Developing SWOT Analysis from Customer Satisfaction Surveys

Abstract

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis is one of the most commonly used tools for strategic planning. It helps organizations gain a better insight of their internal and external business environment when making strategic plans and decisions. Although SWOT analysis has been widely accepted as a tool for strategic planning, the traditional method of conducting SWOT analysis does not prioritize and is likely to hold subjective views that may result in an improper strategic action. One way to make better use of the SWOT framework is to take the customer's perspective in to account which helps the companies to ensure that their perceived capabilities are also recognized and valued by their customer. This work proposes a combination of Back Propagation Neural Network based Importance-Performance Analysis (BPNN-IPA) and SWOT analysis. The 'Importance' is derived by applying BPNN on a customer satisfaction survey and 'Performance' is computed as the mean value of customer's satisfaction rating. The intersection of these two components creates a two-dimensional matrix termed, IPA matrix, which can be identified as strengths and weaknesses of the company. Base on the same principle, opportunities and threats are obtained through the IPA matrix of the company's competitor. The BPNN-IPA yields significant improvement in estimating of attribute importance compared to conventional IPA and regression-based IPA approach, thereby generating effective SWOT analysis. It is expected that this approach will provide more accurate information for strategic planning as it generates prioritized SWOT factors based on the customer's perception.