The Relationship between Customer Collaboration and Software Project Overruns

Most agile projects rely heavily on good collaboration with the customer in order to achieve project goals and avoid overruns. However, the role of the customer in software projects is not fully understood. Often, successful projects are attributed to developer competence, while unsuccessful projects are attributed to customer incompetence. A study was conducted on eighteen of the latest projects of a software contractor. Quantitative project data was collected, and project managers interviewed, on several issues related to estimates, key project properties, and project outcome. It was found that in projects where collaboration was facilitated by daily communication between the contractor and the customer, they experienced a lesser magnitude of effort overruns. In addition, employing a contract that facilitates risk-sharing may also have a positive impact.

[1]  Albert L. Lederer,et al.  Nine management guidelines for better cost estimating , 1992, CACM.

[2]  P. Cozby,et al.  Methods in behavioral research, 5th ed. , 1993 .

[3]  Ken Schwaber,et al.  Agile Project Management with Scrum , 1980 .

[4]  Alistair Cockburn,et al.  The end of software engineering and the start of economic-cooperative gaming , 2004, Comput. Sci. Inf. Syst..

[5]  Mike Cohn,et al.  Agile Estimating and Planning , 2005 .

[6]  Victor R. Basili,et al.  Iterative and incremental developments. a brief history , 2003, Computer.

[7]  P. Cozby,et al.  Methods in behavioral research , 1977 .

[8]  Magne Jørgensen,et al.  An effort prediction interval approach based on the empirical distribution of previous estimation accuracy , 2003, Inf. Softw. Technol..

[9]  Diane Jamieson,et al.  Agile procurement: new acquisition approach to agile software development , 2005, 31st EUROMICRO Conference on Software Engineering and Advanced Applications.

[10]  Magne Jørgensen,et al.  Reasons for software effort estimation error: impact of respondent role, information collection approach, and data analysis method , 2004, IEEE Transactions on Software Engineering.

[11]  Lionel C. Briand,et al.  Resource modeling in software engineering , 2002 .

[12]  N. Nakagawa,et al.  Method to estimate parameter values in software prediction models , 1991 .

[13]  Martin Fowler,et al.  Planning Extreme Programming , 2000 .

[14]  Kjetil Moløkken-Østvold,et al.  Combining Estimates with Planning Poker--An Empirical Study , 2007, 2007 Australian Software Engineering Conference (ASWEC'07).

[15]  Stephen A. McGuire,et al.  Introductory Statistics , 2007, Technometrics.

[16]  Albert L. Lederer,et al.  Causes of inaccurate software development cost estimates , 1995, J. Syst. Softw..

[17]  Barbara A. Kitchenham,et al.  An empirical validation of the relationship between the magnitude of relative error and project size , 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

[18]  Magne Jørgensen,et al.  A comparison of software project overruns - flexible versus sequential development models , 2005, IEEE Transactions on Software Engineering.

[19]  Kjetil Molkken,et al.  A Review of Surveys on Software Effort Estimation , 2003 .

[20]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[21]  June M. Verner,et al.  Case study: factors for early prediction of software development success , 2002, Inf. Softw. Technol..

[22]  Diane Jamieson,et al.  Agile Procurement and Dynamic Value for Money to Facilitate Agile Software Projects , 2006, 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (EUROMICRO'06).

[23]  June M. Verner,et al.  In the 25 years since The Mythical Man-Month what have we learned about project management? , 1999, Inf. Softw. Technol..

[24]  Magne Jørgensen,et al.  A framework for the analysis of software cost estimation accuracy , 2006, ISESE '06.

[25]  Harlan D. Mills.  Software Development , 1976, IEEE Transactions on Software Engineering.

[26]  Issa Traoré,et al.  Measurement Framework for Software Privilege Protection Based on User Interaction Analysis , 2005, IEEE METRICS.