SMALL (and simple) Is USEFUL

1. SMALL (and simple) Is USEFUL Simple Models as aids for Higher Level Military Decision Making 21st ISMOR Moshe Sharvit Thinkware Ltd. hgrtmr@zahav.net.il

2. Examples of H.L. Issues • Force structure • Relating operational means to strategic ends • Force sizing • Acquisition of major w/s

3. Main Points • “Interacting with DM” and “The use and abuse of simple models”– not mutually exclusive • Simple models have some important uses as aids to H.L. decision making

4. The “socio-analytic” situation Analytic community Analyst DM Problem Model

5. The “socio-analytic” situation Analytic community Analyst DM Problem Model “Organizational culture”

6. Problem Characteristics • Squishy; ill defined problems • Undefined goals – no clear “objective function” • Complex relation of operational means to strategic goals • Uncertainty –cannot be reduced to a probability distribution • Multi-criteria • “Soft” criteria - unquantifiable • Paucity of reliable data

7. Implications • What is it all about? • Optimization is rarely sought • Robustness is of the essence • Value judgments

8. Perceptions of Analyst’s Expertise Analyst Technical Expert* Systems analysis expert *e.g.: munitions effectiveness, search theory, logistics etc.

9. Analyst & DM: Domains of Expertise • Technical expert vis-à-vis the DM – Little or no overlap - analyst possesses “professional authority” • Sys. Analyst vis-à-vis the DM - Significant overlap. Interaction: not authority but Persuasion in this case Analyst’s parlance, models and other tools of trade should be communicable to non-members of the analytic community

10. The Analyst’s Role & the Complexity of Models • Opaque vs. Transparent models • Complex, mathematically sophisticated models tend to place the Analyst in the “Surrogate DM” position • Disregard of soft, unquantifiable variables leads to the “bean-counter” trap

11. “Utilization Success”(Goeller)Mainuses of Simple Models • Problem formulation • Generation of alternatives • Estimation of consequences • Rejection of alternatives • Selection of preferred alternative • Promotion of preferred alternative • Implementation

12. In Conclusion “Everything should be made as simple as possible, but not simpler”. Albert Einstein

13. The End

14. Problem formulation: The Role of the Model(after E. Quade) • Provide a depiction of reality • Provide a perspective of reality At the higher operational and strategic levels it is difficult to achieve a reasonably accurate depiction of reality using quantitative models

15. Model need not encompass the whole issue; elucidate an aspect of the problem • Model needs to be relevant to a variety of particular situations • “validation by consent”

16. Problem formulation: Uses of simple models • Gain understanding through: • identification of system elements • identification of interplays and interdependencies (synergy, etc.) • Outline basic dilemmas • An aid to the establishment of criteria • Outline basic alternatives

17. Example - Countering SSM’s: Interception & counter-attack Impacts c.a. only No response Int. only c.a. + int. Time

18. Some issues raised • Mix proportions • Temporal differences: early period vs. later period • # of interceptors • Operational (systemic) effect of each weapon system mop

19. Rejection of alternativesExample: replacement of old weapon systems • Limited budgets but plenty of w/s acquisition opportunities. • To pass the test the candidate w/s needs to have a decisive overall advantage over the incumbent w/s otherwise • There is probably a better opportunity • A simple model may provide a bound on cost/effectiveness ratios

20. An example: Selection of Fighter A/C • Cost (LCC): f1 /f2 =approx. 2 • Effectiveness: f1 selected if either: • f1 has unique, extremely important, capabilities; or • f1 clearly outperforms f2 in almost every major category by at least 2:1.