Paper Summary
Paper 1 – Framing of project critical success factors by a systems model
Introduction
- Critical success factors:
o Limited number of areas in which results will ensure successful competitive performance
for the organization
o Few key areas where ‘things must go right’ for the business to flourish
o Areas of activity that should receive constant and careful attention from management
o Areas in which good performance is necessary to ensure attainment of goals
Comparison of sets of factors
- Only limited agreement among authors on factors that influence project success
- Three most cited factors:
o Importance of project receiving support form senior management
o Having clear and realistic objectives
o Producing an efficient plan
Criticisms of the critical factor approach
- Two criticisms:
o Inter-relationship between factors are at least as important as individual factors
▪ CSF approach does not provide mechanism for taking account of inter-
relationships
▪ ‘better understanding of relationship is required if success factors are to be of any
guidance
o Factors approach tends to view implementation as static process instead of dynamic
phenomenon
▪ Ignores potential for a factor to have varying levels of importance at different
stages of the implementation process
The Formal System Model (FSM)
- Model of robust system that is capable of purposeful activity without failures
- Formal system comprises:
o Decision-making subsystem that manages the system
▪ Responsible for decisions about how the purpose if the system are to be achieved
o Performance monitoring subsystem that observes transformation processes and reports
deviations from expectations
▪ Used to conceptualize situation as a system → compares the resulting system
with the FSM to determine extent to which features necessary for purposeful
activity are present
- Model contains within it factors identified in literature as being critical to success
o Able to act as framing device for project critical success factors
o Should provide way of making links between factors → overcomes two main criticisms
of CSF
Conclusion
- Lot of overlap between sets but the factors selected for inclusion in individual lists vary to a
considerable extent
- FSM contains within it all of the factors covered by sets of CSFs
o Has advantage of being able to consider the relationship between factors
, o Overcomes third criticism of CSF approach
- FSM capable of distinguishing between successful and unsuccessful projects
o Can provide way of tackling human and organizational aspects of systems development
projects
, Paper 2 – One Size does not fill all projects: Exploring Classical
Contingency Domains
Introduction
- Everyone is using some formal project management structure → defined as a temporary
organization that has been established to complete a specific goal
Theoretical Background and Basic Proposition
- Classical contingency theory asserts that different external conditions might require different
organizational characteristics
o Effectiveness is contingent upon the amount of goodness of fit between structural and
environmental variables
- Mechanistic organization was described as formal, centralized, specialized and bureaucratic
o Predominate in simple, stable and more certain environments
o Organizations less differentiated, achieve high degree of integration
- Organic organization was characterized as being informal, decentralized, having just few
authority levels and using extensive levels of communication
o Cope better with uncertain and complex environments → provide more capacity
o Organizations highly differentiated and integrated
- Literature assumes that all projects share universal set of managerial characteristics
o ‘one-size-fits-all’ idea is disappointing
- Emergence of two dimensions – uncertainty & complexity
o Coping with uncertainty is central problem for complex organizations
o Technology and environments major sources of uncertainty
The Conceptual Model
- Focus on study of technical and engineering-based projects → result in new product, process or
service
- Four levels of uncertainty & three levels of complexity (Scope)
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