Establishment and Application of Competitive Systems in mobile Devices


Published on

Published in: Business
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Establishment and Application of Competitive Systems in mobile Devices

  1. 1. Available for free online at Journal of Intelligence Studies in Business 1 (2011) 87-96 Establishment and application of Competitive Intelligence System in Mobile Devices Anass El Haddadi *,**, Bernard Dousset * and Ilham Berrada ** * IRIT UMR 5505, University of Toulouse III 118, Route de Narbonne, F-31062 Toulouse cedex 9, France, ** ENSIAS, Al BIRONI Team, University of Med V-Souissi, B.P. 713 Agdal – Rabat, Morocco Received 25 May 2011; received in revised form 22 August 2011; accepted 11 December 2011ABSTRACT: The strategy concept has changed dramatically: from a long range planning to strategic planning then to strategicresponsiveness. This response implies moving from a concept of change to a concept of continuous evolution. In our context, thecompetitive intelligence system presented aims to improve decision‐making in all aspects of business life, particularly foroffensive and innovative decisions. In the paper we present XPlor EveryWhere, our competitive intelligence system based on amultidimensional analysis model for mobile devices. The objective of this system is to capture the information environment inall dimensions of a decision problem, with the exploitation of information by analyzing the evolution of their interactions.Keywords: Competitive Intelligence, competitive intelligence systems, XPlor EveryWhere, Business Intelligence, continuousevolution
  2. 2. 881. Introduction Finally in section six a summary and evaluation of the method will be found.Companies today are faced with external risk factorslinked with an increased competition in markets that 2. The analytical models of CIare extremely dynamic and unpredictable. This iscaused by new competitors, mergers and acquisition, Through the different characteristics of CI, wesharp price cuts, rapid changes in consumption identify four dimensions in the definition of anpatterns and weak brands. In this dynamical analytical model. The four dimensions are as follows:condition the competitive intelligence system (CIS)and Business Intelligence (BI) software becomes a 1. The environmental dimension for a companymain component when companies develop their which includes elements that may influence thestrategies. Today information technology is strategy of a company. The environment isconsidered as a simple support for organizations, but characterized by partners, competitors, markets andin a strategic way it promises to contribute to a customers.sustainable competitive advantage. For five decades the concept of a strategy has 2. The human dimension which include those whochanged dramatically from being a long range are involved in the CI process, whether internal orplanning tool to become strategic planning and external to the company. The human dimension isthereafter ending up as strategic responsiveness. By characterized by networks of collaboration,embracing the responsiveness concept a company can interaction and communication between differentbe flexible and constantly evolve. A competitive actors.intelligence system (Salles, 2002) aims to improvedecision‐making in all aspects of business life, in 3. The strategic dimension corresponds to differentparticular for offensive and innovative decisions. models of analysis for the company, from To face all the challenges that appear in a identifying objectives to the decision and thedynamic industry, competitive intelligence platforms definition of actions.are designed to provide online services. CompetitiveIntelligence (CI) can be seen as both a process and a 4. The technological dimension brings together allproduct (Haags, 2006). As a process, CI is the set of the methods, tools and techniques used in the CIlegal and ethical methods that a company uses to process; Information retrieval, collection, treatmentharness information that helps them to achieve and dissemination of success. As a product, CI can beconsidered as an information system for analyzing The inclusion of one or more of these dimensions candata concerning competitors’ activities collected result in various models used for the analysisfrom public and private sources, what is also referred (conceptual or practical) of CI. We selected twoto as Business Intelligence. The results of the analysis academic models built on these dimensions: Medesiiecan provide knowledge regarding the current and model and Site model.future behavior of competitors, suppliers, customers,technologies, acquisitions, markets, products and 2.1 Medesiie modelservices, and the general business environment.When collecting data for analysis sources as The Medesiie model is a method for defining anewspaper articles, corporate publications, websites, information system for CI. The CI approach proposedpatent filings, specialized databases, information at in the project Medesiie is devoted entirely to thetrade shows and blogs can be used. The issue needs analysis of Small and Medium-sizedconcerning CI is how to build a CIS (CI as a product) Enterprises (SME) in CI. Medesiie consider a CIS asand model analysis (CI as a process). a representation of the enterprise’s knowledge. Our contribution in this paper is to propose an The conceptual architecture of this system isinformation system adapted to the needs of a CI based on the definition given by Seligman, Wijers &process. The system’s mission is to provide a Sol (1989) regarding the design of CIS. Salles, 2003methodological reference for collecting, treating and describe a CIS with four components; The way ofanalyzing information. Also an analysis of the thinking, The way of modeling, The way ofinformation environment in all of its dimensions will organizing and The way of supporting. Medesiiebe made. suggests a model to describe the company, its The rest of the paper is structured as follows: In strategy, its environment, its needs under/within thesection two we identify the analytical models of CI, CI and its products and services (Salles, 2003).with support from the Medesiie model and the Site There are different types of models that themodel. In section three we explain information Medesiie model describes. It could be a businesssystem adapted to the CI approach. Section four model, that is described according to its differentpresents our multidimensional analysis model for CI functions, for example production, economy / marketand section five presents the architecture of a CIS. linkages, financial and innovation / information
  3. 3. 89system. Each function is itself composed of a set of - Modeling the decision making by its identity,sub‐management functions. personality traits, cognitive style and experience. A strategic model is represented by a set of - Modeling the environment by the immediatestrategic choices and areas of development such as a environment with customers, providers andsearch of independence and business growth. An competitors and the global environment with forenvironment model is described initially by the example social-, economical- and political functions and the relationships it develops in - Modeling of organization, by environment, itsthe environment. The surrounding context includes signal, the assumptions that the decision‐maker canthe spatial geometry of markets, technology, infer the detection of signals collected.competition, the financial system, supply conditions,the regulatory framework, environmental policy and The WISP model, associated with the three-geopolitics. A model of needs provides a framework dimensional MEPD, is incorporating the same pointfor the collection of requirements and their of views (Kislin, 2007). The three dimensions are asformalization, analysis and validation. The expressed follows:needs are represented by a set of units’ needed. Themodel unit requirement is described in terms of three 1. An analytical dimension that includesdimensions. One, the control level of decisions for understanding the demand‐stake‐context, thewhich the units are expressed (value: operational, definition of informational indicators, thetactical or strategic). Two, the phase of the decision‐ operations of analysis and creation of knowledgemaking process associated with the unit and three, its can be achieved by studying the stored elements.informational content (identification of its value and 2. A methodological dimension is incorporated atfunction). The last example of Medesiie’s models is two levels. The first level regards the skills ofa model of products/ services. Any supply of decision transaction of the decision problem in themaking bearing the environment of a company is a information problem. The second level regardsprototyping tool made according to the collected strategies by which the information is identified andneeds, the cost defined, reached and powered to knowledge is acquired.evaluate the effects a priori. 3. An operational dimension to define the selection of an action plan and implement the various stages2.2 Site model of resolution for the methodology associated with the model WISP.The Site model includes different models of CI,proposed by the research team Site‐Loria. These 3. Information systems adapted to the CImodels are based on the linking of three spaces: the approachspace of decision problems, the space of theinformational problems and the space of mediations. For Romagni and Wild (1998) the definition of anThe three spaces are connected through exchanges information system adapted to the CI approach is anbetween the two types of actors, the decision‐maker organized set of procedures, at any time, to giveand the watchman. decision makers a representation of a company in its Teamwork is important, thus the inclusion of environment and market. The CI function providesthe user in the information systems is important. information to assist in executive functions,They propose models to define the different actors, management and decision‐making. It must facilitatetheir interactions and their positioning in the CI decisions to automate a number of actions orprocess. providing decision makers with the necessary We have retained the following three models: information for decision‐making. It must alsoEquAte (Explore Query Analysis annotated), MEPD coordinate the processing of information, store(Model for the Explanation of a decision problem) sustainably information and improve data processingand WISP (Watcher‐Information‐Search‐ Problem). the creation of information directly applicable for The EquAte model represents a situation of decision makers.information retrieval which implies the following The majority of current information systems arecognitive phases (David & Thiery, 2002): inadequate to manage the dynamic markets. They are mostly designed for stable and controlled - Exploring the word of information environments and are built on vertical and complex - Querying the information base organizational patterns. These types of information - Analysis of the information base systems do not meet the needs of a CI process. It is - Annotation based on individual preferences therefore essential to develop information system that enables organizations to better manage informationThe MEPD model defines different steps for a and provide a base for coordination of actionsdecision making problem that is based on (Bouaka, between different actors. This coordination is2004): supported by the following motivations:
  4. 4. 90 -The goals of the CI approach are interrelated and The coupling between the needs are identified in a cannot be led separately process of CI which include different collaborative -The need for information sharing between techniques from business intelligence such as different actors workflow, groupware, data warehousing, data -The sharing of knowledge gained during a process mining, text mining and visualization. This optimizes -The organization of the company in a cross‐ each step in CI process. (Figure 2). It summarizes all functional manner. of these techniques for each step in the CI process. The collection phase is usually through the use of Figure 1: Transaction from a hierarchical structure to a functional global information infrastructureDue to the above mentioned motivations it’s databases, internet, search agents and search engine.important to move from a vertical architecture of The steps of processing can be supported byinformation systems to a cross‐architecture which visualization tools, statistical analysis and dataallows the information to reach the management warehouses. The diffusion step may rely on foroverall. example push‐pull agents and emails. The cross‐architecture is based on a modular andscalable architecture structured around the projects ofa company. The global information infrastructure willenable us to: - Reduce the number of vertical coordination by reducing management layers - Improve environmental monitoring - Opening‐up of cross‐communication - Achieve relationships based on complementary businesses, and - make a better adaptation to market dynamics.According to the report of Cigref “Competitiveintelligence and strategy” (2004) a portal ofinformation management is currently the best tool toimplement the concept and the culture of CI througha network. This portal is built around a softwaresolution called here CI. The advantages of this typeof information system are: Figure 2: The various techniques of CI - Project management monitoring - Information sharing - Custom-made interface - Collection that is more accurate and targeted - Processing, analysis, storage - Dissemination
  5. 5. 914. Xplor: a multidimensional analysis model forCIOur contribution consists of a proposal for aninformation system adapted to the needs of a CIapproach as define above. The objective of thissystem is to provide a reference methodology inorder to collect, process and analyze information. Oursystem will observe and analyze the information of adecision problem in all dimensions. The approachcombines two methods: Knowledge discovering intext (KDT) and environmental scanning. Table 1: Question 5W-1H (Ghalamallah, 2009) Figure 3: Coupling of Environmental scanning and We define this step by the method 5W‐1H: “What, KDT (Ghalamallah, 2009) Why, Who, When, Where, How”. Jakobiak (2006) developed a systemic approach for the creation of aThe model described is based on two main models: CI project based on the 5W‐1H method (Table 1). The principle of the 5W‐1H is based on following 1. A multidimensional representation of circumstances, the person, the fact, the place, the documents which can transfer qualitative data into means and reasons, the manner and the time. In this quantitative. The objective of this model is to get way a company can provide a detailed analysis plan a unified view of the documents collected. for the CI project. 2. A function model which aims to provide a set of generic and combinatory functions to build a different kinds of indicators needed for analysis.The CIS proposed should manage the sharing ofinformation between the different actors involved.The objective is to define a space of communicationand information dissemination to provide a platformfor collaboration and cooperation between differentstakeholders. For this we define a user model adaptedto each user profile.4.1 Planning activityThe first activity of the proposed processes isplanning. It is established from the informationalproblem defined by the users. The objective of thisactivity is to describe the process of guiding analysis. Figure 4 : Lifecycle of Xplor model
  6. 6. 92We adapt this principle to describe the information Once all sub‐activities associated with theneeded and to guide the exploratory analysis. activity of planning are completed and validated, theOriginally, the proposal for the question How was to results will be stored for later use.describe the procedures and actions to realize when We define an information need by grade of Nthe project is implemented. In the context of our Where A need N is defined as follows:process, the question How will describe the indicatorsto be implemented to meet the raised informational N = < SA, ObjA, IndA, ActA, AttA>problems. The products of the planning steps are: -SA : is the overall context of the need for analysis A, -ObjA = < Obj1, Obj2, …, Objm >, represents the objectives set for the subject SA. -IndA = {< Obji, < Indi1, Indi2, …, Indin >>}, represents the indicators associated with each objective. -ActA = {< Indij, < Actij1, Actij2, …, Actijp >>}, represents the actors identified for indicators set for a goal. -AttA = {< Actijk, < Attijk1, Attijk2, …, Attijkq >>}, represent the attributes specified each actors. Table 2: The products of the planning step We define a hierarchy of concepts associated with theIn the planning phase an informational problem is decomposition of indicators (Figure 5). Once all subdescribed. This problem will be identified by the activities associated with the activity of planning aredefinition of its subject analysis. Once the subject is completed and validated, the result will be stored fordefined, the user must identify the themes of analysis, later use.plan analysis operations and identify the involvedactors. The validation of the themes of analysis leadsthe user to define two key activities for each topic,such as source of information and a definition ofanalysis indicators. To enable an analysis, it’s necessary toidentify sources of information. The activity ofindentifying consists in listing any formal andinformal sources that may contain importantinformation about the subject for the study (ElHaddadi, Dousset, Berrada & Loubier, 2010).4.2 Indicators for analysisThe objective of this activity is to define indicators tobe calculated and assessed. These indicators areintended to summarize and interpret the informationenvironment of the analysis. At this level of activity we must introduce thedifferent indicators related to the theme. Eachindicator was analyzed in order to identify targetattributes, their granularity, their values and their Figure 5: Hierarchy of concepts associated with therelation. The aim of this decomposition is to clarify specification requirementsand describe the objects manipulated duringprocessing to meet the indicator requirements. Each 4.3 Multidimensional representation of documentsobject of this decomposition will guide us throughthe various activities of the proposed process. The objectives of this structure are to study the evolution of interactions between variables and make
  7. 7. 93projections in the future which is essential for makingstrategic decisions. Our proposal is to define a unique structure ofintermediate data between raw information andknowledge derived in the form of a generic datawarehouse. The multidimensional structure is basedon a three dimensional modeling. This allowsdefining dependency relationships between differentelements of the mining structured corpus, body ofvariables, with the inclusion of timing, that is thetime variable (Figure 6). Figure 7: Data Cube The Cube can describe existing relationships in a corpus period. We identify two types of Cubes: 1. A symmetric matrix: If we consider the simultaneous terms of a single variable and the time variable in a document the Cube becomes symmetric. 2. A asymmetrical matrix: Where we consider the presence of two distinct variables and the time variable in a document the Cube becomes asymmetric. Figure 6: Example of dependency within three- dimensional material and the temporal element A corpus whose formal structure extraction is defined as:For a corpus of documents whose structure extractionis: Extrac Extrac StructureGlobal = < Chp1G , …, ExtracStructureGlobal Extrac= < N° Doc, Date, Author, ChpiG , Extra Journal,Country, Keywords, Organism > …, ChpjG >, ExtracWe propose to build a three dimensional matrix ChpiG corresponds to the element i of thewhich will define the dependency relationships that structure. We define the types of three‐dimensionalexist between the variables of the body by matrixes between elements of the structure as insystematically incorporating the time variable. Table 3.Principle: Our goal is to identify the dependentrelationships that exist in the body between thedifferent variables of the study. These relationshipsare defined by a co‐occurrence matrix. Thesematrixes indicate the simultaneous presence of theterms of two qualitative variables in a document. Weadopt these matrixes by adding a third variable. Thefirst two variables are qualitative associated with amultidimensional corpus.The third variable is always the time associated withthe corpus, for example date and year. Thus, the co‐occurrence matrix is to indicate the presence of these Table 3: Type of matrixthree variables in a document (three‐dimensionalstructure). We call this matrix a Cube.
  8. 8. 94We define the corpus associated with the dimensions appear simultaneously.multidimensional cube as: ijT i ij ijT Atto = Di x Dj x DT [Attx , Atty , Attz ] et The structure of the multidimensional corpus (3D) ijT Atto >= 1 SCM3D defined as: ijT SCM3D = {< Dimi, Dimij, DimT, NbDoc >} 5. XPlor Everywhere : Competitive intelligence system for mobile The multidimensional corpus CM3D defined as: i ij ijT ijT CM3D = {< Attx , Atty , Attz , Atto >} Xplor EveryWhere is a CI platform that performs global strategic analysis on aggregate or factual With: entries from online bibliographic databases, CDRom, Internet or any other computerized source. Through i i descriptive and statistics exploratory methods of data, - Attx ∈ Di the set of attributes {Att1 , …, Xplor EveryWhere display in a very short time new i Attp } in Dimension i « Dimi », strategic knowledge such as the identity of the actors, ij j - Atty ∈ Dj the set of attributes {Att1 , …, their reputation, their relationships, their sites of j action, their mobility, emerging issues and concepts, Attq } in Dimension j associated with the dimension I i «Dimij », terminology and promising fields. ijT T - Attz ∈ DT the set of attributes {Att1 , …, T Attr } in Dimension time « DimT », ijT Nb - Atto ∈ NbD the set of attributes {Att1 , …, Nb Attl } the number of documents in the three Figure 8: Xplor Everywhere Intelligence Process5.1 System architecture of Information Fusion in the Xplor CI platform. The architecture of our platform consists of four mainAs shown in figure 8, strategic analysis and services as shown in figure 9:surveillance are the basic methodology of the process
  9. 9. 95 ease the navigability of the strategic information, we intend to integrate specific visualization techniques to each type of request like evolutionary histograms, geographical charts, social networks, profile networks, semantic networks and international networks (Figure 10): Figure 10: Reporting service of Xplor Everywhere It is possible to navigate among three different types of networks. The social networks are based on Figure 9: Xplor Everywhere Architecture relationships among the different authors, inventors, research teams, companies and the evolution of their relations. The semantic networks contain 1. Monitoring Service: A request is generated relationships among keywords in a domain and the on a data source like a scientific database, evolution of research topics. The international patents database, RSS and blogs to collect networks are built on international collaboration data depending on client’s needs. The between countries. collected data form the corpus. 6. Conclusion 2. Homogenization and structuring Service: Diversity of data sources leads to In this paper, we present a competitive intelligence heterogeneous data, format and language system tool based on a multidimensional analysis must be restructured. At the end, this service model. A lot of strategic information comes from the defines a unified view of documents in the relationship between and relevance of knowledge corpus. extracted, which often depends on consideration of data evolution and their interactions. In this paper we 3. Reporting Service: Reporting is the service have defined a model for these relationship forms. responsible for presenting the analysis Our CIS is dedicated to cover all stages of results to the decision‐makers according to discovery, extraction and data management: Without the push strategy with IPhone Service (El forgetting the criteria by which we get to handle any type of information, both formal and informal. With Haddadi, Dousset & Berrada, 2010), SMS Xplor and Xplor EveryWhere, which are still mdeos Service, and E‐mail Service or pull strategy but potentially soon to be commercialized, we with Web Site Services. completed an entire reporting service, including the 4. Security Administration Service: Orthogonal aspect of mobility (smartphone application). With the to all three mentioned services, this Service system it’s possible to view updated information as controls data access and ensures the we gain access to strategic database servers in real‐ preservation of privacy during the time and daily feeds by observers. With this treatments (Hatim, El Haddadi, El Bakkali, application it is now easy to enter information at Dousset & Berrada, 2010). trade shows, after customer visits or meetings. Our plan for future studies is to continue our5.2 Reporting service experiments on different types of relationships in order to propose a unified model to better generateThe reporting is the last, important service to be and organize knowledge for companies.accomplished in the CI process. On this level wepropose four types of services, the Phone Service, theSMS Service, the Web Site Service and the E‐mailService. With these different services, it is possible toaccess strategic information anywhere. In order to
  10. 10. 96References Seligman P.S., Wijers G.M., Sol H.G. 1989. Analyzing the structure of I.S. methodologies, anBouaka, N. 2 0 0 4 . Développement d’un modèle alternative approach, In proceedings of the pour l’explication d’un problème décisionnel : Conference in information systems, The un outil d’aide à la décision dans un contexte Netherlands. d’Intelligence Economique. Thèse de doctorat de Vedder R. G., Vanecek M. T., Guynes C. S. and l’université Nancy 2. Cappel J. J. 1999. CEO and CIO Perspectives onEl haddadi, A., Dousset, B., Berrada, I., & Loubier, I. Competitive Intelligence, Communications of the 2010. Les multi‐sources dans un contexte ACM, 42, 8. d’Intelligence Economique, EGC, P A1‐125 A1‐ 136.El haddadi, Dousset, B., & Berrada, I. 2010. Xplor everywhere – a tool for competitive intelligence on the web and mobile, VSST. 25‐29 Octobre, Toulouse France.D a v i d , A . & Thiery, O. 2002. Application of “EQuA2te” Architecture. Economic Intelligence.Ghalamallah, I.. 2009. Proposition d’un modèle d’analyse exploratoire multidimensionnelle dans un contexte d’intelligence economique,doctorat de l’université de toulouse, 18 décembre.Gilad, B. 2008. The Future of Competitive Intelligence, Contest for the Profession’s Soul, Competitive Intelligence Magazine, 11(5), 22.Haags, S. 2006. Management Information Systems for the Information Age, McGraw‐Hill Ryerson.Hatim, H., El haddadi, A., El bakkali, H., Dousset, B. & Berrada, I. 2010. “Approche générique de contrôle d’accés aux donénes et aux traitements dans une plate‐forme d’intelligence économique“, colloque Veille Stratégique et technologique.Jakobiak, F. 2006. Lintelligence économique: la comprendre, limplanter, lutiliser. Les éditions d’organisation.Kislin, P.H. 2007. Modélisation du problème informationnel du veilleur dans la démarche d’intelligence économique. Thèse de doctorat de l’université Nancy 2, France.Rapport Cigref. 2004. Club Informatique des Grandes Entreprises Françaises, Intelligence économique et stratégique. Rapport Cigref.Romagni, P., Wild, V. 1998. LIntelligence économique au service de lentreprise, ou linformation comme outil de gestion. Les Presses du Management.Salles, M. 2002a. Projet MEDESIIE : Méthode MEDESIIE de définition du besoin en intelligence économique des PME, Touluse: Université Toulouse I.Salles, M. 2003b. Modélisation des situations de décision dans une méthode dingénierie du besoin en I.E, Conférence IERA, Intelligence Economique : Recherches et Applications, Nancy, France. Salles, M. 2005c. De lanalyse du besoin des PME en IE à lIntelligence Territoriale. Colloque Européen dIntelligence Economique, Poitiers Futuroscope, ESCEM Poitiers, p. 414‐427, Poitiers, France.