctions of a Team: A Leadership Fable by Patrick Lencioni

•  The Wisdom of Crowds by James Surowiecki

•  The Medici Effect: What You Can Learn from Elephants and Epidemics by Frans Johansson

•  Group Genius: The Creative Power of Collaboration by Keith Sawyer

•  Wikinomics: How Mass Collaboration Changes Everything by Don Tapscott and Anthony Williams

•  The Only Sustainable Edge: Why Business Strategy Depends On Productive Friction And Dynamic Specialization by John Hagel III and John Seely Brown

•  The Support Economy: Why Corporations Are Failing Individuals and the Next Episode of Capitalism by Shoshana Zuboff and James Maxmin

•  The Future of Knowledge by Verna Allee


References

101

Documents

Intelligent Swarming Insights Workshop · 2015-11-06 · • People assigned to “swarm team” for one week a month • Five years of experience and many, many iterations on the