Influential Article Review - Using BPM Capacity Preparation and Process Development in Value-Based Operations

This paper examines operations management. We present insights from a highly influential paper. Here are the highlights from this paper: Business process management (BPM) is an important area of organizational design and an acknowledged source of corporate performance. Over the last decades, many approaches, methods, and tools have been proposed to discover, design, analyze, enact, and improve individual processes. At the same time, BPM research has been and still is paying ever more attention to BPM itself and the development of organizations’ BPM capability. Little, however, is known about how to develop an organization’s BPM capability and improve individual processes in an integrated manner. To address this research gap, we developed a planning model. This planning model intends to assist organizations in determining which BPM- and process-level projects they should implement in which sequence to maximize their firm value, catering for the projects’ effects on process performance and for interactions among projects. We adopt the design science research (DSR) paradigm and draw from project portfolio selection as well as value-based management as justificatory knowledge. For this reason, we refer to our approach as value-based process project portfolio management. To evaluate the planning model, we validated its design specification by discussing it against theory-backed design objectives and with BPM experts from different organizations. We also compared the planning model with competing artifacts. Having instantiated the planning model as a software prototype, we validated its applicability and usefulness by conducting a case based on real-world data and by challenging the planning model against accepted evaluation criteria from the DSR literature. For our overseas readers, we then present the insights from this paper in Spanish, French, Portuguese, and German

Influential Article Review - Process Based on Values Integrated Development of BPM Competence Development and Process Optimization: Project Asset Management

This paper examines business process management. We present insights from a highly influential paper. Here are the highlights from this paper: Business process management (BPM) is an important area of organizational design and an acknowledged source of corporate performance. Over the last decades, many approaches, methods, and tools have been proposed to discover, design, analyze, enact, and improve individual processes. At the same time, BPM research has been and still is paying ever more attention to BPM itself and the development of organizations’ BPM capability. Little, however, is known about how to develop an organization’s BPM capability and improve individual processes in an integrated manner. To address this research gap, we developed a planning model. This planning model intends to assist organizations in determining which BPM- and process-level projects they should implement in which sequence to maximize their firm value, catering for the projects’ effects on process performance and for interactions among projects. We adopt the design science research (DSR) paradigm and draw from project portfolio selection as well as value-based management as justificatory knowledge. For this reason, we refer to our approach as value-based process project portfolio management. To evaluate the planning model, we validated its design specification by discussing it against theory-backed design objectives and with BPM experts from different organizations. We also compared the planning model with competing artifacts. Having instantiated the planning model as a software prototype, we validated its applicability and usefulness by conducting a case based on real-world data and by challenging the planning model against accepted evaluation criteria from the DSR literature. For our overseas readers, we then present the insights from this paper in Spanish, French, Portuguese, and German

A conceptual framework for changes in Fund Management and Accountability relative to ESG issues

Major developments in socially responsible investment (SRI) and in environmental, social and governance (ESG) issues for fund managers (FMs) have occurred in the past decade. Much positive change has occurred but problems of disclosure, transparency and accountability remain. This article argues that trustees, FM investors and investee companies all require shared knowledge to overcome, in part, these problems. This involves clear concepts of accountability, and knowledge of fund management and of the associated ‘chain of accountability’ to enhance visibility and transparency. Dealing with the problems also requires development of an analytic framework based on relevant literature and theory. These empirical and analytic constructs combine to form a novel conceptual framework that is used to identify a clear set of areas to change FM investment decision making in a coherent way relative to ESG issues. The constructs and the change strategy are also used together to analyse how one can create favourable conditions for enhanced accountability. Ethical problems and climate change issues will be used as the main examples of ESG issues. The article has policy implications for the UK ‘Stewardship Code’ (2010), the legal responsibilities of key players and for the ‘Carbon Disclosure Project’

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Local flexibility market design for aggregators providing multiple flexibility services at distribution network level

This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.Postprint (published version

Socio-technical transition processes: A real option based reasoning.

Using a real option reasoning perspective we study the uncertainties and irreversibilities that impact the investment decisions of firms during the different phases of technological transitions. The analysis of transition dynamics via real options reasoning allows the provision of an alternative and more qualified explanation of investment decisions according to the sequentiality of pathways considered. In our framework, flexibility management through option investments concerns both the incumbent and the future technological regime. In the first case it refers to ex-post flexibility management and in the second case to ex-ante flexibility management.

Complexity-based learning and teaching: a case study in higher education

This paper presents a learning and teaching strategy based on complexity science and explores its impacts on a higher education game design course. The strategy aimed at generating conditions fostering individual and collective learning in educational complex adaptive systems, and led the design of the course through an iterative and adaptive process informed by evidence emerging from course dynamics. The data collected indicate that collaboration was initially challenging for students, but collective learning emerged as the course developed, positively affecting individual and team performance. Even though challenged, students felt highly motivated and enjoyed working on course activities. Their perception of progress and expertise were always high, and the academic performance was on average very good. The strategy fostered collaboration and allowed students and tutors to deal with complex situations requiring adaptation

Improving Technology Transfer and Research Commercialisation in the Irish Food Innovation System

End of project reportThe process by which knowledge generated by publicly-funded research is transferred to industry – technology transfer – has been criticised as being inefficient and having limited success. This research project aimed to obtain a better understanding of the technology transfer process and thereby contribute to policy development and provide guidance for researchers to improve the process. Through a series of focus groups, surveys, case studies and depth interviews, the research identified five key challenges that exist in the context of the Irish food innovation system. These relate to communication, industry capabilities, research capabilities, strategic management and socialisation. To address these challenges, a selection of tools, illustrative case studies and recommendations for a range of stakeholders on how to deal with each of these challenges is provided on the project website (www.dit.ie/toolbox/)