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PROJECT: Military Study Solution Strategies

Dean S. Hartley III

(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).

KEY DEFINITIONS

• Solution strategy: consists of a set of sequential and parallel analysis steps, often involving several methodologies and tools. The solution strategy leads from what is known to what one desires to know – the answer to the problem. The strategy can be simple (e.g., calculate mortgage payments by finding the input values for the payment equation and then evaluating the result), moderately complicated (e.g., define input variables, output variables, precision requirements, etc.; create a designed experiment; run the experiment, with appropriate measurements; and perform the regression analysis), or extremely complicated (see the example below). The elements of the solution strategy include the following:

• Measures of Merit (MoM): a set of variables that subsume dimensional parameters, measures of performance, and effectiveness.

• Scenarios: consists of three elements – a context (e.g. a characterization of a geopolitical situation), the participants (e.g. intentions, capabilities of blue, red, others), the environment (e.g. natural – weather and manmade – mines), and the evolution of events in time.

• Human Factors: a set of variables that characterize concepts including beliefs, cultural norms, stress and fatigue, fear, morale, intelligence, level of experience.

• Organizational Factors: a set of variables that characterize organization characteristics including cohesion, command structure, explicit and tacit relationships, information flows, culture.

• Data: values of the variables either empirical, subjective, and/or assumed.

• Model: physical, analogue, or symbolic representation of relevant aspects of reality for a purpose -- an abstraction of reality. A model emphasizes particular aspects of reality. For example, a plastic scale model of an airplane emphasizes size and shapes; however, it does not fly.

• Tool: facilitates the exploration of relationships among model variables and/or develops "solutions" (e.g. maximize value subject to constraints). A tool may be as simple as a checklist, may be an algorithm, or may be an extremely large simulation. A simulation is the instantiation of a model that serves to facilitate the exploration of the relationships among the variables -- generates "data" for analysis, generally emphasizes the passage of time (comes in various forms - constructive, virtual, live).

• Occasionally, the distinction between the tool, model and data is subtle. For example, in a linear program, the model is the set of formulas that specify the objective function and the constraints. The tool is the simplex method (or similar algorithmic solution method). The data is an instantiation of the formulas (provides values for the coefficients and constants). In the case of a simulation, the simulation environment and simulation engine are the tools; the coded simulation embodies the model; and the input values to the simulation comprises the data. Often, the simulation code and the data, together, are required for a complete definition of the model.

PRINCIPLES

The creation of a successful solution strategy is more art than science; however, the following principles are useful guides to the art.

• Prerequisites: the solution strategy should not be designed before the problem structuring process is substantially complete. As shown in figure 1, structuring the problem is an iterative process, with creation of solution strategies forming the last iteration.

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.

• Iteration: As shown in figure 1, the solution strategy creation process is also iterative.

• 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.

• Research Design: Research design serves to structure the solution strategy and address the curse of dimensionality.

• 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

• Live Experiments: In cases where live experiments (trials) are involved, the model-experiment/test-model paradigm has proved useful.

• 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.

PROCESS GUIDANCE

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.

• Occasionally, there is a single, obvious, correct methodology/tool combination for answering the questions that was defined in the problem structuring process. In all other cases, a solution strategy must be defined (see figure 1, above).

• Approach Concepts:

• 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 team’s 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.

• Creating the administrative plan is part of the solution strategy.

• 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

• The output of the solution strategy process is a plan/schedule with

• Activities,

• Time of occurrence,

• Duration,

• Resource allocations, and

• Responsibilties.

• Types of activities include:

• Coordination with others,

• Tool executions,

• Data collection,

• Data reduction, and

• Report writing.

• The narrative of the study should include the following with regard to the solution strategy.

• 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.

REFERENCES

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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