New Product Development Resource Forecasting

Forecasting resource requirements for new product development (NPD) projects is essential for both strategic and tactical planning. Sophisticated, elegant planning tools to present data and inform decision‐making do exist. However, in NPD, such tools run on unreliable, estimation‐based resource information derived through undefined processes. This paper establishes that existing methods do not provide transparent, consistent, timely or accurate resource planning information, highlighting the need for a new approach to resource forecasting, specifically in the field of NPD. The gap between the practical issues and available methods highlights the possibility of developing a novel design of experiments approach to create resource forecasting models.

[1]  Yong Hu,et al.  Systematic literature review of machine learning based software development effort estimation models , 2012, Inf. Softw. Technol..

[2]  Guilherme Horta Travassos,et al.  Cross versus Within-Company Cost Estimation Studies: A Systematic Review , 2007, IEEE Transactions on Software Engineering.

[3]  Antonio Davila,et al.  Management Control Systems in Early‐Stage Startup Companies , 2007 .

[4]  Albert L. Lederer,et al.  Information systems software cost estimating: a current assessment , 1993, J. Inf. Technol..

[5]  Christoph H. Loch,et al.  Dynamic Portfolio Selection of NPD Programs Using Marginal Returns , 2002, Manag. Sci..

[6]  Soumitra Dutta,et al.  Performance Evaluation of General and Company Specific Models in Software Development Effort Estimation , 1999 .

[7]  Emad A. El-Sebakhy,et al.  Functional networks as a new data mining predictive paradigm to predict permeability in a carbonate reservoir , 2012, Expert Syst. Appl..

[8]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[9]  Stylianos Kavadias,et al.  Handbook of New Product Development Management , 2007 .

[10]  Mario Bourgault,et al.  Dimensions of Uncertainty and Their Moderating Effect on New Product Development Project Performance , 2008 .

[11]  Colin J Burgess,et al.  Can genetic programming improve software effort estimation? A comparative evaluation , 2001, Inf. Softw. Technol..

[12]  Changya Hu,et al.  The influence of centrifugal and centripetal forces on ERP project success in small and medium-sized enterprises in China and Taiwan , 2007 .

[13]  Chor-Beng Anthony Liew,et al.  Strategic integration of knowledge management and customer relationship management , 2008, J. Knowl. Manag..

[14]  Abigail Hird A systems approach to resource planning in new product development , 2012 .

[15]  David N. Ford,et al.  Overcoming the 90% Syndrome: Iteration Management in Concurrent Development Projects , 2003, Concurr. Eng. Res. Appl..

[16]  Buyun Sheng,et al.  ERP and PDM integration technology to support collaborative product development , 2010, Int. J. Bus. Inf. Syst..

[17]  D. Tranfield,et al.  Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review , 2003 .

[18]  Jeorge S. Hurtarte,et al.  Best Practices for Fabless Companies , 2007 .

[19]  Samuel P. Marin,et al.  Balancing and optimizing a portfolio of R&D projects , 2001 .

[20]  Ramanath Subramanyam,et al.  In Search of Efficient Flexibility: Effects of Software Component Granularity on Development Effort, Defects, and Customization Effort , 2012 .

[21]  J. Webb The Mismanagement of Innovation , 1992 .

[22]  M. P. Biswal,et al.  A zero-one goal programming approach for project selection , 2007 .

[23]  Gregory Huet,et al.  Manufacturing Process Management: iterative synchronisation of engineering data with manufacturing realities , 2007 .

[24]  Robert G. Cooper,et al.  Defining the new product strategy , 1987, IEEE Transactions on Engineering Management.

[25]  Gavriel Salvendy,et al.  Concurrent engineering and virtual reality for human resource planning , 2000 .

[26]  B. Yegnanarayana,et al.  Artificial Neural Networks , 2004 .

[27]  Paul G. Maropoulos,et al.  Linking design and manufacturing domains via web-based and enterprise integration technologies , 2010, Int. J. Comput. Appl. Technol..

[28]  R. Cooper,et al.  New Product Portfolio Management: Practices and Performance , 1999 .

[29]  Mark Lehrer,et al.  Modularity vs programmability in design of international products: Beyond the standardization-adaptation tradeoff? , 2009 .

[30]  Edward G. Anderson,et al.  A Hierarchical Product Development Planning Framework , 2005 .

[31]  Richard Messnarz,et al.  Qualification and certification for the competitive edge in Integrated Design , 2010 .

[32]  Research on an Information Integration Framework on the Large Complex Product Development PMIS with ERP , 2006 .

[33]  Emilia Mendes,et al.  Why comparative effort prediction studies may be invalid , 2009, PROMISE '09.

[34]  Barbara A. Kitchenham,et al.  Empirical studies of assumptions that underlie software cost-estimation models , 1992, Inf. Softw. Technol..

[35]  Inka Vilpola,et al.  DEVELOPMENT AND EVALUATION OF A CUSTOMER- CENTERED ERP IMPLEMENTATION METHOD , 2009 .

[36]  Vincent Cheutet,et al.  A PLCS framework for PDM/ERP interoperability , 2011 .

[37]  Paul G. Maropoulos,et al.  Application of product data management technologies for enterprise integration , 2003, Int. J. Comput. Integr. Manuf..

[38]  Jiuping Xu,et al.  A fuzzy random resource-constrained scheduling model with multiple projects and its application to a working procedure in a large-scale water conservancy and hydropower construction project , 2012, J. Sched..

[39]  Ali Yassine,et al.  Information hiding in product development: the design churn effect , 2003 .

[40]  Manuel Castejón Limas,et al.  Effort estimates through project complexity , 2011, Ann. Oper. Res..

[41]  Christoph H. Loch,et al.  Project Selection Under Uncertainty , 2004 .

[42]  Michael J. Prietula,et al.  Examining the Feasibility of a Case-Based Reasoning Model for Software Effort Estimation , 1992, MIS Q..

[43]  Barry W. Boehm,et al.  Bayesian Analysis of Empirical Software Engineering Cost Models , 1999, IEEE Trans. Software Eng..

[44]  Stylianos Kavadias,et al.  A Theoretical Framework for Managing the New Product Development Portfolio: When and How to Use Strategic Buckets , 2008, Manag. Sci..

[45]  J. Pfeffer,et al.  Economic Evaluation: The Effect of Money and Economics on Attitudes About Volunteering , 2008 .

[46]  Magne Jørgensen,et al.  A review of studies on expert estimation of software development effort , 2004, J. Syst. Softw..

[47]  B. Wernerfelt,et al.  The resource‐based view of the firm: Ten years after , 1995 .

[48]  David N. Ford,et al.  The Liar's Club: Concealing Rework in Concurrent Development , 2003, Concurr. Eng. Res. Appl..

[49]  Abraham Sin Oih Yu,et al.  Development Resource Planning: Complexity of Product Development and the Capacity to Launch New Products , 2010 .

[50]  R. O. Chao,et al.  A Theoretical Framework for Managing the NPD Portfolio: When and How to Use Strategic Buckets , 2008 .

[51]  Christoph H. Loch,et al.  Communication and Uncertainty in Concurrent Engineering , 1998 .

[52]  P. John Clarkson,et al.  A Classification of Uncertainty for Early Product and System Design , 2007 .

[53]  Parag C. Pendharkar,et al.  Probabilistic estimation of software size and effort , 2010, Expert Syst. Appl..

[54]  S. R. Rosenthal,et al.  Towards holistic front ends in new product development , 1998 .

[55]  Dimitris Mourtzis,et al.  Digital manufacturing: History, perspectives, and outlook , 2009 .

[56]  Kulwant S. Pawar,et al.  Performance measurement for product design and development in a manufacturing environment , 1999 .

[57]  Bernhard R. Katzy,et al.  Learning capabilities and the growth of technology-based new ventures , 2010, Int. J. Technol. Manag..

[58]  Jean-Marc Desharnais,et al.  A comparison of software effort estimation techniques: Using function points with neural networks, case-based reasoning and regression models , 1997, J. Syst. Softw..

[59]  Bart Baesens,et al.  Data Mining Techniques for Software Effort Estimation: A Comparative Study , 2012, IEEE Transactions on Software Engineering.

[60]  Christoph H. Loch,et al.  Chapter 12 – Coordination and information exchange , 2008 .

[61]  Ellis Horowitz,et al.  Software Cost Estimation with COCOMO II , 2000 .

[62]  Shaw C. Feng Manufacturing planning and execution software interfaces , 2000 .

[63]  Christos T. Maravelias,et al.  Scheduling of testing tasks and resource planning in new product development using stochastic programming , 2009, Comput. Chem. Eng..

[64]  B. Wernerfelt,et al.  A Resource-Based View of the Firm , 1984 .

[65]  Liang Hou SOURCING CONFIGURATION FOR PRODUCT MASS CUSTOMIZATION , 2006 .

[66]  Christoph H. Loch,et al.  Project Selection Under Uncertainty: Dynamically Allocating Resources to Maximize Value , 2004 .

[67]  Claudia Eckert,et al.  Investigating design process performance under uncertainty , 2008 .

[68]  Jan Goossenaerts,et al.  A Multi-Level Model-Driven Regime for Value-Added Tax Compliance in ERP Systems , 2009, Comput. Ind..

[69]  Ayse Basar Bener,et al.  Exploiting the Essential Assumptions of Analogy-Based Effort Estimation , 2012, IEEE Transactions on Software Engineering.