Operational process models for crisis management

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Operational process models for crisis management

• Prof. dr. T.J. Grant
• T 31 (0)76 52 73261 (Mon-Wed)
• M 31 (0)638 193 749
• TJ.Grant_at_nlda.nl

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Outline

• Goal
• To survey operational process models showing
  use as basis of IS architecture team
  organisation
• Structure
• Introduction
• Process models
• OODA SHOR Rasmussen PDCA
• Team models
• (Tea break)
• Rational reconstruction of OODA (OODA-RR)
• OODA-RR team organisation
• OODA-RR IS architecture
• OPERATION BEACH TOWEL (if time permits)
• Current future research

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Introduction myself

• Qualifications
• BSc Aeronautical Engineering Bristol UK
• Defence Fellowship (Masters) Brunel UK
• PhD Artificial Intelligence Maastricht NL
• Experience
• 1966-87 Royal Air Force officer UK SG
• 1987-2004 ICT consultant Atos Origin NL
• Dutch-French ICT company aerospace defence
  road traffic
• 2001-date Professor U. Pretoria ZA (20)
• Computer Science Department ICT for Planning
  Control
• 2004-date Professor NLDA Breda NL (50)
• Operational ICT Communications

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Introduction NLDA (1)

• NLDA Netherlands Defence Academy
• Mission
• Educate men women to become professional
  motivated officers in a dynamic military
  organization
• Scientific research in military focus areas for
  knowledge development education policy advice
• Ambition
• To become accredited as a university under
  European regulations in 2008-9

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Introduction NLDA (2)
Faculty Board Dean
Research office
Faculty office
International Security
SEWACO systems
Military Behavioural Sciences Philosophy
Military History General Strategy
Platform systems
Management Organisation Defence Economics
Navigation
Military Operations
Logistics Information
Military Sciences
Management Control Sciences
Technical Sciences
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Introduction architectural context
Operational needs impose requirements on
technical implementation
New ICTs make new types of operation possible
ICT Information Communications
Technology (i.e. IT communications)
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Process models (1) motivation

• Motivation for tutorial
• Seek commonalities across domains
• Military Command Control (C2)
• IS for crisis response management
• Process control
• (more)
• Construct scientific model for commonalities
• Operational process model is one of these
• Opens up possibilities
• Scientific exchange ideas across domains
• Operational enables across-domain
  interoperability
• Commercial enlarges market for COTS products

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Process models (2) examples
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Process models (3) examples
Combined Air Operations Center
Command Centre onboard frigate
Collaborative process
Army Command Post
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Process models (4) characteristics

• Complex real world in which
• Goals tasks ill-defined may conflict
• Situation changes over time
• Multiple players nobody in overall control
• Real-time loop between actions feedback
• High stakes
• Information uncertain ambiguous incomplete
• Decision makers have knowledge expertise
• Decision makers under time stress

Klein Klinger 1991
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Process models (5) definitions

• Command Control (C2)
• Command and control can be viewed as directing
  the process of operations by means of efficient
  and effective application of resources at hand in
  order to achieve a given mission
• C2 system
• An assembly of equipment methods and procedures
  and if necessary personnel that enables
  commanders and their staffs to exercise command
  and control
• N.B. Not just ICT but also people procedures
• C.f. DCMOTP factors
• Doctrine C2 Materiel Organization Training
  Personnel

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Process models (6) Controllers task
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Process models (7)

• What is a process model
• A model of thinking processes of decision-making
  team in crisis management operations
• Compare business process model
• Where do you find them
• Cybernetics literature
• Psychological literature
• Human supervisory control literature
• Organisation management theory
• Military C2 literature
• ISCRAM literature TIEMS

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Process models (8)

• What are process models useful for
• IS architecture (operational view)
• Organising decision-making team
• Selecting training team members
• (Self-) evaluation of team effectiveness
• Layout of control centre
• Data exchange standards protocols
• Providing infostructure

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Process models (9)

• History of process models
• Late 1970s / early 1980s
• Task-oriented process models
• At least 16
• All descriptive variants on the control loop
• From environment thru sensors control to
  actuators
• Each process model can be mapped to others
• Since 2000
• Flurry of interest in
• Applying task model to IS
• At least 6 all OODA-based
• Adding team / collaboration model
• At least 9

Mayk Rubin 1988
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Process models (10) theory
(Adapted from) Ashby 1963
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Process models (11) theory

• Control (informal definition)
• Monitoring influencing actions / events
• Process Under Control (PUC)
• Hardware software and/or humans
• Usually regarded as (finite) state machine
• Inputs from environment (via sensors)
• Outputs to environment (via actuators)
• Internal states
• Controlling Process (CP)
• Goal-directed (objectives)
• HW SW maybe also humans (controllers)
• Human supervisory control
• Not in contact with environment only via PUC

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Process models (12) theory
Objectives
instructions
observations
Controlling process
Process Under Control
inputs
outputs
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Process models (13) theory
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Process models (14)

• Process models surveyed
• OODA (Boyd)
• SHOR (Wohl)
• Rasmussen
• RPDM (Klein)
• SA (Endsley)
• PDCA (Shewhart / Demming)
• HEAT (Lawson)
• Other surveys
• Mayk Rubin 1988 15 models (incl. SHOR)
• Brehmer 2005 4 models (incl. SHOR HEAT)
• Essens et al 2005 8 models

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Process models (15) Boyds OODA

• History
• Source
• Boyd J.R. 1987. An Organic Design for Command
  and Control. In A Discourse on Winning and
  Losing. Unpublished lecture notes
• USAF Col. John Boyd
• 1927-1997
• 1945-47 Enlisted in US Army Air Corps
• 1951-75 USAF officer
• Fighter pilot
• Served in Korean Vietnam wars
• 1954-60 Fighter Weapons School
• Forty-Second Boyd
• Proud of description as maverick thinker

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Process models (16) Boyds OODA

• History (continued)
• Birth of OODA loop
• Small part of Boyds overall thesis
• Energy manoeuvrability
• Fighter design (F.15 F.16)
• Air-to-air tactics
• OODA based on his observation of dog-fights
• Idea advocated by 15-hour/2-day briefings
• Patterns of Conflict
• A Discourse on Winning and Losing (327s)
• Idea rejected by USAF till 1991 Gulf War
• Adopted enthusiastically by US Marines

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Process models (17) Boyds OODA
Observe
Orient
Decide
Act
Observations
Note how orientation shapes observation shapes
decision shapes action and in turn is shaped by
the feedback and other phenomena coming into our
sensing or observing window. From The Essence of
Winning and Losing John R. Boyd January 1996.
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Process models (18) Boyds OODA
Observe
Orient
Decide
Act
Plan
Plan
ImplicitGuidance Control
ImplicitGuidance Control
UnfoldingCircumstances
CulturalTraditions
Observations
Decision(Hypothesis)
GeneticHeritage
Analyses Synthesis
Action(Test)
FeedForward
FeedForward
FeedForward
NewInformation
PreviousExperience
OutsideInformation
UnfoldingInteractionWithEnvironment
UnfoldingInteractionWithEnvironment
Feedback
Feedback
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Process models (19) Boyds OODA

• Observe
• Collect sensor observations of PUC environment
  ( CP)
• Orient/Assess
• Filter observations according to expectations
• Identify situation(s) matching filtered
  observations
• Decide
• Select suitable response to identified situation
• Act
• Implement selected response generate
  expectations
• Often means issuing instructions to sensors
  effectors
• Plan
• Develop options for multiple situations
  predict future states

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Process models (20) Boyds OODA

• Key features of Boyds OODA model
• Centrality of Orient (Situation Awareness)
• Only process shown in detail in Boyds (1996)
  figure
• In Boyds words
• Note how orientation shapes observation shapes
  decision shapes action and in turn is shaped by
  the feedback and other phenomena coming into our
  sensing or observing window.
• Tempo In Boyds words
• In order to win we should operate at a faster
  tempo or rhythm than our adversaries or better
  yet get inside the adversarys
  Observation-Orientation-Decision-Action (OODA)
  loop.

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Process models (21) Boyds OODA

• Situation Awareness (SA)
• Perception of elements in environment within a
  volume of time and space comprehension of their
  meaning and projection of their status in near
  future
• A.k.a. having big picture or helicopter view
• Knowing what is going on around me NOW
• Levels
• Perception of elements in environment PUC
• Comprehension combine interpret store
  information
• Prediction forecast future events what-if
  simulation
• SA determines capacity to decide act
• Good SA depends on
• Receiving information from diverse sources
• Evaluating it quickly
• Distributing it to dispersed units

Endsley 2000
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Process models (22) Boyds OODA

• C2 decision making
• Rational decision-making (1940s-1985)
• Enumeration ranking of options (decision
  theory)
• Rational (optimising) decision makers
• Option selection process central
• Pro proven optimal
• Con needs perfect information unlimited time
• Naturalistic decision-making (1985 on)
• Single-option pattern matching simulation
• Experienced decision makers in natural
  environment
• Situation assessment (Orient) central
• Pro fast / time limited robust under
  uncertainty
• Con satisficing / not optimal human errors /
  biases

Raiffa 1968
Klein 1998
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Process models (23) Boyds OODA

• Influence of OODA
• Military
• OODA underlies
• Manoeuvre warfare
• AirLand battle
• Shock and awe
• Network-centric warfare
• Civil
• Harvard Business Review article 1988
• Adopted by
• Toyota Nokia GE Intel
• Multiple variants in C2 literature

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Process models (24) Wohls SHOR

• History
• Source
• Wohl F.G. 1981. Force Management Decision
  Requirements for Air Force Tactical Command
  Control IEEE Transactions on Systems Man and
  Cybernetics SMC-11 9 618-639 (September 1981)
• Wohl
• Psychologist
• MITRE Corp.
• SHOR model
• Many influences (see p.625)
• Decomposed into sub-processes (see Fig. 7)
• Maps closely to OODA
• See Grant Kooter (2005)
• However Wohl Boyd do not seem to have been
  aware of each others work

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Process models (25) Wohls SHOR
Triggering event (deadline enemy action new
data etc)
Stimulus
Response
Hypothesis
Option
Environment
Raw or pre-processed data
Action or communication
Antagonists
Protagonists
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Process models (26) Wohls SHOR

• Influence of Wohls paper
• Much cited
• Largely for Tactical Decision Process (not SHOR)
• Easily accessible in open literature
• Not spawned other areas of research
• (unlike Rasmussen)

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Process models (27) Rasmussen

• History
• Source
• Rasmussen J. 1983. Skills rules and knowledge
  signals signs and symbols and other
  distinctions in human performance models IEEE
  Transactions in Systems Man and Cybernetics
  SMC-13 3 257-267 (May/June 1983)
• Rasmussen
• Psychologist
• Worked with W.B. Rouse human diagnosis
• Riso National Laboratory
• Three-level model
• Stimulus-Response theory (Skinner)
• Roots in diagnosis
• If experience doesnt work use 1st principles
• Influenced by Artificial Intelligence
• IF-THEN rules (expert systems)

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Process models (28) Rasmussen
skill based (signals)
Rasmussen 1983
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Process models (29) Rasmussen

• Influence of 3-level model
• Analysis of control task
• Task analysis
• Matching levels of decision support
• User interfaces
• Sources of human error
• Reasons GEMS model
• Training
• Multi-agent systems
• 3-tier (3T) architecture
• Used 2 levels (rule knowledge) in my PhD

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Process models (30) Rasmussen
knowledge based (symbols)
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Process models (31) PDCA

• History
• Sources
• Shewhart. 1939. Statistical Method from the
  Viewpoint of Quality Control
• Demming. 1951. The New Way. In Elementary
  Principles of the Statistical Control of Quality
  Nippon Kaagaju Gijutsu Remmei Tokyo Japan
• Shewhart
• 1891-1967
• Statistical control (in manufacturing)
• Origin of PDCA
• Shewharts 1939 book
• Demmings role
• Management by position cooperation 14 points
• Champion of Shewharts ideas Shewhart Cycle
• Introduced 4th step 1951

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Process models (32) PDCA
Plan
Do
Act
Check
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Process models (33) PDCA

• Plan
• Determine goals targets
• Determine method of reaching goals
• N.B. Combines OODAs Plan Decide
• Do
• Engage in education training
• Implement plan (c.f. Act in OODA)
• Check
• Check effects of implementation
• N.B. Sometimes called Study (PDSA)
• Act
• Take appropriate action
• N.B. Not same as Act in OODA learning process

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Process models (34) PDCA

• Influence of PDCA
• Quality control
• Management theory
• Widely used by management consultants
• Information computer security
• BSI 17799

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Process models (35) comparison
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Team model communication
Received Signal
Signal
Message
Message
Information source
Transmitter
Receiver
Destination
Noise source
Adapted from Shannon 1948
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Team model OODA-based
Information distribution
Shared awareness
Team maintenance task (re-)allocation
Confirmation authorisation
Adapted from Keus 2002
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Team model CTEF (1)
Essens et al 2005
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Team model CTEF (2)

• Task-focused behaviours
• Managing information
• Obtaining information
• Processing information
• Exchanging information
• Assessing situation
• Making decisions
• Planning
• Directing controlling
• Liaising with other command teams
• Maintaining common knowledge

Essens et al 2005
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Team model CTEF (3)

• Team-focused behaviours
• Providing maintaining vision
• Maintaining common intent
• Interacting within team
• Communicating
• Coordinating
• Providing feedback
• Motivating
• Adapting
• Monitoring
• Correcting (offering feedback / guidance)
• Backing-up (supporting with compensatory
  behaviours)
• Providing team maintenance

Essens et al 2005
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OODA-RR (1) OODAs shortcomings

• Neither detailed nor formalised
• No guarantee of scalability
• Other agents not modelled explicitly
• Competitive interactions only
• Lacks psychological validity
• No domain state or world model
• No concept of attention or memory
• Lacks deliberative planning process
• Lacks learning process
• Not published in accepted scientific way
• Has been subjected to peer review

Grant Kooter 2005
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OODA-RR (2) need for RR

• OODA influential as mental model
• Describes decision-makers thinking process
• But is it suitable as IS architecture
• Indication is positive (N.B. as operational view)
• User-centred design
• Suitability needs testing (research)
• Rational reconstruction essential
• Using SADT/IDEF0 UML notation
• Using systematic set of use-cases
• In context of C2 architecture standards
• E.g. DoD Architecture Framework ATCCIS

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OODA-RR (3) RR approach

• Rational reconstruction
• Systematic translation of intuitive knowledge
  into logical form
• Reconstructing OODA
• Identify shortcomings
• Define requirements
• Define top-level use-cases
• Select notation
• Formalise process model walking through
  use-cases
• Implement
• Evaluate

Habermas 1979
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OODA-RR (4) requirements

• Requirements
• Retain 4 processes as core functionality
• Add planning learning processes
• Emphasise concurrent processing
• Provide rule- knowledge-based levels of
  reasoning
• Base decomposition on RPDM for validity
• Represent real-time aspects (tempo)
• Explicitly show agent boundary
• Allow multiple human and/or machine agents
• Permit competitive and/or collaborative
  relationships

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OODA-RR (5) use-cases

• Use-cases

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OODA-RR (6) the model
Set Filter
Observation
Observing
Retrieve alternative COA
Signal
Goals
Goals
Orienting
Unexpected situation
Sensors
Expected Situation
Control of planning
Accepted goal
Prototypes
Planning
Plans
Assessors
Observed prototypes
Construct COA
Effects achieved
Prototypes
New/modified Prototype
Environment
Planners
Deciding
Situation not recognised
Selected Plan
Decisionmakers
Control of Sensemaking
Existing prototypes
Sensemaking
Acting
Sensemakers
Actuators
COAs
Expectations
Actions
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OODA-RR (7)

• Processes
• Observing
• Collecting observations
• Orienting
• Assessing situation using Prototypes creating SA
• Planning
• Developing courses of action (COA) based on SA
• Deciding
• Selecting which COA to execute
• Acting
• Executing selected COA generating expectations
• Sensemaking
• Creating Prototypes from experience

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OODA-RR (8)

• Data structures
• Observations
• Raw observations / data (typically from sensors)
• Situations
• Assessed situations matching Observations to
  Patterns
• (selected) Plans
• Courses of action ( action-sequences)
• Goals
• Desired future Situations / effects to be
  achieved
• Prototypes
• Templates describing Situation-patterns based on
  experience
• Actions
• Instructions / requests to PUC
• Expectations
• Expected Observations if PUC executes Actions
  correctly

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OODA-RR for organising team (1)

• Typically specialisation
• By discipline
• Logistics transport medical etc
• By organisation
• Army Navy police fire brigade UN Red Cross
  etc
• Leads to stove-pipes
• Communications up/down hierarchies
• Communication delays noise distortion
• Coordination only at top levels
• Overloads top

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OODA-RR for organising team (2)

• Possibilities based on OODA(-RR)
• One person does everything
• Group sub-processes one person per group
• Combine Plan in Orient or in Decide
• Group Observe Orient
• Group Decide Act
• One person per sub-process
• Observe Orient Plan Decide Act Sensemaking
• Multiple people for important sub-processes
• E.g. multiple people for Orient or for Plan
• Deliberately omit sub-processes
• Plan - purely reactive only 1 step look-ahead
• Sensemaking - no learning or post-hoc

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OPERATION BEACH TOWEL
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OPERATION BEACH TOWEL (1)

• We could run OPERATION BEACH TOWEL twice
• Centralized operation
• Control Post (CP) as master node
• Nodes as (honest) slaves do (only) what CP tells
  them to do
• Network-centric operation
• No control cell / master node
• Nodes as intelligent agents ( everyone is
  master)
• Hand-simulation
• You will simulate
• OODA-RR processes in CP
• PUC nodes (Barracks Depot APOE SPOE etc)
• I will act as simulation controller
• Start stop simulation
• Simulation clock (in days)
• Ensure nodes play according to their Rules of
  Engagement

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OPERATION BEACH TOWEL (2)

• Situation
• Germlish tourists have overrun eastern Madeira
• Madeirans have appealed for UN help
• Dutch government has responded
• 6000 policemen to round up Germlish tourists
• Dutch Army logistics battalion
• Three KC-10 aircraft for air transport Dutch AF
  personnel
• Hired Queen Mary II for sea transport
• Mission
• To round up all Germlish tourists in eastern
  Madeira and to transport them back to Barracks in
  Netherlands in the shortest possible time

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Strategic transportation concept
POE
POD
TOA
Operational Control
Transportation for strategic mobility
Air Sea
Road Rail Waterways
Road Bus Rail
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OPERATIONAL COMMANDER
OPCO
TOA
CA
Strategic movement
Operational movement
Tactical movement
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OPERATION BEACH TOWEL (3)
Madeira
Netherlands
CP
1d
1d
Barracks
APOE
APOD
AA1
KC-10s only
1d
2d
1d
TOA
2d
1d
1d
1d
7(2)d
Depot
SPOE
SPOD
AA2
QM II only
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OPERATION BEACH TOWEL (4)
Madeira
Netherlands

• Network-centric communications
• Anyone can query or make request of anyone else
• Can broadcast queries / requests (e.g. Who has
  X)

1d
1d
Barracks
APOE
APOD
AA1
KC-10s only
1d
2d
1d
TOA
2d
1d
1d
1d
7(2)d
Depot
SPOE
SPOD
AA2
QM II only
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OPERATION BEACH TOWEL (5)

• Compare the two runs
• Differences in communication patterns
• Topology / connectivity
• Communications workload
• Differences in cognitive patterns
• Planning effort
• Decision-making effort
• Workload
• Differences in effectiveness
• Completeness of awareness of the situation
• Quality of decision-making
• Differences in efficiency
• How quickly were first Germlish tourists
  evacuated
• How long before all Germlish tourists were
  evacuated

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OPERATION BEACH TOWEL (6)

• Allocating roles
• PUC nodes
• The leader (Decide)
• I wanna be the leader
• I wanna be the leader
• Can I be the leader
• Can I Can I
• Promise Promise
• Yippee Im the leader
• Im the leader
• OK what shall we do
• Roger McGough (b. 1937)
• Rest of CP nodes

66
OPERATION BEACH TOWEL (7)
Madeira
Netherlands
1d
1d
Barracks
APOE
APOD
AA1
KC-10s only
1d
2d
1d
TOA
2d
1d
1d
1d
7(2)d
Depot
SPOE
SPOD
AA2
QM II only
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End ofOPERATION BEACH TOWEL
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OODA-RR for IS architecture (1)

• Two choices
• Implement OODA-RR (at operational level)
• Decompose OODA-RR implement
• E.g. Crew/Operator Support POLicy (COSPOL)
• Based on analysing 12 implemented C2 systems
• Implemented for ESA in Advanced Crew Terminal

Grant 2002
69
OODA-RR for IS architecture (2)

• On-going research
• Key question
• Is OODA a good basis for C2 system architecture
• Intuition
• Systems based on users mental model have higher
  useability acceptance
• Users mental model (in military C2) OODA
• Running projects
• HackSim 2 Masters students at Univ. Liverpool
• Future projects
• Hierarchical vs. network-centric connectivity
• Speed-up planning by 1 OOM
• Implement Sensemaking (from my PhD)

70
References (1)

• Ashby W.R. 1963. An Introduction to
  Cybernetics. John Wiley Sons New York
• Boyd J.R. 1987. An Organic Design for Command
  and Control. In A Discourse on Winning and
  Losing. Unpublished lecture notes
• Brehmer B. 2005. The Dynamic OODA Loop
  Amalgamating Boyds OODA Loop and the Cybernetic
  Approach to Command and Control. In Proceedings
  10th International Command and Control Research
  Technology Symposium McLean VA USA
• Brehmer B. 2006. One Loop to Rule Them All. In
  Proceedings 11th International Command and
  Control Research Technology Symposium Cambridge
  UK
• Demming. 1951. The New Way. In Elementary
  Principles of the Statistical Control of Quality
  Nippon Kaagaju Gijutsu Remmei Tokyo Japan

71
References (2)

• Endsley M.R. 2000. Theoretical Underpinnings of
  Situation Awareness. In Endsley M.R. Garland
  D.J. (eds). Situation Awareness Analysis and
  Measurement. LEA Mahwah NJ USA
• Essens P. Vogelaar A. Mylle J. Blendell
  C. Paris C. Halpin S. Baranski J. 2005.
  Military Command Team Effectiveness Model and
  instrument for assessment and improvement. NATO
  RTO Technical Report AC/323(HFM-087)TP/59 (April
  2005)
• Ferrell W.R. Sheridan T.B. 1967.
  Supervisory control of remote manipulation IEEE
  Spectrum 4 81-88
• Grant T.J. Kooter B.M. 2005. Comparing OODA
  and Other Models as Operational View C2
  Architecture. In Proceedings 10th International
  Command and Control Research and Technology
  Symposium (ICCRTS 2005) Washington DC USA

72
References (3)

• Grant T.J. 2005b. Unifying Planning Control
  with an OODA-based Architecture. In Proceedings
  South African Institute of Computer Scientists
  Information Technologists (SAICSIT 2005) White
  River RSA
• Habermas J. 1979. Communication and the
  Evolution of Society. Beacon Press Toronto
  Canada
• Keus H.E. 2002. A Framework for Analysis of
  decision Processes in Teams. Proceedings CCRP
  Symposium June 2002 Monterey CA USA
• Klein G. 1998. Sources of Power How people
  make decisions. MIT Press Cambridge Mass. USA
• Lawson J.S. 1981. Command and Control as a
  Process. IEEE Control Systems Magazine (March
  1981) 5-11 16

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References (4)

• Mayk I. Rubin I. 1988. Paradigms for
  Understanding C3 Anyone In Johnson S.E.
  Levis A.H. (eds). Science of Command and
  Control. AFCEA International Press Washington
  DC USA 48-61
• Rasmussen J. 1983. Skills rules and knowledge
  signals signs and symbols and other
  distinctions in human performance models IEEE
  Transactions in Systems Man and Cybernetics
  SMC-13 3 257-267 (May/June 1983)
• Shewhart. 1939. Statistical Method from the
  Viewpoint of Quality Control
• Wohl F.G. 1981. Force Management Decision
  Requirements for Air Force Tactical Command
  Control. IEEE Transactions on Systems Man and
  Cybernetics SMC-11 9 618-639 (Sep 81)

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Any questions