(Contribution to NATO SAS-026 Panel, July 2001,
included in the
NATO Code of Best Practice (COBP) for C2 Assessment, 2002,
which can be obtained from the CCRP website using their order form.)
Part of the results of the COBP project was the consideration of the role of the military study process:
It is important is that there be a conscious effort to create (and follow) a study plan that uses the insights and data that are assembled by the study to create a solution. The study plan consists of two inter-related parts the formulated problem (the What) and the solution strategy (the How).
The creation of a successful solution strategy is more art than science; however, the following principles are useful guides to the art.
Figure 1. Prerequisites and Process for Solution Strategies
- The actual question to be answered must be known.
- The measures of merit must be identified to consider how to connect more detailed analyses to the final question.
- The driving scenarios must be identified in sufficient detail to consider which tools are inappropriate/appropriate.
- The human issues must be identified to consider which tools address them and what supplemental analyses will be required to mitigate poor fits between issues and tools.
- The solution strategies that are chosen (or often the choice of available solution strategies) will frequently affect the measures of merit, scenarios, and human issues that can be addressed.
- Initial solution strategies will imply what data are required. The availability of data will also affect the choice of solution strategies.
- Similarly, the initial solution strategy choices will affect the levels and types of risk and uncertainty that will attach to the study. Again, the acceptable types and levels of risk and uncertainty will affect the choice of solution strategies.
- The research design serves to define the analysis domain.
- Its structure can identify unwanted confounding of variables.
- In some cases, the research design can reduce the number of discrete analyses that are required by identifying variables that can be purposefully confounded without loss to the overall analysis. In figure 2, several scenarios are listed (with example variable values to hint at the definitions of each). Several solution options are also listed (with hints for defining variables). The complete solution strategy would involve an analysis for each possible pairing; however, some pairs require no analysis and are marked with "x" values. (The choices here are random. In an actual study, the choices would be dictated by logic.)
Figure 2. Research design: options vs scenarios
- The research design defines the elements of the problem that must be addressed. The example in figure 3 expands the analyses depicted in figure 2. In this case, each scenario must have a version addressing entry into a peace making, peace enforcement, and peace keeping situation. In addition, each scenario must address the possible transitions to a less agreeable and to a more agreeable situation.
Figure 3. Research design details from one cell
- The research design defines the connections among the different tools to be used. In our example, figure 4 imagines that the SIAM tool will yield the final desired measure of merit. SIAM requires a number of inputs, each a measure of merit in its own right. One input (3) has been determined to be unavailable, but unimportant. One input (4) has been determined to be unavailable, but important. It will have to be addressed by using a series of values to determine the nature and range of impact. Two of the inputs can be generated by a second model (represented by DIAMOND). The final input requires human inference to be applied to a DIAMOND output.
Figure 4. Research design connection of multiple tools
- Prior to the experiment or equipment test, analyses are performed to prepare an understanding of what needs to be investigated in the experiment or test.
- To the extent possible, the experiment or test is instrumented with devices or human observers to gather the desired data and to look for unexpected events.
- After the experiment or test, analyses are performed to understand and extend/ extrapolate the observed results.
This example is created for illustration and does not represent a real study; however, it does show many of the elements of real solution strategies. In particular, it illustrates a plan for conducting specific purposeful activities and connecting them to yield the desired result.
The basic guidance for the process for creating a good solution strategy is documentation, iteration, and concentration on the desired product of the study. Documentation is required to remind the team of what has been done, why and how it supports the end product. Iteration is required because everything affects everything else. Concentration on the desired product of the study is required because that is the touchstone for reducing complexity and achieving success.
- Select an approach philosophy, e.g., cost-benefit, risk centric, and hybrids.
- Solution options may be
- Given by sponsor,
- To be derived by study,
- Single domain (e.g., technology options),
- Multiple domains (e.g., technology, organizational structure & doctrine), or
- Co-evolving domains (e.g., changes in technology drive changes in doctrine, which changes technology requirements, which drives doctrine changes, etc.)
- Tool selection process:
- The need for tools is most obvious in the solution strategy part of the analysis; however, there are also tools that are useful in other parts of the analysis.
- The purpose of a tool is to improve the quality of work, reduce the human effort required, or reduce the time required for the work (or some combination of these).
- Human nature leads the analyst to focus on reducing the effort.
- Human nature leads the sponsor to focus on reducing the time required.
- A tool that includes all of the required factors and produces the desired output has the appearance of perfection; however, investigation is required to determine whether it is a "good" model of the problem.
- It will require effort to focus on improving the quality.
- Analysis of OOTW problems is a relatively new process and there are correspondingly few large simulation tools that are germane. Many of the needed tools are missing (at this date). For example, the application of social science methodologies is needed, but not supported in any convenient way and OOTW mission-to-task force designers are generally limited to particular services of particular countries and lack joint, combined and inter-agency features.
- Data selection process:
- Analyses should start by defining the needed data.
- Unfortunately, some data are unavailable. In OOTW problems, much of the data may be missing or difficult to find. Some unavailable data can be collected. The remainder will cause problems that must be mitigated.
- The solution strategy may need to be modified.
- Risk assessment & mitigation (e.g., non-availability of data) process:
- In OOTW problems and in C2 problems, variability (of everything) is high and risk assessment and mitigation are important.
- As the solution strategy is being created and before it is finalized, the team needs to question the strategy. Are all the MOMs covered? Do the tools selected address the human issues that are relevant? Is the C2 model in the tools sufficiently detailed, e.g. is communication content passed on or just a bit count? Has the team identified sources for all the data? Do the data and tools discriminate among the scenarios and options? Are there ways to mitigate the problems? Application sharing of the Excel-based Generic Risk Register will support the teams risk and uncertainty analysis.
- The solution strategy will need to be modified.
- In general, the solution strategy process will feed back into the MOMs, Human Issues, and Scenarios, resulting in refinements of these elements of the study and refinement of the problem definition.
- The format and procedures for the project journal must be defined.
- The format and procedures for the data and results library must be defined.
- The project schedule, including both activities and resources must be defined.
PRODUCT (OUTPUT) GUIDANCE
- Time of occurrence,
- Resource allocations, and
- Coordination with others,
- Tool executions,
- Data collection,
- Data reduction, and
- Report writing.
- Purpose of activities,
- Tool selections, with reasons,
- Connections among tools, with descriptions of inferences and assumptions,
- Risks and mitigations,
- Descriptions of required data, and
- Descriptions of archived output data.
With most textbooks, the bulk of the text is concerned with teaching about the available tools, not with how to use them as an ensemble. Each of the following references provides a piece of the picture.
Clemen, Robert T., Chapter 1 in Making Hard Decisions: an Introduction to Decision Analysis, Duxbury Press, 1990.
Hillier, Frederick S. and Gerald J. Lieberman, Chapter 2 in Introduction to Operations Research, Fifth Edition, McGraw-Hill, 1990.
Hoeber, Francis P., Editor, Chapter 1 in Military Applications of Modeling: Selected Case Studies, Military Operations Research Society and Gordon and Breach Science Publishers, 1981.
Hughes, Wayne P., Jr., Editor, Overview in Military Modeling, Military Operations Research Society, 1984.
Jaiswal, N. K., Chapter 1 in Military Operations Research: Quantitative Decision Making, Kluwer Academic Publishers, 1997.
Quade, E. S., Editor, Chapters 1, 16, and 17 in Analysis for Military Decisions, Military Operations Research Society, 2000.
Rosenhead, Jonathan, "Problem Structuring Methods," in Encyclopedia of Operations Research and Management Science, Second Edition, Gass & Harris, Eds., Kluwer Academic Publishers, 2001.
Wagner, Harvey M., Chapter 1 in Principles of Management Science, Second Edition, Prentice-Hall, 1975.
The first entry below provides a good starting point for learning about methodologies/ tools that may be useful. The second gives a brief overview of OOTW tool types, describe more expansively in the third entry.
Gass, Saul I. and Carl M. Harris, Editors, Encyclopedia of Operations Research and Management Science, Second Edition, Kluwer Academic Publishers, 2001.
Hartley, Dean S., III, "Military Operations Other Than War," in Encyclopedia of Operations Research and Management Science, Second Edition, Gass & Harris, Eds., Kluwer Academic Publishers, 2001.
Hartley, Dean S., III, Operations Other Than War: Requirements for Analysis Tools Research Report, K/DSRD-2098, Lockheed Martin Energy Systems, Inc., 1996.
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