Title: Operational process models for crisis management
1 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
2 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
3 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
4 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
5 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 6 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) 7 Process models (1) motivation
8 Process models (2) examples 9 Process models (3) examples Combined Air Operations Center Command Centre onboard frigate Collaborative process Army Command Post 10 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 11 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
12 Process models (6) Controllers task 13 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
14 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
15 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 16 Process models (10) theory (Adapted from) Ashby 1963 17 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
18 Process models (12) theory Objectives instructions observations Controlling process Process Under Control inputs outputs 19 Process models (13) theory 20 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
21 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
22 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
23 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. 24 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 25 Process models (19) Boyds OODA
Observe
Collect sensor observations of PUC environment ( CP)
Often means issuing instructions to sensors effectors
Plan
Develop options for multiple situations predict future states
26 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.
27 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
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 29 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
30 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
31 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 32 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)
33 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)
34 Process models (28) Rasmussen skill based (signals) Rasmussen 1983 35 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
36 Process models (30) Rasmussen knowledge based (symbols) 37 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
38 Process models (32) PDCA Plan Do Act Check 39 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
40 Process models (34) PDCA
Influence of PDCA
Quality control
Management theory
Widely used by management consultants
Information computer security
BSI 17799
41 Process models (35) comparison 42 Team model communication Received Signal Signal Message Message Information source Transmitter Receiver Destination Noise source Adapted from Shannon 1948 43 Team model OODA-based Information distribution Shared awareness Team maintenance task (re-)allocation Confirmation authorisation Adapted from Keus 2002 44 Team model CTEF (1) Essens et al 2005 45 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 46 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 47 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 48 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
49 OODA-RR (3) RR approach
Rational reconstruction
Systematic translation of intuitive knowledge into logical form
52 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 53 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
54 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
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
59 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
60 Strategic transportation concept POE POD TOA Operational Control Transportation for strategic mobility Air Sea Road Rail Waterways Road Bus Rail 61 OPERATIONAL COMMANDER OPCO TOA CA Strategic movement Operational movement Tactical movement 62 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 63 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 64 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
65 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 67 End ofOPERATION BEACH TOWEL 68 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
73 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)
74 Any questions
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