Project portfolio management: The linchpin in strategy processes

© Cambridge University Press 2017. Introduction Project portfolio management (PPM) is a central component of organizational project management (OPM), especially through its role in both the formulation and the delivery of organizational strategy. Corporate activities are increasingly carried out in the form of projects, in a trend that has been called “projectification” (Midler, 1995). In particular, for the implementation of complex innovations, it is not enough for organizations to focus on the successful management of individual innovation projects; they must also manage a large number of interdependent projects from a portfolio perspective. In today's dynamic environment, organizing by projects has become the rule rather than the exception, and organizations face challenges in managing these large project landscapes (programs and portfolios). The management of project portfolios is closely linked to the implementation of strategies. As strategies are ultimately implemented by projects, PPM – as a link between corporate strategy and projects – plays a central role (Meskendahl, 2010). In most research and practice this role is considered from a top-down perspective: strategies are considered to be a given yardstick for the prioritization and selection of projects and the allocation of resources. From such perspectives, PPM acts as the recipient of strategic goals and requirements that need only to be operationalized. However, the strategic management literature has long recognized the importance of emergent strategy; and that the realized strategy (the strategy that is actually implemented) often strays from the intended strategy (Mintzberg, 1978). Surprisingly, this is hardly considered in existing research models and standards for PPM (PMI, 2013). While there is some empirical evidence to suggest that hierarchical, formal, top-down approaches are not the actual practice of PPM (Christiansen & Varnes, 2009; Jerbrant & Gustavsson, 2013; Martinsuo, 2013), a much broader debate is needed to fully explore the role of PPM in the context of emergent strategies. The goal of this chapter is therefore to explore the role of PPM in the relationship between the formulation and implementation of strategy and consider both the top-down approach as well as the bottom-up strategy emergence. We first discuss emergence in the context of strategy implementation and the role of different phases in the PPM process that affect strategy implementation

The Role of Innovation Portfolio Management in the Nexus between Deliberate and Emergent Innovation Strategies

Planning and implementing innovation strategies are typically considered to be top-down processes and innovation portfolio management plays a decisive role in this context by aligning the project portfolio to the firm’s strategy. However, in strategic management research it is well accepted that strategies are not solely deliberate but can also be emergent. Thus, between top-down innovation strategy formulation and its implementation, responding dialectic elements are required to sense emerging strategic impetuses and cope with changing environmental conditions. This paper addresses the role of portfolio management in the nexus between strategy formulation and implementation. Using a sample of 182 medium and large firms with two informants, we show that portfolio management not only fosters the implementation of intended innovation strategies through vertical integration but also discloses strategic opportunities by unveiling emerging patterns. The findings show that portfolio management contributes to innovation portfolio success by supporting both the implementation of deliberate and emergent strategies through vertical integration and strategic disclosure. The effects are complementary in that both activities increase the positive effects of the other. Furthermore we find that strategic control (i.e. premise control, implementation control, and strategic surveillance) on a portfolio level indirectly contributes to success mediated by vertical integration and strategic disclosure. Finally, we show that the influence of vertical integration on innovation portfolio success is reduced under high environmental turbulence

Business Case Control in Project Portfolios - An Empirical Investigation of Performance Consequences and Moderating Effects

© 1988-2012 IEEE. Practitioners place strong emphasis on business cases with the expectation that using business cases to inform and drive investment decisions will assist in creating value from those investments. Maximizing the value generated by project investments is a central aim of the project portfolio management, and the business case provides the underlying rationale for the evaluation of the value created in each project. However, research regarding the use of business cases at a project portfolio level is scarce, and there is a little guidance for portfolio managers on when and how to control the business cases. We identify three elements of a business case control at the portfolio level - the initial review, the ongoing monitoring during the project execution, and the postproject tracking until the business case is realized - and investigate the relationship between business case control and project portfolio success. Furthermore, we analyze enablers and contingencies for the application of the business case control. Based on a cross-industry sample of 183 firms, we find that the business case control is positively related to the project portfolio success. Accountability for business case realization and corresponding incentive systems increase this positive effect. Finally, we show that the portfolio complexity also positively moderates the relationship

Reviewing GPU architectures to build efficient back projection for parallel geometries

Back-Projection is the major algorithm in Computed Tomography to reconstruct images from a set of recorded projections. It is used for both fast analytical methods and high-quality iterative techniques. X-ray imaging facilities rely on Back-Projection to reconstruct internal structures in material samples and living organisms with high spatial and temporal resolution. Fast image reconstruction is also essential to track and control processes under study in real-time. In this article, we present efficient implementations of the Back-Projection algorithm for parallel hardware. We survey a range of parallel architectures presented by the major hardware vendors during the last 10 years. Similarities and differences between these architectures are analyzed and we highlight how specific features can be used to enhance the reconstruction performance. In particular, we build a performance model to find hardware hotspots and propose several optimizations to balance the load between texture engine, computational and special function units, as well as different types of memory maximizing the utilization of all GPU subsystems in parallel. We further show that targeting architecture-specific features allows one to boost the performance 2–7 times compared to the current state-of-the-art algorithms used in standard reconstructions codes. The suggested load-balancing approach is not limited to the back-projection but can be used as a general optimization strategy for implementing parallel algorithms