Effort estimates through project complexity

This paper reports the results obtained from use of project complexity parameters in modeling effort estimates. It highlights the attention that complexity has recently received in the project management area. After considering that traditional knowledge has consistently proved to be prone to failure when put into practice on actual projects, the paper endorses the belief that there is a need for more open-minded and novel approaches to project management. With a view to providing some insight into the opportunities that integrate complexity concepts into model building offers, we extend the work previously undertaken on the complexity dimension in project management. We do so analyzing the results obtained with classical linear models and artificial neural networks when complexity is considered as another managerial parameter. For that purpose, we have used the International Software Benchmarking Standards Group data set. The results obtained proved the benefits of integrating the complexity of the projects at hand into the models. They also addressed the need of a complex system, such as artificial neural networks, to capture the fine nuances of the complex systems to be modeled, the projects.

[1]  Joana Geraldi Patterns of complexity: The thermometer of complexity , 2006 .

[2]  Hercilio Castellano Bohórquez Complexity and Co-Evolution: Continuity and Change in Socio-Economic Systems / Chaos Theory in the Social Sciences , 2012 .

[3]  Chiara Francalanci,et al.  The Impact of Complexity on Software Design Quality and Costs: An Exploratory Empirical Analysis of Open Source Applications , 2008, ECIS.

[4]  Shie Mannor,et al.  Basis Function Adaptation in Temporal Difference Reinforcement Learning , 2005, Ann. Oper. Res..

[5]  Kathrin Fischer,et al.  Combined location-routing problems—a neural network approach , 2009, Ann. Oper. Res..

[6]  Ana González-Marcos,et al.  TAO-robust backpropagation learning algorithm , 2005, Neural Networks.

[7]  Lynn Crawford,et al.  Fundamental uncertainties in projects and the scope of project management , 2006 .

[8]  Mark L. Gillenson,et al.  Employee Relationship Management: Applying the Concept of Personalization to U.S. Navy Sailors , 2004, Inf. Syst. Manag..

[9]  Stavros J. Perantonis,et al.  A Learning Framework for Neural Networks Using Constrained Optimization Methods , 2000, Ann. Oper. Res..

[10]  Mark Vandenbosch,et al.  Project Complexity and Efforts to Reduce Product Development Cycle Time , 1999 .

[11]  Bernhard Maschke,et al.  Dissipative Systems Analysis and Control , 2000 .

[12]  Terry Williams,et al.  Rethinking Project Management: Researching the actuality of projects , 2006 .

[13]  Grzegorz Waligóra,et al.  Simulated Annealing for Multi-Mode Resource-Constrained Project Scheduling , 2001, Ann. Oper. Res..

[14]  Paul C. Kainen,et al.  Continuity of Approximation by Neural Networks in Lp Spaces , 2001, Ann. Oper. Res..

[15]  Wai Kean Yap,et al.  Comparative analysis of artificial neural networks and dynamic models as virtual sensors , 2013, Appl. Soft Comput..

[16]  Jovan Popovic,et al.  Dynamic programming—neural network real-time traffic adaptive signal control algorithm , 2006, Ann. Oper. Res..

[17]  Fran Ackermann,et al.  The Effects of Design Changes and Delays on Project Costs , 1995 .

[18]  Sun-Jen Huang,et al.  An empirical analysis of risk components and performance on software projects , 2007, J. Syst. Softw..

[19]  K. Thangavel,et al.  Optimization of code book in vector quantization , 2006, Ann. Oper. Res..

[20]  Peter W. G. Morris,et al.  Practitioner development: From trained technicians to reflective practitioners , 2006 .

[21]  Mark Winter,et al.  Directions for future research in project management: The main findings of a UK government-funded research network , 2006 .

[22]  Kin Keung Lai,et al.  A Neural Network Application in Personnel Scheduling , 2004, Ann. Oper. Res..

[23]  Günter Radons,et al.  Collective Dynamics of Nonlinear and Disordered Systems , 2005 .

[24]  Joana Geraldi,et al.  Unraveling complexities in engineering projects , 2006 .

[25]  Weidong Xia,et al.  Complexity of Information Systems Development Projects: Conceptualization and Measurement Development , 2005, J. Manag. Inf. Syst..

[26]  B. Brogliato,et al.  Dissipative Systems Analysis and Control , 2000 .

[27]  T. M. Williams Holistic methods in project management , 1995 .

[28]  David Baccarini,et al.  The concept of project complexity—a review , 1996 .

[29]  J. R. Turner,et al.  Goals-and-methods matrix: coping with projects with ill defined goals and/or methods of achieving them , 1993 .

[30]  Donald W. Marquaridt Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation , 1970 .

[31]  Patricia Shaw,et al.  Complexity and Management: Fad or Radical Challenge to Systems Thinking? , 2002 .

[32]  Sven Bertelsen,et al.  CONSTRUCTION MANAGEMENT IN A COMPLEXITY PERSPECTIVE , 2004 .

[33]  Petya I. Ivanova,et al.  Indicator space configuration for early warning of violent political conflicts by genetic algorithms , 2000, Ann. Oper. Res..

[34]  Terry Williams,et al.  The Need for New Paradigms for Complex Projects , 1999 .

[35]  Ralph Levene,et al.  Focusing on business projects as an area for future research: An exploratory discussion of four different perspectives , 2006 .

[36]  Simon A. Austin,et al.  Modelling and managing project complexity , 2002 .

[37]  Peter Dalgaard,et al.  R Development Core Team (2010): R: A language and environment for statistical computing , 2010 .

[38]  Jiming Peng,et al.  A confidence voting process for ranking problems based on support vector machines , 2009, Ann. Oper. Res..

[39]  Andreas Charitou,et al.  ANNALS OF OPERATIONS RESEARCH , 2000 .

[40]  Terry Williams,et al.  Assessing and moving on from the dominant project management discourse in the light of project overruns , 2005, IEEE Transactions on Engineering Management.