A Cognizant Pattern of IT Project Success Model: A Case Study on ...Presentation Transcript
International Conference on IT to Celebrate S. Charmonman’s 72 nd Birthday A Cognitive Model of Project Success Delivery by Montri Wiboonrat, Ph.D. Assumption University Bangkok, Thailand. 30 March 2009
Significance of the Study
Data Center Facility Implementation Project (DCFIP) represents a complex system, with scarce expertise or body of knowledge in the field.
Business and IT objectives are continually changing, thus a proper decision-support model is needed.
The completed data center is incompliant with the original design.
Down time costs of data centers raise CIO’s or COO’s concerns on optimum investment for a data center. What are the criteria for making this important decision?
What are the causal factors and success criteria for DCFIP?
How can DCFIP success be measured and delivered?
To propose a systematic method for comprehensive assessment of technological and business risks.
To conduct a sensitivity analysis on such project management’s key performance indicators as time, cost, and quality, via differing what-if scenarios. The analysis results are examined for inter-relationships among these KPIs to shed lights on how they may be adjusted to obtain optimum project performance.
To identify causal factors and success criteria of data center project management success and project success.
To develop a model for analyzing and evaluating data center designs and operations before contract/ agreement and after implementation.
A DC is the place that creates, stores, exchanges, updates, and distributes information.
Rapid technological changes and trends, according to Moore’s law (5-15 yrs)
DC downtime costs may kill business operations.
The implemented DC is incompliant with the master system design.
Skills and extensive knowledge of consultants and contractors required
Multidimensional system integration problems
Operations and human errors are higher than system failures.
No certified body for DC
Literature Review: International Standards
1993 : Uptime Institute Inc. inaugurated consulting services for maximizing data center uptime. (Tier Classifications)
1999 : IEEE 1100; Recommended Practice for Powering and Grounding Electronic Equipment
2003 : IEEE 1490; PMI Standard: A Guide to PMBOK
Before 2005 , there was no standard for the Data Centers.
April, 2005 : TIA-942; Telecommunications Infrastructure Standard for Data Centers - Telecommunications Industry Association (TIA)
2005 : ISO 20000; IT Service Management Standards
2006 : ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineering, Inc. (ASHRAE TC 9.9, 2006)
2007 : BS 25999; Business Continuity Management
2007 : IEEE 493; Recommended Practice for Design of Reliable Industrial and Commercial Power System
2008 : ITILv3; IT Infrastructure Library
Literature Review: Techniques & Theories
Software Simulation “BlockSim7”
Topology: Series-Parallel, K-out-of-N, Active Standby, N+1, Bridge
Golden Triangle (Cost, Time, and Quality)
Literature Review: Summary
Over 100 citations from literature reviews of various international journals:
IEEE Trans. on Engineering Management, Trans. on Reliability, Power Distribution, Industrial Application, etc.
International Journal of PM, PM International Journal, PMJ, IJCIM, IJMSEM, IJEPESE, etc.
Quantitative Application (Cont.) Tier IV DC by: - Uptime Institute - TIA 942 - IEEE 493 Availability: 99.995% Downtime: 0.4 hr/yr Time ( T ) = 365 days Lamda~ 1.3698x10 -7 Mode or Topology: Active Stand-by Parallel Loaded balance Availability: >99.99914%
Qualitative Results Factors and Standards Driven Project Achievement
Qualitative Results Transformation of DCFIP Success Model (V Model)
Qualitative Results (Cont.) Stages of Project Management Failure or Success
Qualitative Results (Cont.) DCFIP Service Quality Model Want Need GAP CP SQI
Qualitative Results (Cont.) Weight, Mean, and SD of Service Quality
Qualitative Results (Cont.) Mathematical Derivation of Service Quality Index (SQI)
Qualitative Results (Cont.) Mathematical Equation of DCFIP Success Level
Qualitative Results (Cont.) Sampling Test of DCFIP Success Levels
Qualitative Results (Cont.) Dynamic Relationship between DCFIP Success and Failure
Overall Findings (Cont.) Chronological Impact on DCFIP Success
DCFIP stakeholders must jointly participate since the outset of the processes and be clear on each party’s objectives, scopes, accountabilities, and perceived results.
DCFIP success needs to correspond with the Chronological Theory in 2 Steps:
Project Management Success (Time, Cost, Quality)
Operations and Service Delivery Success (Marketing and Sales)
Experiences and skills of project managers, consultants, and contractors contribute significantly to DCFIP success.
DCFIP success can be measured quantitatively and qualitatively.
Quantitative success of DCFIP can be measured by the achievement of TIA 942 standard, by the designated time, within allocated budget, and at the agreed-upon performance targets.
Qualitative success of DCFIP can be measured via the product of ROI and SQI.
DCFIP needs to comply with all local and international standard requirements, e.g. local codes, SLAs, TIA 942, ISO 20000, ITILv3, etc.
Standards are merely targets for measuring achievements against. They may be appropriately set as guidelines for human actions.
Human determination is, actually, the engine that propels the project towards success.
DCFIP as Human Finger Prints: Each one has its own unique requirements and constraints. The models to achieve project success are applicable in general; however, adjustments to fit specific problems, place, and time may be needed.
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