Abstract
As business competition increases, there is pressure on software development projects to become more productive and efficient. Previous research has shown that quality planning is a key factor in enhancing project performance. Thus, this article reports on the successful development and implementation of a tool (QPLAN) that enhances software development project performance by evaluating the planning quality of any type of software project and introducing best planning practices (such as references from historical data) that suggest how to manage projects in an appropriate manner, including encompassing lessons learned and involving the customer in the development process. This is applied research aimed at solving a real problem; thus, Design Science Research was adopted as the research methodology and the design science research process (DSRP) model was selected to conduct it. This artifact was designed for the project management literature, and implemented and validated in 11 organizations in five countries.
TopIntroduction
Software organizations are taking over large slices of the economy from other sectors (Krishnan, Kriebel, Kekre, & Mukhopadhyay, 2000). For example, Google is the largest direct-marketing platform, while Netflix is the largest video service based on number of subscribers (Andreessen, 2011). In the automotive industry, cars have been launched on the market with software to control their engines and safety features, entertain passengers, and guide drivers to their destination. In the oil and gas industry, software has been used for the automation and control of operations that are essential for exploration and refining efforts. The defense industry has planes that do not require human pilots and missiles that achieve their targets guided by software. In some cases, software organizations have become leaders in traditional industries—for example, Amazon is currently the world’s largest bookseller. More than one decade ago, Borders sold its online business to Amazon because Borders believed that online book sales were unimportant (Andreessen, 2011).
Despite the significant influence of software around the world, the low performance of software development projects has plagued the IT industry for years (Krishnan et al., 2000). In 2000, only 28 percent of software projects were considered successful—that is, were completed on time and on budget and offered all features and functions as initially specified. However, 23 percent failed and, of the remaining fraction, the projects had higher costs than the original estimates, were completed behind schedule, or offered fewer features or functions than originally specified (Standish Group, 2013). For customers, unsuccessful projects may lead to a lack of productivity or loss of business, and the implications are equally problematic for organizations (Moløkken-Østvold & Jørgensen, 2005). In 2013, the results were slightly better; however, the success rate was still low, with only 39 percent of projects completed successfully (Stojanov, Dobrilovic, & Stojanov, 2013). Motivated by the significance of the software industry in the contemporary world and the frequently low performance of software development projects, the following research question was formulated to guide this research:
How can the planning quality effectiveness of software development projects be evaluated and improved?
Key Terms in this Chapter
QPM: This abbreviation stands for “quality of planning by manager”. QPM is a measure from the PMPQ model ( Zwikael & Sadeh, 2007 ) that evaluates the planning-quality processes for which a project manager is responsible.
QPLAN: This abbreviation stands for “quality of planning tool”. QPLAN is a tool that enhances the performance of software development projects by evaluating the quality of project planning of any type of software project and introducing best planning practices in the development process.
Planning Quality: This is equivalent to “quality of planning” and refers to a project’s planning stage, which a project manager leads and commences immediately after project approval. During the planning stage, the project manager develops a project plan that should be aligned with the business case and provide a clear direction for the work to be completed during project execution. Planning quality measures the quality of the planning processes undertaken by the project manager and directly affects the quality of the project plan document.
PMPQ Model: This abbreviation stands for “project management planning quality”. Zwikael & Globerson (2004) developed the PMPQ model to evaluate the quality of project planning through the evaluation of planning products. The model has been validated and utilized extensively in the literature (e.g., Barry & Uys, 2011 ; Masters & Frazier, 2007 ; Papke-Shields et al., 2010 ; Rees-Caldwell & Pinnington, 2013 ; Zwikael & Ahn, 2011 ; Zwikael et al., 2014 ; Zwikael & Globerson, 2006 ; Zwikael & Sadeh, 2007 ).
Project Management Success: This success dimension is used for testing the efficiency of the development process to deliver the project’s outputs ( Zwikael & Smyrk, 2011 ). QPLAN calculates it from efficiency ( Lechler & Dvir, 2010 ), which values range from 0.0 to 1.0.
Project Ownership Success: This success dimension is used for testing the the perceived benefits of the project for customers, the organization and society ( Zwikael & Smyrk, 2011 ). QPLAN calculates it from the average of effectiveness, business results and customer satisfaction ( Lechler & Dvir, 2010 ), which values range from 0.0 to 1.0.
QIPlan: This abbreviation stands for “planning quality index”. QIPlan is an index calculated by QPLAN to represent the quality of project planning of software development projects from the average of QPM and QCM and ranges from 0.0 (lowest) to 1.0 (highest).
Cognitive Maps: A methodology based on expert knowledge ( Stach et al., 2005 ) aimed at graphically describing the behavior of a system ( Rodriguez-Repiso et al., 2007 ). This is used in numerous areas (such as electrical engineering, supervisory systems and medicine) ( Alizadeh, Ghazanfari, Jafari, & Hooshmand, 2008 ) to solve a variety of practical problems (such as transportation planning and technology management) ( Osei-Bryson, 2004 ) and in decision-making systems ( Sharif, Irani, & Weerakkoddy, 2010 ). For project planning, cognitive maps are used to identify critical paths ( Banerjee, 2009 ), help structure issues ( Eden, 2004 ), support risk analysis ( Ngai & Wat, 2005 ; Salmeron & Lopez, 2012 ), and model success factors ( Salmeron, 2009 ).
QCM: This abbreviation stands for “quality of planning through cognitive maps”. QCM evaluates the quality of planning of software development projects by evaluating 55 factors, organized in 21 cognitive maps that affect project planning.