BSC-SI: A Framework for Integrating Strategic Intelligence in Corporate Strategic Management

BSC-SI: A Framework for Integrating Strategic Intelligence in Corporate Strategic Management

Mouhib Alnoukari (Damascus University, Damascus, Syria), Rakan Razouk (Damascus University, Damascus, Syria) and Abdullatif Hanano (Damascus University, Damascus, Syria)
DOI: 10.4018/IJSODIT.2016070101
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Integration of Strategic Intelligence with corporate strategic management is becoming of vital importance for modern and flexible organizations in the last few years. The main achievement of this integration is to help decision makers to implement systemically their corporate strategies, adapt easily to changes in the environment, and gain competitive advantages. In this article, the authors will extend the studies in this domain, and clarify the relationships between Business Intelligence, Competitive Intelligence with Strategic Intelligence. They will also explain the impact of Business Intelligence on Corporate Performance Management, Operational Business Process, Competitive Intelligence, and Strategic Intelligence. Finally, the authors will explain the new proposed framework BSC-SI that can facilitate the integration of Strategic Intelligence with Balanced Scorecard methodology.
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Business Intelligence (BI) was introduced by Dresner in the year 1989, as an umbrella term that “describe a set of concepts and methods to improve business decision making by using fact-based support systems” (Power, 2007). BI is an IT framework that helps organizations managing, developing and communicating their information and knowledge. Thus, BI can be considered as an imperative framework in the current knowledge-based economy arena (Alnoukari, 2012). BI is an environment in which ‘marrying’ between business knowledge with data mining would provide great results (Anand, Bell, and Hughes, 1995; Cody, Kreulen, Krishna, and Spangler, 2002; Weiss, Buckley, Kapoor, and Damgaard, 2003; Graco, Semenova, and Dubossarsky, 2007). Some researchers consider business intelligence as an umbrella that combines: architectures, tools, data bases, applications, practices, and methodologies (Turban, Aronson, Liang, & Sharda, 2007; Cody, Kreulen, Krishna, & Spangler, 2002; Rouhani, Asgari, & Mirhosseini, 2012). Weiss et al. 2003 defined BI as the: “Combination of data mining, data warehousing, knowledge management, and traditional decision support systems” (Weiss, Buckley, Kapoor, & Damgaard, 2003). BI systems can have multiple benefits including: faster access to information, particularly big data complexes, increasing revenue, better customer satisfaction and generate or improve competitiveness of enterprises (Brinkmann, 2015).

Dedijer considers that Knowledge Management emerges in part from the thinking of the “Intelligence Approach” to business. Dedijer thinks that “Intelligence” is more descriptive than knowledge. “Knowledge is static, intelligence is dynamic” (Marren, 2004)., Luhn defines intelligence as: “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.” The main challenging part in any business intelligence solution is in its intelligence ability. This can be found in the post data mining phase where the system has to interpret its data mining results using visual environment (Alnoukari, 2012). We can measure the capability of any business intelligence solution by its ability to derive knowledge from data (Azevedo & Santos, 2009). The challenge in any BI solution is to meet with the ability to identify patterns, trends, rules, and relationships from volumes of information which is too large to be processed by human analysis alone (Alnoukari, 2012). In summary, BI is “the use of all the organization’s resources: data, applications, people and processes in order to increase its knowledge, implement and achieve its strategy, and adapt to the environment’s dynamism” (Alnoukari et al., 2008). Competitive advantage has shifted from companies that focus on implementing new technologies to those that employ technology to share, manage, and increase the level of knowledge inside the organization (Brinkmann, 2015). BI and analytics evolutions started by DBMS-based and structured content, evolved into web-based and unstructured content, and currently based on mobile and sensors contents (Chen, Chiang, & Storey, 2012).

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