Considering the systems engineering leading indicators to measure projects performance

To measure projects performance is available a wide range of methods which help project managers to effectively control the project progress and evaluate project results (Atkinson, 1999; Anantatmula, 2015). However remain several critical issues in their application: unbalanced development of KPIs types (Zidane, Johansen and Ekambaram, 2015), limited availability of leading KPIs (Kueng, Andres, and Wettstein, 2001), etc. Conversely, even if systems engineering measurement (SEM) is a more recent discipline, it offers very deep developments, published in several standards and guides (Wilbur, 1995; INCOSE Measurement Working Group, 1998; INCOSE Measurement Working Group, 2010; INCOSE & PSM, 2005; Roedler, et al., 2010). In particular, SEM uses lagging (reactive) measurement and defines methods to promote leading (predictive) measurement which provides insights before a problem arises (INCOSE & PSM, 2005; Roedler, et al., 2010). To improve project success rate, we propose to improve the measurement of projects performance, on which decisions rely in project management. One way is to extend the indicators to measure project performance by indicators used to measure systems engineering performance. This paper thus considers transferring and adapting the good practices in SE performance measurement such as described in SE guides as well as the set of SE leading indicators (SELIs) defined in (Roedler, et al., 2010) to project performance measurement. INTRODUCTION (BARC, 2009) is a global survey that explores the key challenges faced by organizations today and it is pointed that these challenges make performance management become a key enabler. In fact, since the early 1980s, performance management in general has been widely developed for adapting enterprises into complex business environment through introducing non-financial indicators. Some typical and classic PMSs have been proposed between 1980s and the 1990s, like the Performance Pyramid System (Lynch and Cross 1991) or the Balanced Scorecard (Kaplan and Norton 1992, 1996). Since, the family of PMSs grew with experts from different disciplines having brought fresh blood in the domain by blending the methods of system dynamic, total quality management, supply chain management and so on into the traditional PMSs. As one related diversification, the measurement of projects performance (MPP) has been receiving wide focus from both academy and practitioners (Lauras, Marques and Gourc, 2010; Zheng, et al., 2016). Focus has been diversified in many domains and some remarking results have been gotten, such as earned value project management (Anbari, 2003; Lipke, et al., 2009), performance measurement of engineering projects (Shi., et al., 2015; Guo and Yiu, 2015), benchmarking project performance management (Barber, 2014; Kim and Huynh, 2008 ), et al. Even through the research results have great contributions to the economic development and enterprise competitions, but it seems that all the prior MPP research has proposed a wide variety of KPIs or measures that evaluate the outcomes of a project based on the traditional “iron triangle”: “cost, time and quality” (Atkinson, 1999; Zidane, Johansen and Ekambaram, 2015). Some research provided a set of KPIs that can monitor and control project progress in time and set alarms whenever deviations of project