Abstract

Many nations’ defence departments use capabilitybased planning to guide their investment and divestment decisions. This planning process involves a variety of data that in its raw form is difficult for decisionmakers to use. In this paper we describe how dimensionality reduction and partition clustering are used in the Canadian Armed Forces to create visualizations that convey how important military capabilities are in planning scenarios and how much capacity the planned force structure has to provide the capabilities. Together, these visualizations give decisionmakers an overview of which capabilities may require investment or may be candidates for divestment.

Highlights

  • Prior to the end of the Cold War, many defence departments based their strategic planning process on the threat–based planning paradigm (NATO Re-search and Technology Organization, 2003)

  • In this paper we describe how the visualization approach is used in the CAF current Capability-Based Planning (CBP) system

  • Similar to Rempel (2012), we use dimensionality reduction and partition clustering to visualize the importance of capabilities, we extend this approach by using these methods to visualize the planned force structure’s capacity and apply algorithms to select which dimensions and how many clusters to use in the visualizations

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Summary

Introduction

Prior to the end of the Cold War, many defence departments based their strategic planning process on the threat–based planning paradigm (NATO Re-search and Technology Organization, 2003) This paradigm is generally equipment– centric and tends to create capabilities designed for operations in a single environment. The remainder of this paper is organized as follows: Section 2 describes how the importance of capabilities and the planned force structure’s capacity to provide them are assessed in the CAF current CBP process; Section 3 presents a description of the dimensionality reduction and partition clustering techniques used; Section 4 discusses an example application; and Section 5 presents a conclusion

Capability and Force Structure Assessment
Methods
Partition Clustering
Example
Visualization
Conclusion

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