Abstract

Given the complex and disruptive open-ended dynamics in the current dynamic global environment, senior management recognizes the need for a formalized, consistent, and comprehensive framework to analyze the firm’s strategic posture. Modern assessment tools, such as H. Igor Ansoff’s seminal contributions to strategic diagnosis, primarily focused on identifying and enhancing the firm’s strategic performance potential through the analysis of the industry’s environmental turbulence level relative to the firm’s aggressiveness and responsiveness of capability. Other epistemic modeling techniques envisage Porter’s generic strategic positions, Strengths, Weaknesses, Opportunities, Threats (SWOT), and Resource-Based View as useful methodologies to aid in the planning process. All are complex and involve multiple managerial perspectives. Over the last two decades, attempts have been made to comprehensively classify the firm’s future competitive position. Most of these proposals utilized matrices to depict the position, such as the Boston Consulting Group, point positioning, and dispersed positioning. The GE/McKinsey later enhanced this typology by expanding to 3 × 3, contributing to management’s deeper understanding of the firm’s position. Both types of assessments, Ansoff’s strategic diagnosis and positional matrices, are invaluable strategic tools for firms. However, it could be argued that these positional analyses singularly reflect a blind spot in modeling the firm’s future strategic performance potential, as neither considers the interactions of the other. This article is conceptual and takes a different approach from earlier methodologies. Although conceptual, the article aims to present a robust model combining Ansoff’s strategic diagnosis with elements of the performance matrices to provide the management with an enriched capability to evaluate the firm’s current and future performance position.

Highlights

  • There are few studies in the area of analyzing the strategic decision-making process

  • The present study emphasizes the development of key determinants for assessing the performance or strategic classification of various firms

  • The advantage of Support Vector Machine (SVM) is the approximation mechanism that avoids the complexity on tuning the parameters such as in Neural Networks, maps the original attributes into a function space, namely, the feature space

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Summary

Introduction

There are few studies in the area of analyzing the strategic decision-making process. The Optimal Strategic Performance Positioning (OSPP) matrix is designed to provide managers with specific measurable data on areas of the firm that require additional resources to improve its strategic positioning.

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