A Cognitive Model of Project Success Delivery Montri Wiboonrat Graduate School of Information Technology Computer and Engineering Management Assumption University, Bangkok, Thailand [email protected] Abstract- An incompatibility of data Keywords- System Reliability, System processing and integrated systems of data Integration, Service Quality, Project migration and system implementation is Success Delivery always happening in all organizations which rely on electronic transactions. 1 INTRODUCTION Since implementation of hardware facilitate infrastructures and software Business downtime cost of brokerage applications is deployed on a different may cost $6.45 million US per hour. Credit period. Service interruption may cause card sales may cost $2.6 million US per hour from many reasons such as, hardware [10]. This cost is directly impact on financial failures, software failures, human errors, loss and business reputation. It does not upgrading systems, and incompatible matter, it happens from which section of functions of system integration. To business operation such as, power outage, understand of system malfunctions and data center operations, application operation, system failures, we need to comprehend electronic transaction and communication, on each level of user requirements, internet data center (IDC), or internet service application designs, facility designs, provider (ISP). It will cost welfare loss and system integrations, system operations, bad image to the end users. Business system maintenances, and quality service reputation is reflected directly to business management to increase the system quality of services. Financial sector is a good reliability and robust system operations. example of delivering quality service This research proposes to construct the because they are integrated of facility novel model of the integral system infrastructure and marketing / application reliability from resolving user services. All banking systems need a unified requirements in data center process of; operation and each system cannot leave design and planning; implementation; without the others. monitoring and controlling; systems Problem reaction or fast respond to the evaluating and development; throughout problem is eliminated the accumulation costs the system operations and delivering of downtime [19]. Preventive cost is much quality services. Primary investigations cheaper than corrective actions. The via data processing and data center problem is how to solve through the right experts and secondary literature search root cause of the problem at the first time were conducted. The findings revealed and prevent the trial and error. such dominant factors as technology, Comprehensive understanding on system consultant, contractor or implementer, design and system operation is the key to marketing strategy, and operations and increase more on the system reliability. service team are the vital based on project Interconnection and communication is the success delivery. other key to reduce misinterpretation and reaction to the problem. This research

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investigates, what are the multiple facets or Reliability: An indication of the ability of dimension on which they evaluate the a component or system to perform its success services? The example of data center intended function during a specific time [19]. project subject to design, planning, 2.2 Data Center (DC) implementation, monitoring and controlling, maintenance, and operation; network, server, A data center is an IT infrastructure storage, operation system, application system built for storing and disseminating installation, and application operation; are information nearly light speed on real-time concerned to find out the critical factors that over the earth observation via the Internet; impact on project success or quality service. LAN, MAN, and WAN. The data center is designed for all online requirement Design and operation on fault tolerance proposals. The certain data sets will be topology is the key to increase system stored, updated, exchanged, and delivered to reliability and robust service system to all computers or mobile units that are support the critical operation 24x7 hour. available and online connected. Reliability/ Moreover, the fault tolerance topology might availability/ dependability of a data center come with high system reliability but it become a competitive advantage for critical needs to tradeoff with the high investment as applications of each company’s core well. This paper aims to institute and businesses. combine the conceptual model of delivering quality service by complying with the One of the most complex systems of IT international standards namely; TIA 942 project is a data center (DC) implementation [15], BS25999 [3], ITILv2 [6], ISO20000 and operation. Why? Because DC is [7], IEEE 1490 [27], and Thailand local comprised 16 sub-systems [16]. Moreover, codes. all 16 sub-systems must be operated in synergy to contribute to DC performance 2 BACKGROUND subject to availability, reliability, scalability, 2.1 Definitions flexibility, capacity, simplicity, and manageability. The other complexity of DC Service quality (SQ) defines as the extent design is rapid technological changes, as of discrepancy between customers’ suggested by Moore’s law (1965), stating expectations or desires and their perceptions that “a chip density will double every 18 [23]. months” [8]. The result of Moore’s law is Tangible (W1, x1) defines as appearance directly impacted the data center design in of physical facilities, equipment, personal, terms of heat load and power consumption. and communication materials. The data center implementation has to Reliability (W2, x2) defines as ability to concentrate not only on the chain reaction of perform the promised service dependably Moore’s law, but also on how to implement and accurately. data center to meet the golden triangle or iron triangle objectives [22]. The criteria for Responsiveness (W3, x3) defines as willingness to help customers and provide measurement is under the concerns of time, prompt service. budget, delivery exactly specification and quality of data center performance [4]. It Assurance (W4, x4) defines as knowledge seems that DC project needs to do concurrent and courtesy of employees and their ability engineering (CE) [2], as the same time it to convey trust and confidence. needs to answer and achieve by Moore’s law

Empathy (W5, x5) defines as caring, in terms of DC size, power consumption, and individualized attention the firm provides its forecasting heat loaded. customers. How to make a DC project success? Many researchers mention it in the literature

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35.2 A Cognitive Model of Project Success Delivery reviews in the topic of “Key Success of perceived service quality, service quality Project Management”. In this topic, the level (SQL) and service quality index (SQI). researchers try to concentrate on project Customer and service provider may have management processes of DC. During DC different perspective on service quality project, there are many parties that are however the scope of service quality must be involved namely DC owners/end users, under SLOs. More than SLOs, we called “the consultants, main contractors, sub value added or the great expectation” which contractors, suppliers, and technology can be measured by SQI. owners. Each party has their own concerns. The analytical sets of potential On this process, the most concerning part is outcomes are sorted into grouping or cluster to focus on consultants and contractors. that has similar influences or effects. The Experiences and project site references are procedure of decision making is involved as the key factors that contribute to project follows: management success [9], [17]. 1. Structure a problem with a model that 2.3 Service Quality (SQ) explains the problem’s key factors The evaluation of service quality is and their interaction. the most difficult for customers to make a 2. Extract judgment that reflects decision rather than a goods quality. Hence, knowledge, needs, feelings, the evaluation of service quality needs the emotions, and past experiences. standardized criterion. It may be more difficult for the provider to comprehend. 3. Correspond to those judgments with Zeithaml, Parasuraman, and Berry (1990) significant numbers. research defines the service quality as the 4. Apply these numbers to calculate the gaps between customer’s expectations and priorities of the factors of the perceptions. Moreover, their research hierarchy. proposes key factors; internal factors for instance, knowledge; needs, feelings, and 5. Synthesize these results to ascertain emotions; and past experience; external an overall result. factors such as, word-of-mouth and 6. Analyze sensitivity to change in communication channels; that influence judgment. customer’s expectations. Analytic hierarchy process (AHP) is The difference between expected applied through the quality service model. It service and delivered service is the perceived assists decision making by organizing service quality. The Fig. 1 illustrates a perceptions, needs, feelings, judgment, and pictorial summary of their findings which memories into a model that illustrates the included; dimensions of service quality, forces that impact a decision [13]. internal imagination, external illusion, SLOs,

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Internal Imagination External Dimensions of Needs Past Propagation Service Quality Knowledge Feelings Experience Communication Tangibles Emotions Channels

Reliability Word of Mouth Responsiveness Expected Competence Service SQL

Courtesy SQI Perceived CUSTOMER Credibility SLOs Service Quality SERVICE Security PROVIDER

Access Delivered Service Communication Competitive Advantage Understanding Operation Site Company the Experience Finance Customers Team References Vision

Fig. 1. Customer assessment for service quality.

3 METHODOLOGY owner, and IT specialist, as depicted in Fig. 2. The research selected a broad spectrum of 3.1 Corporate Population Model data center operation and services to study of To understand a crucial role in the this research because we are looking for the assessment of service quality, we need to factors that reflect and transcend the scopes answer which factors are influenced the of specific data center service businesses. service quality to become success. The research conducted five focus groups in According to the limitation of experts on Thailand, and international conferences such DC, this research conducted an exploratory as IEEE IEMC [18], IEEE ICMIT [20], study consisting of 5 focus-group interviews IEEE ICSET [21], and ACIS-NSPD [19]. (G1, G2, G3, G4, and G5); each group Additional information supports from comprised 20 companies/ experts, the total literature review are referred to Zeithaml, 100 persons will have direct interview and Parasuraman, and Berry (1990), Saaty questionnaire; technological supplier, (1994), and Wiboonrat and Jungthirapanich designer & consultant, contractor or (2007). implementer, operator or service system

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Corporate Populations OSI

Data Centers Layer 8 (G3) Application AIT, CDG, Samart, G-able, DataPro, Mflex, NetOne etc. (G4) Contractors Implementation

1. PTT Layer 8 (G2) EDS, PriceWaterhouse, Accenture, TSS, C2 Consultant, Merrin etc. Consultant 2. Kbank Software & Application: Linux, Microsoft, Oracle, SAP, PeopleSoft, Layer 7 (G1) 3. BankThai Teamworks etc. 4. BBL Security & Utility: f5, MaAfee, Symantec, Trend Micro, Check Point Layer 6 (G1) 5. True Enterasys, and CyberSafe. Application Consultant 6. TCC Layer 5 (G1) Storages: Acer, Dell, EMC, Hitachi, HP, IBM, and SUN 7. KCS

8. TMB Layer 4 (G1) Servers: Acer, Dell, HP, IBM, and SUN

9. MEA Layer 3 (G1) 10. PEA Networks: 3COM, Alcatel, Avaya, Cisco, Ericson, Huawei, Juniper, Lucent, Linksys, NEC, Nortel, Procurve, and Siemens 11.ThaiPost Layer 2 (G1) 12. TOT Cabling Infrastructure: AMP, Belden, Datwyler, Darka, Clipsal, 13. CAT Krone, Nexans, and Systimex. Data Center Consultant 14. BOT Layer 1 (G1) Electrical System: APC, AEG, Blueline, Chloride, Liebert, MGE, and 15. SCB Infrastructure Socomec IT Specialist / Doctor / Professor (G5) / Professor / Doctor IT Specialist 16. Reuters Mechanical System: APC, Canatel, Delco, Hiross, Liebert, RC Group, and Stutz 17. Loxifo Layer 0 (G2) TSS, C2Consultant, COT, IBM, HP, Artos, Merrin etc. 18. GSB Consultants 19. C2 Layer 0 (G3) Data Center Sitem, Emerson, W&W, Unitrio, IBM, HP, APC, Rittal, Schneider etc Contractors Implementation 20. Inet

Fig. 2. Corporate population and IT specialist model.

3.2 Interview Model site reference and an official citation notice. That is the other way that the consultant and A presentation of the related impact contractor accept a project success. The model of communication framework of data biggest achievement of a successful project center project team depicts in Fig. 3. It is when sponsors/clients recommend the shows an intermediate result of action and consultant or contractor to other companies interaction between each party e.g. requestor, or his friends with guarantee on the working commander, interpreter, implementer, and quality. end user. The external impact (independent variables) will affect the internal factors Assessment for project success criteria is (dependent variables) of project success. different for each stakeholder. For an investor/sponsor, the most important factor is Deliverability is the most important the return on investment. Improve on factor for consultant and contractor for business reputation, productivity, efficiency, project management success. Consultant and and competitive advantage is a compelling contractor point of view concerns on the function of data center that must be achieved project achieved by contract agreement and when creating the benchmark with other got paid by sponsor. Sponsor/Project owner competitors in the same market. allows consultant/contractor to use DC as a

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Users Communication Frame Work End (Dependent Variables)

Sponsors Data Center Contractor Owner (Implementer) External Impactors (Requestor) (Independent External Impactors Project Variables) (Independent Manager -Economics Variables) (Commander) -Standards -Competitors -Regulations -Customer -Technologies Perceptions -Competitors -Partner Directions -Politics Consultant Supplier -Disasters (Interpreter) (Supplier)

Fig. 3. Data center conceptual framework from direct interview and factors analysis

4 CONCEPTUAL MODEL From definition (2.1) we given by;

The first objective of qualitative model is + + + + WWWWW 54321 =1 (1) to investigate the key success factors and key success criteria that are normally applied for + + + xWxWxWxWxW 5544332211 =+ σ , project measurement in the market and where byσ = [0.1,…, 1] (2) research. The second objective is to examine Since the result from 100 questionnaires and analyze two sources of the result an average weight on each W is 0.2412, directions, i.e. literature reviews and direct i 0.1859, 0.1840, 0.2021, and 0.1868 interviews, to resolve the conclusion of the respectively. Substitution each value of W in chronological project success model. It i (2), we will receive (3) as follows: delineates to a simple mathematical model as “project management success (PMS) + + xx + 1840.01859.02412.0 x + 1 2 3 (3) quality products / services success (QPSS) = x + 1868.02021.0 x = σ project success (PS).” This is different from 4 5 Baccarini (1999) that defined “project 4.2 Project success Model success = project management success x Project success is under the time domain project products/services success”. of multi-activities that consist of operation The analysis and evaluation of management, marketing management, and chronological project success model is service management. Beyond project contributed to the success pattern of the data management success, project success is an center project success in term of project uncertain strategy. It is a dynamic solution. implementation, project operation, and Project success can be defined into short run delivering quality service. success and long run project success. Fig. 4 illustrates the integration of each activity 4.1 Service Success Model (σ ) from project start to project management This research model uses multiple success. Short run project success may be criteria based on AHP to analyze the service measured a few days or a few months after success or subjective value (σ ) of DC project management success. Short run complex problems [13]. σ is comprised project success may be marketing campaign numerous subjective values such as, or the project announcement to the market. tangibles, reliability, responsiveness, Sometimes, it works as a rise up of company assurance, and empathy [23].

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35.6 A Cognitive Model of Project Success Delivery stock for a short period. For the real factors”. Operation management and operation, it is a trial period for the real marketing management are the key factors functional testing for revealing bugs and how that lead to project success, as depicted in easy for users to use. Besides, the reliability Fig. 4. and availability of connection, accuracy, and Project success can be defined into security of transfer data is the critical process objective value or financial figure and to evaluate the achievement of the subjective value or reputation. Project international standards before receiving the success is recorded in many literatures, it certifications. must have at least one characteristic For DC project, the international objective or subjective, or both. Financial standard certifications are a kind of figure is easy to calculate by time value of competitive advantage in the business money (TVM) as return on investment segment. However, it is declared as a short (ROI), as shown in (6). Normally, on run project success on reliable operation. calculation for budget approval, most people forgot about the operation costs and A long run project success depends on marketing costs, as on (5), that distorts ROI time. It may be a few months or a few years of each year because operation costs and or longer than that. As it has many factors marketing costs could be 1.5-2 times of affecting the project success, this research is investment on (4). limited only to the controllable and predictable factors or called “internal

Regulations Criteria / Business Measurement Marketing I Risk&Opps Safety Management Technical Risk Time/Schedule Key Quantitative Re-invest Factors Planning & Cost/Budget Project User Implementation Project II Requirements Design Specification/ Management Sustain Standards Reliability Success Success Fade Out Project Scope Quanlitative Resource Risk Each Party Satisfaction Operation Competitors Management III Environment

Phase I Phase II Phase III Phase IV Phase V A B C D E F G H

Level of Long Run Project Success 2 Project Success I Short Run Project Success II Project Management Success F 1 F Quality Service S4 S3 III S2 S1 Work BreakdownS0 Structure ROI 0 Time ISO 9001: 2000 ISO 14001 ISO 10006 IEEE Std 1490-1998 / PMBOK Process BS 25999 1/2 Control TIA 942 ITIL v .3 Standards ISO 20000

Fig. 4. Chronological of data center project success: delivering quality service model.

Facility Infrastructure Investment + Interest Rate (yr*) = A Software License, Servers and Network Hardware + Interest Rate (yr**) =B (4) Operation Costs (mth) + Marketing and Service Costs (mth) = C

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+ BA = YearsROI )( (5) Monthly Income

++ CBA = YearsROI )( (6) Monthly Income * is calculated since the investment on the project started. ** is calculated after the payment fully finished. TIA 942 (2005) shows the life cycle of IT equipment, which is around 3-5 years but the facility infrastructure’s life cycle is around 10-15 years. IT equipment and facility infrastructure depreciation may need to include the calculation to ROI. However, it is shown only in accounting. 1 + QPSSfPMSf ).()( = PSf )( ; σ = Subjective Values, byσ = Value range is among [0.1, i j σ k 0.2, ..., 1]. (7) Where by: i = Stage of project management failure or success

⎧ ,0 PMSi = Stage0 ⎪ ⎪0 PMSi << ,999.0 PMSi = Stage1 PMSf i )( = ⎨ (8) ⎪ 999.0 PMSi ,1 PMSi =<≤ Stage *2 ⎪ ⎩ = ,1 PMSPMS ii = Stage **3 * Stage 2 must be transferred to Stage 3 at the final process of PMS with corrective actions and executions to satisfy the business objective and subjective values, for all stakeholder profits.

⎡ ⎤ ROI j 1 QPSSf )( = ⎢ al)(Re ⎥. , j = year on measurement (9) j ⎢ ROI ⎥ σ ⎣ j Expected)( ⎦ ROI of the project is derived from Equation (6) Substitute (3), (8) and (9) in Equation (7), we will have Equation (10).

⎧OUTSTNADIN PSG k < 2, ⎪ ⎪EXCELLENT PSk <≤ 75.22, 1 ⎪ + QPSSfPMSf ).()( = PSf )( ⎨GOOD 75.2, PS <≤ 167.4 (10) i j σ k k ⎪FAIR 167.4, PS <≤ 7 ⎪ k ⎩⎪ PSfailurebemayorPOOR k ≥ 7, At Stage 3 in Fig. 5 which defines as a is limited. Vast increase in sale level and project success in the short run, however, a sold out, may take 1-2 years or less than that. FAIR or GOOD project at Stage 3, when it The reinvestment for the next data center cannot perform as expectation it may could be on this. Secondly, scenario II become project failure in the long run (GOOD and FAIR), sustain on sales and measurement. keeps the same amount of space left in data center, this scenario may keep data center The result from (10) could be probable in sustain on operation but not too long to 3 scenarios: Firstly, scenario I survive. Lastly, scenario III (POOR), no (OUTSTANDING and EXCELLENT), more sales, space of data center still existing gradual increase in sales level, fully occupied there, the data center operation costs will kill space may take 2-3 years, until it is sustained or sold out because the space of data center

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35.8 A Cognitive Model of Project Success Delivery

this project success or fade out the project Phase III: Implementing; the standards from this business, as shown in Fig. 4. which are required to comply are the same as Phase I and TIA 942, IEEE 446 (1995), Each phase process of Fig. 4 reveals a IEEE 493 (2007), and IEEE 1100 (1999). big picture of factors that reflect on DC project success. Requirements of Phase IV: Complying; the standards international standards, system reliability on which are required to comply are the same as data center operations, and delivering quality Phase I and TIA 942, IEEE 493, and IEEE services are catalyzed data center project 1100. team to have the same project objectives, as Phase V: Sustaining Quality Service; the follows: standards which are required to comply with Phase I: Converting; the standards which the international standards. Mostly of this are required to comply are ISO 9001 (2000), phase are related to delivering quality service ISO 10006 (2003), ISO 14001 (2004), IEEE which must comply with ITIL v.3 or ISO 1490 (2003), and BS 25999. 20000.

Phase II: Interpreting; the standards PSf k )( Dynamic function could be changed which are required to comply are the same as which depends on the time domain, internal Phase I. and external variables, as shown in Fig. 5.

GOOD OUTSTANDING Stage 3 Stage 1 FAIR EXELLENT Ongoing project but terminated before finish

POOR

Stage 2 Stage O Project finish but with major defect, it Project feasibility not accepted, hence need corrective and execution processes the project might not start to fulfill project requirements and objectives

Fig. 5. PSf k )( Dynamic of Project Success and Project Failure

Phase I-IV is necessary to comply with dependent. Return on investment (ROI) of PMBOK (2007) processes of work data center depends on: first, internal factors breakdown structure (WBS), as depicted in or human activities, e.g. marketing support, Fig. 4. Microsoft project software, WBS, reliable operation, problems handling, and helps project manager trace, update, monitor, customer services; second, external factors, and control all activities as project planning. e.g. economic, politics, regulations, customer The completion of WBS lead to project trends, technology trends, national disaster. management success at the first step before ROI must be generated after the project moving on to the second step, chronological management success and not before, because theory, of project success that project success products and service are created after data is reflected on human activity and time center project operation. According to

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35.9 Montri Wiboonrat chronological theory, one set of events The high reliability, six’s nine or zero should be pursued by another. The reverse downtime, of data center is one kind of the order is impracticable [5]. criteria that show DC project management success. The history data of IEEE 493 are Project success is defined as “the changing every 10 years according to the delivered benefits of the project to evolution and development of technology. stakeholder in terms of financial forms or Simulation of DC shall be adjusted following quantitative values, against with the by technology changes. It is approximately commitment of returning times, and non- every 1.6 years as Moore’s law [8]. financial forms or qualitative values, e.g. business reputation, quality service, brand The effective operation and service of loyalty, new market segment, social DC to the clients is now one of the most responsibility, competitive advantage, critical competencies that successful problem solving, and respond to functional business needs in today’s unpredictable requirements.” world. The DC which providing a highly efficient and flexible infrastructure 5 DISCUSSION controlled by a common system management A project success is not about delivering will support a rapid scale of dynamically a project on time, on budget, and with business growth with the highest specific products or high quality services, but performance. Furthermore, DC that project success needs parallel processes of incorporate virtualization, dynamic load, marketing management, quality service allocation, and built-in management can management, and operation management of leverage the specific space, power saving, project to push the project’s success. Project and performance advantages of comparative success cannot be success by itself. Project advantage for clients. success requires more time consumption. It depends on which model to prove the project In order to obtain the levels of data success. Only the Chronological Project center availability, the system requires the Success Model of Data Center may not be preventive processes for the critical loaded enough to push the project become success points. The necessary processes need to take but effectiveness operation, excellent into consideration as follows: marketing support, and delivering quality 1) Operators require a comprehensive service should handle and solve the training on existing system design, power problems. Good project managers need to distribution system layout, common understand the value of their work, and they problems and solutions. These activities are comprehend their work will contribute to a preventing the manmade from commission project result on schedule and on estimated and omission during the daily operations and investment with a good level of satisfaction regularly maintenances. from the customer and the project team. 2) In the beginning of a design process, Project manager, operation manager, consultant or designer needs to consider and marketing manager and team members with concern with the international standards, the experiences and knowledge are the major latest equipment technologies and the mature key factors to keep and support project technologies before designing, planning, success to be faster and sooner. On the other implementing, operating and maintaining hand, it may be faster and sooner to fail. procedures. The high reliability (MTTF) and These project success and failure are correct sizing of selected equipment are suggested by Pinto and Slevin (1998), Pinto prevented, short life operation period, and Mantel (1990), and Shenhar and Dvir overloaded current (trip), energy (2007). effectiveness, optimal investment, and maintenance costs, as a perfected synergy.

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3) Contingency plans are required to uncertainty politics, regulations, customer institute to prevent the unexpected trends, natural disaster, and man made. incidences of national disasters that are Data center planning shall be engaged at unpredictable and uncontrollable situations. the early stage of project identification of The relation for downtime cost model what are the user expectations, business and reliability model is called “optimum objectives, and business constraints?, and availability and investment tradeoffs” that how to solve the problems from the designer and investor needs to discuss on limitation of the project in terms of what is the enough point of system company’s objectives, constraints, availability with constrained investment that regulations, reputations, and customer can achieve? While, absolutely service pays expectations? Rather than setting project off with ROI because it creates the true and time, budget, and results requirements loyal customers. The essence of marketing objectives as the critical criteria of project success is quality service success as well. success, a team needs to settle on how the Quality service and ROI is a reciprocal project can be judged and delivered results correlation. Any project cannot take its both when the project is completed and operating as the same time that why we called trade- for quality services as a chronological offs. project success. 6 CONCLUSION REFERENCES Data center project success is not only 1. Baccarini, D.: The Logical Framework Method for Defining Project Success. Project considered simply as a construction project Management Journal, vol.30, no.4, pp.25-32 or a capability to deliver services but as (1999) factors that have an impact on almost every 2. Bhuiyan, N., Thomson, V., Gerwin, D.: Implementing Concurrent Engineering: Product standards, business constraints, history development managers need a single, well- problems, customer expectations, defined process with clear ownership and goals. Research Technology Management, January- management methods and real practices. DC February (2006) project success does not always have the 3. BS25999, BS 25999-2 Business Continuity same pattern which is a predictable process. Management-Part2: Specification Business Continuity Management, July (2007) At the stage of project institution, even the 4. Cooke-Davies, T.: The “real” success factors on most novel project engages the uncertainties projects. International Journal of Project Management, 20, pp.185-190 (2002) and many unknown factors. It is complicated 5. Gray, D.B.: Doing Research in the Real World. to predict exactly how to management and Bill Gillham, Sage Publications Ltd., 1st ed., May delivering service through a project success. 25, (2004) 6. ITIL, An Introductory Overview of ITIL: version What are the appropriate criteria to measure 2.0, IT Infrastructure Library. IT Service the project success? Since one solution Management Forum (itSMF), (2006) cannot apply to all projects. Data center 7. ISO 20000, ISO 20000 IT Service Management Standards, http://20000.standardsdirect.org project management is in dynamic structure; 8. Moore, G. E.: Moore’s Law. project planning requires not only onetime www.intel.com/technology/mooreslaw/index.htm , (1965) activity for a whole project but needs multi 9. Ng, S.T., Skimore, R.M.: Contrators’ risks in alternative options, rethinking and Design, Novate and Construct contracts. reconsidering, flexibility, and consequence International Journal of Project Management, 20, pp.119-126, (2002) of actions to weight a decision. Adaptation 10. Patterson, D.A.: A Simple Way to Estimate the of change requirements for the project is Cost of Downtime. In: The Proceedings of LISA th necessary to make throughout the project ’02: 16 Systems Administration Conference, Berkeley, CA: USENIX Association, (2002) lifecycle, regarding to the nature of project’s 11. Pinto, J. K., Mantel, S.J.: The Causes of Project evolution and the technological development Failure. IEEE Transaction on Engineering Management, Vol.37, NO.4, November (1990) that changes the project’s characteristics 12. Pinto, J.K., Slevin, D.P.: Critical success factors according to the external factors for example, across the project life cycle. Project Management economics, breakthrough technology, Journal, 19(3), pp.67-75, (1998)

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13. Saaty, T.L.: How to make a Decision: The 28. ISO 9001, ISO 9001:2000, Quality Management Analytic Hierarchy Process for Decision in a Systems: Specifies requirement for a quality Complex World. RWS Publication, 3rd Edition, management system. http://www.iso.org/iso Pittsburgh, USA (1994) (2000) 14. Shenhar, A.J., Dvir, D., Levy, O.: Reinventing 29. ISO 10006, ISO 10006:2003, Quality Project Management: The Diamond Approach to management systems: Guidelines for quality Successful Growth and Innovation. Harvard management in projects. http://www.iso.org/iso Business School Press, (2007) (2003) 15. TIA-942, Telecommunications Infrastructure 30. ISO 14000, ISO 14001:2004, Environmental Standard for Data Centers, (2005) management system: Requirements with http://www.tiaonline.org/standards/catalog/search guidance for use. http://www.iso.org/iso (2004) .cfm?standards_criteria=TIA%2D942 16. Uptime, Uptime Institute, Inc. Tier Classification Define Site Infrastructure Performance (2006) www.upsite.com/whitepapers 17. Wiboonrat, M., Jungthirapanich, C.: A Taxonomy of Causal Factors and Success Criteria on Project Management Success and Project Success. In: 8th International Conference on Opers. & Quant. Management (ICOQM), Bangkok, Thailand, October, 17-20 (2007)

18. Wiboonrat, M.: An Empirical IT Contingency Planning Model for Disaster Recovery Strategy Selection. In: IEEE, International Engineering Management Conference (IEMC), Estoril, Portugal, June, 28-30 (2008a) 19. Wiboonrat, M.: An Optimal Data Center Availability and Investment Trade-Offs. In: 9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/ Distributed Computing (SNPD), Phuket, Thailand, August 6-8, (2008b) 20. Wiboonrat, M., Kosavisutte, K.: Optimization Strategy for Disaster Recovery. In: 4th IEEE International conference on Management of Innovation & Technology (ICMIT), Bangkok, Thailand, 21-24 Sep (2008) 21. Wiboonrat, M.: Risk Anatomy of Data Center Power Distribution Systems. In: IEEE International Conference on Sustainable Energy Technologies (ICSET), Singapore, November 24- 27, accepted for publication, (2008c) 22. Yu, A.G., Flett, P.D., Bowers, J.A.: Developing a value-centred proposal for assessing project success. International Journal of Project Management, 23, pp.428-436, (2005) 23. Zeithanml, V.A., Parasuraman, A., Berry, L.L.: Delivery Quality Service. The Free Press, A Division of Macmillan, Inc., New York (1990) 24. IEEE Std 446-1995, (Revision of IEEE Std 446- 1987), IEEE Recommended Practice for Emergency and Standby Power Systems for Industrial and Commercial Applications, December,12 (1995) 25. IEEE Std 493-2007, (Revision of IEEE 493- 1997), Recommended Practice for Design of Reliable Industrial and Commercial Power System, Gold Book. February, 7 (2007) 26. IEEE Std 1100-1999, (Revision of IEEE Std 1100-1992), IEEE Recommendation Practice for Powering and Grounding Electronic Equipment, March, 22 (1999) 27. IEEE 1490, IEEE Std 1490-2003: IEEE Guide Adoption for PMI Standard A Guide to the Project Management Body of Knowledge, The Institute of Electrical and Electronics Engineering, December,10 (2003)

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