A Competitive Intelligence framework to support decisionmaking based on Rough Set Theory

Abstract

Given the increasing complexity of the economic context, it is important for each company to master information and build a robust strategic planning process. Competitive Intelligence (CI) is important for companies to manage their information. CI identifies opportunities and determinants of success, anticipates threats and prevents risks. CI becomes an imperative for any company wishing to sustain its growth and innovation sustainably. In addition, decision-makers have a key role to play when making decisions, some of which can have a significant impact and therefore justify the effort to reflect and deliberate on possible options before making a decision. Strategic decisions can be defined as important and far-reaching decisions in terms of actions taken, resources committed, number of actors involved and impact on all future operations. Our answer to this challenge is an approach that uses Rough set theory. Our approach is designed to support decisionmaking and respects the characteristics of strategic decision support in complex, uncertain and evolving situations. Rough set theory can effectively process data and information in complex system. In this article, we propose a CI approach where we used the rough set theory to generate rules in order to help decision makers make a decision in a complex and multi-criteria situation and under a context of uncertainty. We applied our model on the choice of implementation of an Enterprise Resource Planning (ERP) within the company.