Dynamism in Complex Engineering: Explaining Uncertainty Growth Through Uncertainty Masking

Abstract

The development of uncertainty over the progression of a project (i.e. dynamism) is a central issue in engineering management; however, it has been little explored. This paper answers the question of how uncertainty develops over the course of complex engineering. We present a case of a renewable energy power plant where we performed content analysis on over 54,000 e-mails. The findings reveal a new mechanism affecting uncertainty development. We call this mechanism 'uncertainty masking' and define it as: the process through which a 'root uncertainty' is misidentified by the project team, resulting in the creation and management of a 'symptomatic uncertainty'. Root and symptomatic uncertainty types compound over time and hamper uncertainty resolution, leading to growth in level of uncertainty during later project stages. We describe the impact of uncertainty masking on the u-shape level of uncertainty in the case project. This research contributes to the engineering-management literature by explaining observations of uncertainty growth, which existing theory is unable to explain. We thus significantly advance uncertainty theory in engineering management. Managerial relevance statementThis research identifies a core challenge for engineering managers, particularly in complex engineering. Managers need to be able to correctly identify the uncertainty types their engineering project face. Specifically in complex engineering, this may be a significant challenge as shown by this research. For example, technical uncertainty may be misidentified by the project team because it creates challenges for supplier management or internal organisation. However, identifying uncertainty types correctly reduces the potential adverse effects of uncertainty in the later project stages, where the project team can deliver and integrating engineering outputs instead of re-designing and re-developing technical parts.

Exploring the link between uncertainty and project activities in new product development

“…The propositional relationships outlined in Figure 1 take a first step towards addressing the two major needs of engineering designers when dealing with uncertainty in NPD i.e. uncertainty identification and appropriate response (Kreye et al 2020).…”

“…In particular, this is essential to understanding if the specific instances relating to the uncertainty types are conceptually consistent with prior descriptions in the literature. Further, a case-based approach has also been used in a number of major prior studies of uncertainty and project activity (O'Connor and Rice 2013; Kreye et al 2020;Unger and Eppinger 2011), providing a basis for comparison with this work.…”

“…The data were collected via multiple sources (Yin 2018) following best practice (Gibbert, Ruigrok, and Wicki 2008;Yin 2018) as well as prior works in this context (Marion, Friar, and Simpson 2012;Kreye et al 2020). These included over 40 semistructured interviews, extensive observation at the case company (over four months), project reports, process plans, Gantt charts and other secondary documentation, and further unstructured meetings with all major participants before and after data collection.…”

“…This gap is of critical importance because in order to effectively deal with uncertainty NPD team leaders and engineering designers must be able to: i) identify the specific uncertainty type, and ii) carry out those project activities best suited to its resolution (O'Connor and Rice 2013). Misidentifying the type of uncertainty or taking ill-suited remedial action can have significant negative consequences on project outcomes, including increasing uncertainty, rework, overruns, or project failure (Kreye et al 2020). Despite this, the relationship between uncertainty types and specific project activities remains ambiguous.…”

Where next for design research? Understanding research impact and theory building

“…Notably, there is little attention to management theory (2% of total articles), despite this being an important context for design (Kleinsmann & Valkenburg, 2008;Kreye, Cash, Parraguez, & Maier, 2019;Robinson, 2012), and linked to both design thinking (Brown, 2008;Dörner, 1999) and team processes (Cash, Dekoninck, & Ahmed-Kristensen, 2017;Hult, Ketchen, & Slater, 2004;Kleinsmann & Valkenburg, 2008). Further, there is little attention to theory dealing with design methods and tools (6% of total articles).…”