One Army One Team One Vision Operational Research

One Army, One Team, One Vision Operational Research Land Capability Development Operational Research Team

One Army, One Team, One Vision Operational Research Deciding Which Method to Use –

One Army, One Team, One Vision Operational Research Cameron’s Rubbish. Can Bin Model of

One Army, One Team, One Vision Operational Research March’s Garbage Can Model of Decision

One Army, One Team, One Vision Operational Research Description • “Deciding Which Method to

One Army, One Team, One Vision Operational Research The Operational Research Tool Box Some

One Army, One Team, One Vision Operational Research Our Early Meta-decision Rules for “Deciding

One Army, One Team, One Vision Operational Research Simulation Types People Simulated Real Simulated

One Army, One Team, One Vision Operational Research Goal Synthetic Environment Joint War Game

One Army, One Team, One Vision Operational Research Constructive Simulations • Command Staff Trainer

One Army, One Team, One Vision Operational Research Constructive Simulations Une Armée, une équipe,

One Army, One Team, One Vision Operational Research Lesson 1: AE-7 B* Armed Griffon

One Army, One Team, One Vision Operational Research AE-7 B – The Textbook Case

One Army, One Team, One Vision Operational Research Lesson 2: LOE* 0301 – TUAV

One Army, One Team, One Vision Operational Research LOE 0301 – The Short Circuit

One Army, One Team, One Vision Operational Research Ascription • Does the Garbage Can

One Army, One Team, One Vision Operational Research The Operational Research Skill Set Toolbox

One Army, One Team, One Vision Operational Research Roles of Soft OR Methods •

One Army, One Team, One Vision Operational Research Prescription • Consider the full spectrum

One Army, One Team, One Vision Operational Research Application of the Spectrum of Methods

One Army, One Team, One Vision Operational Research Proscription • Woe, woe, and thrice

One Army, One Team, One Vision Operational Research Specification Error Models, Complexity and Error

One Army, One Team, One Vision Operational Research Main Recommendation • Make the actors

One Army, One Team, One Vision Operational Research References • Michael D. Cohen, James

One Army, One Team, One Vision Operational Research Questions – Discussion Fred Cameron Tel:

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One Army, One Team, One Vision Operational Research Babes in the Woods: How Naïve Analysts Clashed with Trained Killers to the Mutual Benefit of All Fred Cameron Operational Research Advisor to the Director General Land Capability Development Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Defence Research and Development Canada Kingston, Ontario Une Armée, une équipe, une vision Directorate of Land Synthetic Environments Recherche opérationnelle

One Army, One Team, One Vision Operational Research Land Capability Development Operational Research Team • • • Mr Fred Cameron (Team Leader) Mr Roger Roy Ms Eugenia (Jenny) Kalantzis Mr Ian Chapman Mr François Cazzolato Maj Bruce Chapman (to join July 2006) • The Army Experimentation Centre – Part of the Directorate of Land Synthetic Environments (Army’s home for Computer-based Wargames, Models, and Simulations for Training and Experimentation) • Strategic Analyst – Mr Peter Gizewski • Science Advisor – Mr Regan Reshke Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Deciding Which Method to Use – A Meta-Decision • A meta-model of the meta-decision process • An analysis: – Description • What happened? – Ascription • Were there causes and effects? – Prescription • What should we do in future? – Proscription • What should we avoid in future? Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Cameron’s Rubbish. Can Bin Model of March’s Garbage Decision Making • Born of many years of observation • Employed for organizations that are “organized anarchies” • Basis for workshop on “Ambiguity and Command” in 1986 • Used provocatively: – Is it really that bad? Sources: Cohen, March, and Olsen (1972), March and Weissenger-Baylon (1986), and March (1994) Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research March’s Garbage Can Model of Decision Making Complex interactions between: • Actors (decision makers) • Problems • Choice opportunities • Potential solutions Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research March’s Garbage Can Model of Decision Making • Some ways to “improve” garbage-can decision making – Increase the heat and pressure • Force more frequent interactions – Put more garbage in the can • Add more potential solutions • Add more problems, more actors, more decision opportunities too? – Make actors “stickier” • Hope that they will carry problems or potential solutions with them long enough to get a better fit Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Description • “Deciding Which Method to Use” – OR analysts make great critics of the decisionmaking of others – But, turn the lens into a mirror • The Analyst’s Toolbox… Our Experience • Canadian Army Modelling and Simulation • Specific Examples and Lessons Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research The Operational Research Tool Box Some Examples • Structured brain storming • Scenarios Soft • Analysis of historical data • Options analysis, Decision analysis • Group ranking OR/OA Methods • Seminar war games • Analytical tools – mathematical analysis • Computer-based war games (JANUS, One. SAF) Hard • Trials, exercises, and evaluations Less: • time • resources • credibility More: • time • resources • credibility – Source: Future Army Development Plan, 1998 Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Our Early Meta-decision Rules for “Deciding Which Method to Use” • If time and resources are short, and credibility is not an issue, then use soft OR methods • If credibility is paramount, and time and resources are available, then use hard OR methods • Our experience supports: “hard and soft methods can be used together at appropriate stages of a study (usually soft for problem formulation, hard for resolution)” Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Simulation Types People Simulated Real Simulated Virtual Constructive Equipment Real Une Armée, une équipe, une vision Live Recherche opérationnelle

One Army, One Team, One Vision Operational Research Goal Synthetic Environment Joint War Game C 2 Systems Real World Link Live Constructive Link Link Army Navy Air Force Link Simulators Une Armée, une équipe, une vision Operational Tactical Virtual Recherche opérationnelle

One Army, One Team, One Vision Operational Research Constructive Simulations • Command Staff Trainer • UK’s ABACUS Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Constructive Simulations Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Lesson 1: AE-7 B* Armed Griffon Helicopter • Aim. To provide insights into differences in effectiveness and survivability between an armed an unarmed helicopter • Purpose. To validate the incorporation of aerial firepower requirements in the CH-146 Griffon Helicopter mid-life upgrade • Simulation Structure. Constructive and virtual computerbased simulation supported by One. SAF Testbed Baseline (OTB), with virtual workstations for Griffon helicopters and Pointer-type Unmanned Air Vehicles (UAV) * AE = Army Experiment Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Lesson 1: AE-7 B Armed Griffon Helicopter Constructive OTBSAF DIS Griffon Pointer Une Armée, une équipe, une vision Tactical Virtual Recherche opérationnelle

One Army, One Team, One Vision Operational Research AE-7 B – The Textbook Case Strong Sponsor Involvement Weak Synthetic Environment Specification Late Terrain Generation Late Scenario Build Define Develop Conduct Analyze Excellent Participant Base Automated Small Sample Statistics Late Griffon Simulation Delivery Une Armée, une équipe, une vision Apr 03 Mar 03 Feb 03 Jan 03 Dec 02 Nov 02 Oct 02 Sep 02 Aug 02 Jul 02 Jun 02 Report Corrective Action • Implemented Synthetic Environment Statement of Requirement Recherche opérationnelle

One Army, One Team, One Vision Operational Research Lesson 2: LOE* 0301 – TUAV in Controlled Airspace • Aim. To investigate possible reduced airspace restrictions for UAVs if Air Traffic Controllers have better situational awareness • Objective. To identify any differences in situational awareness enabled by various improvements to ATC situational awareness (in the vicinity of Kabul) • Simulation Structure. Constructive and virtual computerbased simulation supported by One. SAF Testbed Baseline (OTB), with virtual workstations for ATC Tower, Air Defence and ATC radars, and UAV * LOE = Limited Objective Experiment Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Lesson 2: LOE 0301 – TUAV in Controlled Airspace Constructive Tactical OTBSAF DIS AD Rdrs/ EOs DIS DIS ATC Rdr Tower Ops TUAV Une Armée, une équipe, une vision Virtual Recherche opérationnelle

One Army, One Team, One Vision Operational Research LOE 0301 – The Short Circuit Staff Check Problem Identification Sponsor Identification Iterative Prototyping Define Develop Conduct Analyze Terrain Incomplete Sponsor Participant Access Automated Situation Awareness Analysis Tools Report Pre-Preparation Nov 03 Oct 03 Sep 03 Aug 03 Jul 03 Jun 03 May 03 Report Une Armée, une équipe, une vision Corrective Action • Create Terrain/Visualization Cell Recherche opérationnelle

One Army, One Team, One Vision Operational Research Ascription • Does the Garbage Can Model fit? Is it really that bad? • Decision outcomes driven by – Temporal Confluence: Decision makers, Choice opportunities, Problems, Potential solutions • Is the method we use for “deciding which method to use” any better that? Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research The Operational Research Skill Set Toolbox • Structured brain storming • Scenarios Soft • Analysis of historical data • Options analysis, Decision analysis OR/OA • Group ranking Methods • Seminar war games • Analytical tools – mathematical analysis • Computer-based war games Hard (JANUS, One. SAF) • Trials, exercises, and evaluations Une Armée, une équipe, une vision Skill set • Facilitator • Scribe • Co-author of scenarios • Enumerator of votes • Analyst of preferences • Modeller • Mathematician/Statistician • Experimenter in simulation space • Experimenter in live trials Recherche opérationnelle

One Army, One Team, One Vision Operational Research Roles of Soft OR Methods • To support thinking and planning by an individual analyst or decision maker – problem articulation • To support discussion between consultant and decision maker – problem negotiation • To support debate and conclusion among decision makers – group decision support • To initiate or strengthen organisational capabilities – organisational development – Source: Steve Cropper presentation in Holt and Pickburn (2001) Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Prescription • Consider the full spectrum in the tool box • Prepare for the full range of required skills • Implement a “lessons” process, and strive to improve Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Application of the Spectrum of Methods • Soft and hard OA should be viewed as equally useful and part of the analyst’s toolkit. These should be viewed as a spectrum of options within the analyst’s toolkit which should be selected and used as appropriate. • It was recognised that hard and soft methods can be used together at appropriate stages of a study (usually soft for problem formulation, hard for resolution). • Analysts need to be aware of all OA techniques and, broadly where they should and should not be employed. Better education may help to achieve this. • An expert practitioner (or team) is needed with expertise in the range of methods appropriate to the problem. – Extracts from Holt and Pickburn (2001), pp. 15, 17 and 19 Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Proscription • Woe, woe, and thrice woe • Beware of complexity Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Specification Error Models, Complexity and Error Model Error Complexity Measurement Error Minimize Model Error Complexity Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Specification Error Models, Complexity and Error Complexity If we can increase the accuracy of performance characteristics, we can accommodate greater complexity. Error Model Error Measurement Error Overall error drops. Complexity Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Specification Error Models, Complexity and Error Model Error Complexity Measurement Error Minimize Model Error by Decreasing Complexity Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Main Recommendation • Make the actors “stickier”: – Analysts need to be aware of all OA techniques and, broadly where they should and should not be employed. Better education may help to achieve this – An expert practitioner (or team) is needed with expertise in the range of methods appropriate to the problem Source: Holt and Pickburn (2001) Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research References • Michael D. Cohen, James G. March, Johan P. Olsen “A Garbage Can Model of Organizational Choice” Administrative Science Quarterly, Vol. 17, No. 1. (Mar. , 1972), pp. 1 -25 • James G. March and Roger Weissenger-Baylon eds. (1986) Ambiguity and Command: Organizational Perspectives on Military Decision. Making. Marshfield, MA Pitman Publishing Inc. • James G. March (1994) A Primer on Decision Making: How Decisions Happen. New York: The Free Press • Future Army Development Plan (1998) Kingston, Ontario: Directorate of Land Strategic Concepts • John Holt and George Pickburn (2001) OA Techniques for the Future. Farnborough, UK: Defence Evaluation and Research Agency. 30 March 2001 Une Armée, une équipe, une vision Recherche opérationnelle

One Army, One Team, One Vision Operational Research Questions – Discussion Fred Cameron Tel: +1. 613. 541. 5010 ext 2470 Email: Cameron. FWP 2@forces. gc. ca Une Armée, une équipe, une vision Recherche opérationnelle