Using DSS for Global Competitiveness: An Effective Information-Based Decision Making Process in...

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Yi-chen LanUniversity of Western Sydney, Australia

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Global information society : operating information systems in a dynamic global businessenvironment / Yi-chen Lan, Editor.

p. cm. Includes bibliographical references and index. ISBN 1-59140-306-5 (hc) — ISBN 1-59140-307-3 (sc) — ISBN 1-59140-308-1 (ebook) 1. Information technology—Management. I. Lan, Yi-chen, 1969- HC79.I55G549 2005 658.4’038’011—dc22 2004023597

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Using DSS for Global Competitiveness 113

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Chapter VI

Using DSS for GlobalCompetitiveness:

An Effective Information-BasedDecision Making Processin Public Administration

Sherif KamelThe American University in Cairo, Egypt

Ahmed ZyadaMiddlesex University-Regional IT Institute, Cairo, Egypt

Abstract

With a changing global environment driven by the innovative evolutions ofinformation and communication technology, organizations are setting theirpriorities to cater to a global marketplace. In that respect, they are focusingon adding value propositions to different data and information elementsgathered to help know more about customers and various environmentswhere products and services are manufactured and traded. Thereforeorganizations continuously need to increase their business intelligence bymonitoring systems that analyze information and develop indicators coupledwith support mechanisms to decision makers to handle semi-structured andun-structured problems characterized by varying alternatives andparameters to understand the problem spectrum and help develop alternativesolutions. This chapter discusses concepts and characteristics of decision

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114 Kamel & Zyada


support methods and demonstrates the gap between the decision maker andthe decision support systems techniques demonstrating the experience ofthe government of Egypt in building its information infrastructure to helpdevelop the decision-making process both at the government level and thelocal public administration level.

Background

Organizations continuously need to increase their business intelligence bymonitoring systems that analyze information and developing indicators that arecoupled with support mechanisms to decision makers to handle various types ofdecision problems characterized by varying alternatives and parameters tounderstand the problem spectrum and help develop alternative solutions. Theobjective is always to remain competitive and adapt to local and global organi-zational and market changes. Decision support systems (DSS), commerciallycalled business intelligence (BI) solutions, represent powerful tools capable ofenhancing the capabilities of managers in facing challenges, especially at timesof continuous change. It helps improving decisions by providing accurate andrelevant information and also supports in saving time. It also helps build aknowledge repository that can help understand the marketplace and competemore effectively. Business intelligence, which has a broader concept than datawarehousing, is an essential component of the overall strategy of differentorganizations in a world much affected by globalization and where culture,change, competition, and technology represent influential forces in driving thedecision-making process. It is important to note that data warehousing increasesthe decision-maker capabilities in a passive way due to its dependences onhistorical data; however, business intelligence helps in projecting the future to beable to set the appropriate tactical and strategic plans in a more active way andhence realize organizational objectives. Business intelligence definitely bringscompetitive advantages to the organization in the time of globalization. Itsimportance is in the forward and future projection of the needs of the organiza-tion. Strategies of the future nowadays represent the platform to decide theactions of today, and business intelligence helps to do that. Therefore the moreit is used in strategy development, the more likely it can survive, grow, andcompete.Little (1970) defines decision support systems as a model-based set of proce-dures for processing data and judgments to assist a manager in his decision-making processes. He argues that to be successful, such a system must besimple, robust, easy to control, adaptive, complete on important issues, and easyto communicate with. Early definitions of DSS identified it as a system intended



to support managerial decision makers in semi-structured and un-structureddecision situations acting as tools to decision makers to extend their capabilitiesbut not to replace their judgment. The human interface in the decision supportformula is invaluable and an integral complementing element to the computer-based outcome. DSS are computer-based applications that operate interactivelyonline and preferably would have graphical output capabilities. As for businessintelligence tools, which are DSS for the business context, they were introducedto overcome the problems raised from disintegrated information clusters comingfrom different sources. Business intelligence tools add value to corporateinformation through sophisticated analytical processing and rapid delivery andpresentation of accurate information to executives, managers, analysts, andother knowledge workers. Its data sources vary both internally (data-ware-house, data mart, transaction processing applications, and expert staff opinionsand recommendations) and externally (market research and survey data). Thedevelopments and the historical path are demonstrated in Figure 1. It is importantto note that while business intelligence is more deployed in business organiza-tions, decision support systems are more available in government organizationsand public administration.

Decision Support Systems

Organizations are increasingly in search of effective vehicles that can help themincrease their benefits of stored data within the organization and transform such

Figure 1. Development of management support systems

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data into information and knowledge. There is always a need to explore themarketplace, the competition, and the economic environment among otherconstituencies in the community and to possess the mechanism and the internalbusiness intelligence that can transform the knowledge of the society into inputsthat can help formulate the organization’s strategy. Such knowledge affects thebusiness and organizational decision-making process at all levels. It also contrib-utes to the organizational knowledge that is compiled from both internal andexternal sources. From day-to-day business tasks to the major strategic issuessuch as taxation policy and long-term business planning, information is requiredthat is timely, accurate, and effective for the overall business decision process.In that respect decision support systems help decision makers generate alterna-tives and choose among the optimal course of action that can help attain thebusiness goals (Kamel, 1998). The role of information experts and humaninterface will remain invaluable to assess the variable in the marketplace that canaffect the performance of the organization.DSS applications are designed, delivered, and institutionalized in differentsectors and industries such as the health sector, tourism, petroleum, banking, andagriculture, among others. The usefulness of such applications varies in solvingproblems. They are not all equal in solving problems or in supporting decision-making processes where some of them are more intelligent than others in termsof quality and response time, which brings the concept of intelligent density,which is a scale for these systems to solve problems or to support decisions. Theintelligent density concept; therefore, provides the decision maker with a rankingmechanism so whenever he/she has a problem or needs a support, then there isa need to select a tool based on the most intelligent capacities available. Suchcapacities also change and adapt from time to time according to the case in hand;that is, it could be viewed as a one-time system with many variables to be adjustedand adapted.Some other definitions include Simon (1977), who mentions that managerialdecision making is synonymous with the whole process of management; Little(1970), who claims that it is a model-based set of procedures for processing dataand judgments to assist a manager in his decision making; and Keen (1980), whoclaims that DSS apply to situations where a final system can be developed onlythrough an adaptive process of learning and evolution (Turban & Aronson,2001). The decision-making process is also bound to the changes in themarketplace, and that is why it usually goes through the design, development,implementation, and institutionalization phases with continuous adaptation. Un-less such adaptation takes place, more problems occur because of dissatisfactionof the decision maker, who attempts to reach a process that can help him makethe most optimal decision. The institutionalization process is a continuous processthat allows for regular changes to fit the environment, whether internal orexternal. The problem identification process also includes and is complemented



by the problem classification and decomposition. It is important to note that thenature of the problem could vary from totally structured to semi-structured tounstructured. This actually defines and forces the information system model to beused to handle the problem and the challenge faced by the decision maker. In theproblem decomposition phase many problems and issues could be divided into subproblems. In that respect, there are three phases of the decision-making process.

Phase I – Intelligence Phase

This phase is concerned with gathering information from different sources andbeing aware of occasions when a decision is required, routinely collectingknowledge relevant to the business area, and classifying and storing it. Theintelligence phase focuses on the identification of organizational goals andobjectives related to an issue of concern, such as inventory management anddetermining whether they are being met. The intelligence phase relies onextensive quality information. Information about the market, competition, andpotential new products, services, and elements affecting the decision makingprocess are essential for survival and growth.

Phase II – Design Phase

This phase handles the full understanding of the problem and is concerned withdesigning, developing, and analyzing various solutions. The feasibility of possiblesolutions and a model of the problem is built and tested. This can be implementedby accessing information, generating business models, and using communicationmechanisms to readily share and consolidate results and identify the bestsolution. Comparative analysis reports and mapping between different scenariosis essential. Moreover simulation models enable the decision maker to experi-ment, to try different scenarios to determine the most feasible solutions affectingdifferent decisions and business processes.

Phase III – Choice Phase

This phase reflects the selection among the different alternatives. Numerousfeedback and alternatives are being discussed, and it is up to the decision makerwith his support aids to aim for the optimal solution. It is important to note thatsome problems have one clear solution agreeable to all involved, but it is oftenthe case that a lot of allowable solutions exist, and the choice or selection are notquite easy. This phase, supported by modern presentation tools, help the entireteam to choose the solution.

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Decision Support SystemsCharacteristics and Capabilities

It is important to mention that decision support systems characteristics andcapabilities include: (a) providing support to several interdependent and/orsequential decisions, (b) supporting a variety of decision-making processes andstyles, (c) adapting over time where the decision maker should be reactive, ableto confront changing conditions quickly, and able to adapt the DSS to meet thesechanges, (d) supporting various managerial levels, ranging from top executivesto line managers, and (e) supporting individuals as well as groups with lessstructured problems.

Decision Support System Application

Decision support systems application, mainly targeting senior executives andchief executive officers, could be composed of the following subsystems (a) datamanagement subsystem, which includes a database that contains relevant datafor the case analyzed and is managed by a software (database managementsystem) that could be connected with the corporate data warehouse; (b) modelmanagement subsystems, which are a software package that includes financial,statistical, and other quantitative models that provide the system’s analyticalcapabilities and appropriate software management as well as modeling languagefor building custom models; (c) knowledge-based subsystem that providesexpertise in solving complex unstructured and semi-structured problems throughthe use of expert or other intelligent systems; (d) user interface including allcommunication between a user and the DSS software through graphical userinterfaces; and (e) users who are different including managers, decision makers,knowledge workers, business analysts, and staff.

Decision Support Systems Classification

Pending the nature of information and knowledge required, decision supportsystems could be identified and classified as follows: (a) text-oriented DSS, (b)database-oriented DSS, and (c) model-oriented-DSS. With respect to text-oriented DSS, information (including data and knowledge) is often stored in atextual format and accessed by decision makers. A text-oriented DSS supportsdecision makers by electronically keeping track of textually represented infor-mation that could have a bearing on decisions. It allows documents to be



electronically created, revised, and viewed as needed. Information and commu-nication technology such as Web-based, document imaging, hypertext, andintelligent agents can be incorporated into text-oriented DSS applications. Withrespect to database-oriented DSS, the database organization plays a major rolein the DSS structure. Early generations of database-oriented DSS mainly usedthe relational database configuration. The information handled by relationaldatabases tended to be huge, descriptive, and rigidly structured. A database-oriented DSS features strong report generation and query capabilities. Withrespect to spreadsheet-oriented DSS, a spreadsheet represents a modelinglanguage that allows the user to write models for analysis. Such models not onlycreate, view, and modify descriptive knowledge but also instruct the system toexecute its self-contained instructions and is effective support for end user-developed DSS such as Excel and Lotus.Based on the theoretical overview, following is the experience of a developingnation, Egypt, in developing its national information infrastructure and theutilization of decision support systems in attempting to solve its socio-economicproblems as well as render the business community more aware and sensible tothe massive support, accurate, timely, and relevant information could introduceto the business sector and help it compete globally.

Building Egypt’s Information Society

Egypt is home to more than 70 million people and growing at an estimated rateof 1.9% (www.mcit.gov.eg). Egypt is one of the largest economies in the MiddleEast. The nation’s current economic growth rate stands at 3.1% annually withan inflation rate of 6% (www.economic.idsc.gov.eg). It is undergoing privatizationand liberalization of a number of its major economic sectors. Although thepopulation is settled on only 4% of its land, which extends to around 1 millionsquare kilometers, infrastructure development and extension reaches all 26different provinces. Infrastructure is growing in two directions, horizontally toprovide the basic needs of the society and vertically to keep pace with thedevelopments taking place worldwide in different sectors, including informationand communication technology. Egypt has a large service sector mainly builtaround tourism and transportation. Its major exports are human resourcecapacities, petroleum products, cotton, and leather products; its major importsare food, machinery, and vehicles. Agriculture accounts for nearly 16% of thegross domestic product, industry 35%, and services 49% (www.mcit.egov.eg).Information technology has been identified by the government of Egypt since themid 1980s as a potential player and a platform for growth.

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In 2001, the information technology market was valued at 849 million U.S. dollarswith an annual growth rate of 16.3% and by 2004, the value of the market isexpected to reach 1.315 billion U.S. dollars with a compounded average growthrate (CAGR) of 16.1% from 1998 (American Chamber of Commerce in Egypt,2002). It is important to note that although information technology came to Egyptin the early 1960s, it was only in September 1999 that it was featured extensivelyon the agenda when the government of Egypt took a major step toward thedeployment of information and communication technology for socio-economicdevelopment following the earlier steps and projects that had started since themid 1980s. In that respect, the ministry of communications and informationtechnology were established. Moreover a three-year national ICT plan wasformulated that addressed the following issues: upgrading the current telecom-munications infrastructure to build an effective and accountable infrastructurethat can provide Egypt and the Middle East and North Africa region with reliable,effective, and affordable telecommunications services; creating a legislativeenvironment conducive to encouraging local and foreign investors to operate inthe ICT field; creating local demand for the ICT industry to motivate local andforeign investors; targeting international markets by creating an ICT industrycapable of competing globally and transforming the sector into an export-ledindustry in order to capture a greater share of the global market; developingqualified human resources to develop and employ cutting-edge information andcommunication technologies; and attracting foreign investment through globalalliances (www.mcit.gov.eg). The plans developed and the resources allocatedwere capitalizing on an earlier effort that was put together since 1985 and hadresulted in the establishment of the Cabinet Information and Decision SupportCenter (IDSC), which introduced to both the public and private sector for the firsttime the concepts of using computer-based decision support systems forbusiness and socio-economic purposes.

Decision Support Systems in Egypt

Decision support systems, since their inception in the 1970s, have been differ-ently defined and conceptualized by vendors, researchers, and academic com-mentators. However there has been general agreement that decision supportsystems are computer-based systems that help decision-makers confront ill-structured problems through direct interaction with data and analytical models.Some of the classic DSS texts show that the focus of research and applicationof decision support systems has to a large extent been on individual managers andon organizational decision processes, largely for the private sector. Thus DSSare mainly represented as providing a set of opportunities directed towardimproving the effectiveness and productivity of managers and professionals,



boosting the organization’s competitive edge, and rationalizing the decisionmaking process within an organizational context. They aim at realizing the desirefor accurate, timely, and relevant information to help individual managers inorganizations deal with an increasingly turbulent economic environment and thegrowing pressures of competition. Much less emphasis has been given to theapplication of DSS in three particular areas: (a) their use with groups (althoughgroup decision support systems nevertheless represent a significant domain ofresearch and application); (b) their use in the public sector; and (c) their use tosupport socioeconomic development.In many ways, Egypt is a typical developing country. It faces the commonproblems of developing countries such as heavy foreign debt, a balance ofpayments deficit, a high illiteracy rate, poor technological infrastructure, lack offinancial resources, and high unemployment. It has been striving to implement anation-wide strategy to support the realization of its targeted socioeconomicdevelopment program to deal with these problems. Over the last decade Egypthas managed to restructure many of its sectors and has improved the position ofits economy and is striving to complete the economic reform program, althoughsometimes being hindered by internal economic deterrents as well as by externaleffects that affect the growth of the economy at large.In the mid 1980s, the government of Egypt adopted a far-reaching supply-pushstrategy for the introduction, implementation, and institutionalization of largeinformation and decision support systems intended to improve strategic decisionmaking at the Cabinet level with respect to socioeconomic development. Thestrategy had to be tailor-made to the decision-making needs of the Cabinet ofEgypt, which addresses a variety of socio-economic development issues. Theseissues include public sector reform, administrative reform, debt management,and privatization. The nature of these issues makes them adaptive to theenvironment and liable to continuous changes taking place locally, regionally, andglobally. Before decision support systems were implemented, the followingcharacteristics were identified within Cabinet decision making: (a) it was datarich but information poor; (b) information systems and management specialistswere isolated from the decision makers; and (c) computer systems were notviewed as tools that could support decision making. Moreover, the focus ofimprovements was more on technical issues rather than on decision outcomes.Despite these undoubted obstacles a project was initiated to support Cabinet-level decision making through state-of-the-art information technology tools andtechniques (Kamel, 1996, 1998). In 1985, the Cabinet of Egypt established theInformation and Decision Support Center (IDSC), whose mission is to provideinformation and decision support services to the Cabinet for socioeconomicdevelopment. The objectives of IDSC included: (a) developing information anddecision support systems for the Cabinet and top policy makers in Egypt; (b)supporting the establishment of decision support systems/centers in different

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ministries and making more efficient and effective use of available informationresources; (c) initiating, encouraging, and supporting informatics projects thatcould accelerate managerial and technological development of Egyptian minis-tries, sectors, and governorates; and (d) participating in international co-operation activities in the areas of information and decision support.The Cabinet’s IDSC activities accommodate four different domains: (a) TheCabinet for which IDSC provides information, decision support, crisis manage-ment support, modeling, and analysis of various high priority issues and multi-sectors information and database developments; (b) the economic sectors forwhich IDSC provides assistance in the development of decision support systems/centers, advice, and consultancy in the area of information and decision supportservices, sectors’ database development, and project financing and support; (3)the economy for which IDSC provides assistance in policy formulation anddrafting, as well as support for legislative reform and human and technicalinfrastructure development; and (4) the national information and technologicalinfrastructure for which IDSC provides opportunities and facilities for technol-ogy transfer to Egypt as well as to other developing countries through theestablishment of generic DSS models for socioeconomic development. Follow-ing are four different decision support cases that were managed and analyzed bythe Cabinet of Egypt Information and Decision Support Center and set the pacefor other cases that deployed advanced information systems in developingscenarios for socio-economic challenges.

Decision Support Cases

a. DSS for Strategic Issues: DSS-Based Debt Management System

During the 1990s, economic rebuilding efforts required Egypt to accumulate aforeign debt of about 33 billion U.S. dollars covered in 5,000 loans. These loansneeded to be monitored for debt service payments, term re-negotiations, interestrate levels, and payment management and scheduling. The magnitude of the debtburden led the reform of the debt management program to become a priorityissue at Cabinet level. Hence IDSC initiated, developed, and implemented a debtmanagement system aimed at the rationalization of debt utilization and at debtreduction and rescheduling. The system was developed to provide a manage-ment tool to support and facilitate the registration, monitoring, control, andanalysis of Egypt’s debts.Over a period of 18 months a national comprehensive database, located in theCentral Bank of Egypt, was developed by IDSC’s technical staff. The databaseincluded details of government debts and payments, linked to a debt payments



transaction processing system. The database was provided with decision supportsystem capabilities, enabling the implications of different debt managementscenarios to be tested. Throughout the development phase a number of technicaland cultural problems came up that caused delays and frustration, includinghardware requirements, software availability, and processing of operations.Cultural issues included the fact that most of the software was developed andinterfaced in English, which represented a problem for many Egyptian users. Theimpacts of the system, using decision support tools and generators, was thesuccessful negotiation of debt rescheduling with 14 countries. Negotiation wassmoothly managed through the provision of grounded information support thatwas made available via the DSS. Moreover loans have been viewed ever sinceas part of a comprehensive, integrated, and dynamic portfolio rather than beingmanaged on an isolated case-by-case basis.

b. DSS for Strategic Issues: Customs Reform Program DSS

Through one of its reform programs the Cabinet of Egypt was about to imposea new set of customs tariffs, largely for imported goods, which were intended toreduce the burden on low-income groups, increase the revenue of the govern-ment, and create a homogeneous and consistent tariff structure. Anticipation ofthe tariff changes caused stagnation in the business sector for four months. Asa result, multi-sectors conflicts arose between six different ministries. Hencesome form of decision support system was needed to resolve the conflict and tosupport imposition of the new tariffs.Therefore a team consisting of Ministry of Finance and IDSC personnel wasformed to interact with the different parties, get feedback, and generate differentscenarios to be assessed. A computerized DSS was developed, as a result ofwhich the various inter-ministerial conflicts were resolved within a four-weekperiod. Moreover a tariff structure was formulated, based on the variousscenarios and alternatives that were generated by the decision-support system.The government endorsed the new tariff model, which was also accepted by thebusiness sector.

c. Sectoral DSS: Ministry of Electricity DSS

The increasing cost of government subsidy to electricity generation in Egyptwere continuously enlarging the country’s balance of payments deficit andadding to public sector debt. To help address this issue, IDSC developed adecision support system for the Ministry of Electricity that was intended to: (a)assess the impact of tariff changes on different income groups, (b) provide

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statistical data on power and energy generation, (c) provide statistical data on thedistribution and consumption of electricity, and (d) assist decision making aboutthe pricing and management of loans within the electricity sector.A joint team was formed from IDSC and Ministry of Electricity staff. While theministry staff collected data from different sources, IDSC staff focused on issuestructuring, systems and human resource development, and, more importantly,on managing the process of developing and delivering the decision supportsystem. During the implementation process, drought emerged in the sources ofthe river Nile, causing a dramatic drop in the hydroelectric power generated bythe Aswan dam and necessitating the provision of 5 million U.S. dollars to fundthe rapid construction of three power-generating stations. As a result, theMinistry of Water Resources was drawn into contributing to the project, sinceit became a stakeholder in the decision-support system design process. At thisstage the project team therefore incorporated a third group from the Ministry ofWater Resources to cover the issues relating to hydroelectric power. In part therecognition of the ministry as a key stakeholder in electricity generation and itsinclusion in energy decision making was one of the main outcomes of the DSSdesign and implementation process. The DSS also led to decisions about a newelectricity tariff after assessment of the possible alternatives generated by thedecision support model and the evaluation of their impacts on different incomegroups. The case showed that design and implementation processes are insepa-rable and evolutionary throughout the entire information systems lifecycle.

d. Information Infrastructure Build-Up: Governorates’ DecisionSupport Centers

Once IDSC realized the vital role of information in decision making and in socio-economic development, it adopted a supply-push strategy to improve administra-tive effectiveness at the provinces level through the use of information anddecision support tools and techniques. The project aimed to rationalize thedecision making process of the governors through the use of state-of-the-artinformation technology. The project adopted its supply-push strategy through theimplementation of two parallel policies: the development of an infrastructure forinformatics and decision support systems, and the development of humancapabilities in the areas of information, computers, and communications. Tofulfill this strategy, IDSC developed a comprehensive information base for thegovernorates through the establishment, in each governorate, of a governorateinformation and decision support center (GIDSC) to introduce and diffuseinformation technology and to re-envision the role of the governorates indevelopment planning. The impact of GIDSCs was reflected in the number ofinformation and decision support cases delivered and in the diffusion of informa-



tion technology knowledge and use at the governorate level. Moreover the workof the GIDSCs led to the introduction and implementation of a new law for localadministration — representing a direct result of the project — that alloweddecentralization of decision making authority and power to the governors. It isimportant to note that the GIDSCs had a direct impact on the structure of decisionmaking at the governorate level (Kamel, 1996).

Managing the Process from Design toInstitutionalization

The experience of managing the development, design, and implementation ofdecision-support systems such as those described above can be generalized asa set of steps and procedures for future use of decision support systems in similarcases. IDSC adopted a two-phased approach for the implementation andinstitutionalization of its issue-based decision support systems projects (El Sherif& El Sawy, 1988). The first phase (implementation) was concerned with therealization of decision support systems and includes a particular focus on modelbuilding. The second phase (institutionalization) was concerned with embeddingthe DSS into their organizational contexts and includes a particular focus onmanagement. The implementation phase was typically divided into three parts:(a) the identification of policy needs and the full mobilization of human andtechnical resources to achieve effective response and support, (b) the identifi-cation of decision areas and information requirements, thus translating theplanned policy support into specific issues of concern for the recipient organiza-tion; and (c) the formulation of projects with specific goals and dedicated humanand technical resources for each potential area of policy and/or decision support.DSS project teams were selected to provide fast response and a focus on resultsand action. They were two-tier teams comprising government bureaucrats andprofessional technocrats able to deal with bureaucracy and IT professionalscompetent to handle state-of-the-art information and decision support technolo-gies. These two-tier teams were hybrids that represented one of the key successfactors in bridging the application gap between systems builders and applicationsusers (Kamel, 2001).The institutionalization phase covered IDSC’s experience with designing, devel-oping and implementing decision support systems for development planningpurposes. This experience suggested that managing institutionalization is asimportant as model building and that institutionalization is a complementary andintegrated process that accompanies systems development, design, and imple-mentation. It comprises six components as shown in Table 1.

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The use of decision support systems in development planning led to theidentification of a number of challenges related to strategic public sector decisionmaking, decision-support systems, and the implementation and institutionaliza-tion of rational management approaches. It is important to identify and deal withthese challenges effectively to be able to deploy such advanced informationsystems in a way to render the organization more competitive both locally andinternationally within a global environment that is consistently and continuouslychanging. Table 2 demonstrates such challenges.

Lessons Learned

Based on the implementation of more than 500 projects targeted at the develop-ment and diffusion of decision-support systems in Egypt for developmentplanning, the following set of lessons learned can be summarized and could be

Table 1. Institutionalization phases

Phase Actions Taken Adaptation �� Various modifications needed to fit the contextual

and cultural characteristics of the application environment, such as making use of available Arabized software and designing and developing tools and utilities to support and facilitate the use of Arabic-interface software.

Diffusion �� Spreading the use of decision-support systems and developing the information technology infrastructure across all organizational levels.

Adoption �� Personalized use of information technology tools and techniques by decision makers as well as their support staff.

Monitoring and Tracking

�� Addressing critical issues, assumptions, priorities, and information and decision requirements, and tracking changes in technology and its potential input to the decision-making process.

Value Assessment

�� Reviewing the contribution of decision support systems to public sector strategic decision making in Egypt in terms of tangible and intangible benefits such as: improved decision making at the Cabinet and governorate levels and more efficient use of available resources.

Evaluation �� Appraising, analyzing, and validating value-added benefits of decision support systems developed for socio-economic development planning.



used as possible models for similar implementations in similar settings indeveloping nations and in public administration environments. The lessons are:

• Structuring of socioeconomic decision-related issues is an integral part ofthe design and implementation of decision support systems dealing withnational development planning.

• Providing decision support systems requires much time and effort inbuilding and integrating databases from multiple data sources and sectors.

Table 2. Implementation challenges

Strategic Public Sector Decision Making Decision Support Systems Development

�� Efficient and effective use of scarce resources

�� Factors determining implementation of socio-economic development planning

�� Ill-structured nature of strategic decision making processes

�� Turbulent and dynamic environment within which decisions have to be made

�� Crisis management mode of operation for many strategic decisions in the public sector

�� Strategic decision making is usually a group effort rather than an individual one

�� Need for conflict resolution in strategic decision making, given the major issues and stakeholders involved

�� Formulation, development, and implementation of policy reform programs

�� Managing the development of multiple information and decision support systems

�� Institutionalization of such systems within their application contexts

�� Development of usable decision-support systems interfaces

�� Availability of decision support systems tools and generators relevant to different sectors and applications

Practical Implementation and Institutionalization of DSS �� Resistance to change �� Lack of timely, adequate information about user needs �� Lack of user involvement �� User language problems �� Lack of top management support �� Lack of continuous communication from users �� Difficulty of problem definition �� Difficulty of responding to user needs �� Inadequacy of model evaluation �� Poor documentation

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• Developing a decision-support system to address one socio-economic issuemight affect other issues that should be put into consideration during thedesign phase to save time and effort and avoid duplication of activities.

• Providing decision-support systems for development planning is oftenurgent and critical; hence the design should allow for a crisis managementmode of operation.

• Providing crisis management teams with managerial and technical supportcapabilities is essential.

• Depending on timely, effective and accurate information is essential foreffective decision-support systems.

• Implementing successful decision-support systems are necessary but not asufficient condition for successful institutionalization of DSS.

• Integrating implementation and institutionalizations processes of decision-support systems is vital.

• Implementing successful decision-support systems requires top manage-ment support; institutionalizing successfully the process requires broaderorganizational support.

• Evaluating and assessing decision-support systems is a vital ongoingprocess to provide a real-time response to changes occurring in theenvironment.

• Conducting continuous multi-level capacity development plans is crucial forthe successful adoption, adaptation, and diffusion of decision-supportsystems within organizations.

References

American Chamber of Commerce in Egypt. (2002). Information technology inEgypt (Business Studies and Analysis Center).

Economic News Letter. (2004). Newsletter. Retrieved January 24, 2004, fromwww.economic.idsc.gov.eg

El Sherif, H., & El Sawy. O. (1988). Issue-based decision support systems forthe cabinet of Egypt. MIS Quarterly, 12.

Kamel, S. (1996, May 19-22). Decision support systems for strategic decisionmaking. Proceedings of the 7th International Conference of theInformation Resources Management Association, Washington D.C.



Kamel, S. (1998). Decision support systems and strategic public sectordecision making in Egypt in information systems for public sectormanagement. Working paper series, Institute for Development Policy andManagement, University of Manchester.

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