The design structure matrix (DSM), also called the dependency structure matrix, has become a widely used modeling framework across many areas of research and practice. The DSM brings advantages of ...simplicity and conciseness in representation, and, supported by appropriate analysis, can also highlight important patterns in system architectures (design structures), such as modules and cycles. A literature review in 2001 cited about 100 DSM papers; there have been over 1000 since. Thus, it is useful to survey the latest DSM extensions and innovations to help consolidate progress and identify promising opportunities for further research. This paper surveys the DSM literature, primarily from archival journals, and organizes the developments pertaining to building, displaying, analyzing, and applying product, process, and organization DSMs. It then addresses DSM applications in other domains, as well as recent developments with domain mapping matrices (DMMs) and multidomain matrices (MDMs). Overall, DSM methods are becoming more mainstream, especially in the areas of engineering design, engineering management, management/organization science, and systems engineering. Despite significant research contributions, however, DSM awareness seems to be spreading more slowly in the realm of project management.
Complexity in product development (PD) projects can emanate from the product design, the development process, the development organization, the tools and technologies applied, the requirements to be ...met, and other domains. In each of these domains, complexity arises from the numerous elements and their multitude of relationships, such as between the components of the product being developed, between the activities to develop them, and among the people doing the activities. One approach to handing this complexity is to represent and analyze these domains’
design structures or
architectures. The design structure matrix (DSM) has proved to be a very helpful tool for representing and analyzing the architecture of an individual system such as a product, process, or organization. Like many tools, the DSM has been applied in a variety of areas outside its original domain, as researchers and practitioners have sought to leverage its advantages. Along the way, however, its fundamental rules (such as being a square matrix) have been challenged. In this paper, we formalize an approach to using a domain mapping matrix (DMM) to compare two DSMs of different project domains. A DMM is a rectangular (
m
×
n) matrix relating two DSMs, where
m is the size of DSM
1 and
n is the size of DSM
2. DMM analysis augments traditional DSM analyses. Our comparison of DSM and DMM approaches shows that DMM analysis offers several benefits. For example, it can help (1) capture the dynamics of PD, (2) show traceability of constraints across domains, (3) provide transparency between domains, (4) synchronize decisions across domains, (5) cross-verify domain models, (6) integrate a domain with the rest of a project or program, and (7) improve decision making among engineers and managers by providing a basis for communication and learning across domains.
ABSTRACT
Developing products that are more easily adaptable to future requirements can increase their overall value. Product adaptability is largely determined by choices about product architecture, ...especially modularity. Because it is possible to be too modular and/or inappropriately modular, deciding how and where to be modular in a cost‐effective way is an important managerial decision. In this article, we gather data from four case studies to model effects of firms’ product architecture decisions at the component level. We optimize an architecture adaptability value (AAV) measure that accounts for both the benefits of more architecture options and the costs of interfaces. The optimal architecture prompted each firm to rearchitect an existing product to increase its expected future profitability. Several insights emerged from the case evidence during this research. (i) Although decomposing an architecture into an increasing number of modules increases product adaptability, the amount of modularity is an insufficient predictor of the adaptability value of a system. AAV, which also accounts for interface costs, provides an improved measure of appropriate modularity. (ii) Managers can influence the path of architectural evolution in the direction of increased value. This influence may diminish but does not disappear as products become more mature. Also, modularity and innovations coevolved, as the new modularizations suggested by AAV optimization prompted and guided searches for further innovations. (iii) When presented with the concepts of options, interface costs, and AAV, the firms’ designers and managers were initially skeptical. However, in each case, the modelers were able to rearchitect an actual product not only with increased AAV by our model (theoretical improvement) but also with actual future benefits for their firm. Postproject reports from each firm confirmed that the AAV modeling and optimization approaches were indeed helpful, equipping them to increase the adaptability, cost‐efficiency, lifespan, and overall value of actual products. The evidence suggests that firms can benefit from designing products for adaptability, but that how they do so matters. This study expands our understanding of modularity and adaptability by illuminating managerial decisions and insights about appropriate approaches to each.
•Competitive collectors invest in collection service to attract customers perceiving convenience.•Remanufacturing and recycling of wasted products are simultaneously investigated.•Channel ...discrimination and collection convenience jointly drive the competitive collection.•A less competitive collection market increases remanufacturing rate but decreases recycling rate.
Competitive collection affects the remanufacturing and recycling of end-of-life products, and collectors competitively invest in improving channel convenience to attract customers to return such products. We propose a closed-loop supply chain model consisting of one manufacturer and one third-party collector to investigate competitive collection and channel convenience. With the comparison of monopolistic and competitive scenarios, we find that channel discrimination and collection convenience drive the competitive collection. Specifically, extreme channel discrimination reduces competitive collection, whereas, with reasonable channel discrimination, a more competitive market has a higher collection convenience level. In the market, customers who are less sensitive to the selling price prefer a more competitive collection market, since a competitive market can better reduce selling prices thanks to a remanufacturing benefit. Our model reveals important insights about how competitive collection and channel convenience drive the remanufacturing and recycling to be more sustainable.
Especially in large, complex projects, various aspects of process (activity network) information reside in separate models and diagrams that can become unsynchronized over time. Prior research has ...introduced the concept of a process architecture framework (PAF), which provides a solution by tying all the models and diagrams together in a single, rich process model with many views, where each view presents a subset of model information. This paper advances that work by (1) proposing an expandable PAF structure that organizes 27+ new and existing views, (2) suggesting examples of three new views that align well with specific concerns of users, and (3) presenting insights to guide the development of new views. Thus, this paper takes further steps towards the development of a PAF that provides at once both simplicity and completeness for project managers and other users of process models and project management information systems.
•A process architecture framework (PAF) helps to manage processes in complex projects.•A PAF is a rich process model with a portfolio of views.•This paper proposes an organizational structure for the portfolio of views.•It also demonstrates three new views, each well-aligned with particular concerns.•It also presents several insights to guide the development of new views.
Uncertainty, risk, and rework make it extremely challenging to meet goals and deliver anticipated value in complex projects, and conventional techniques for planning and tracking earned value do not ...account for these phenomena. This article presents a methodology for planning and tracking cost, schedule, and technical performance (or quality) in terms of a project’s key value attributes and threats to them. It distinguishes four types of value and two general types of risks. The “high jumper” analogy helps to consider how high the “bar” is set for a project (its set goals) and therefore how challenging and risky it will be. A project’s capabilities as a “jumper” (to clear the bar and meet its goals) determine the portion of its value at risk (VaR). By understanding the amounts of value, risk, and opportunity in a project, project managers can design it for appropriate levels of each. Project progress occurs through reductions in its VaR: Activities “add value” by chipping away at the project’s “anti-value”—the risks that threaten value. This perspective on project management incentivizes generating results that eliminate these threats, rather than assuming that value exists until proven otherwise.
Managers of multiple projects with overly constrained resources face difficult decisions in how to allocate resources to minimize the average delay per project or the time to complete the whole set ...of projects. We address the static
resource-constrained multi-project scheduling problem (RCMPSP) with two lateness objectives, project lateness and portfolio lateness. In this context, past research has reported conflicting results on the performance of activity priority rule heuristics and does not provide managers with clear guidance on which rule to use in various situations. Using recently improved measures for RCMPSP characteristics, we conducted a comprehensive analysis of 20 priority rules on 12,320 test problems generated to the specifications of project-, activity-, and resource-related characteristics—including network complexity and resource distribution and contention. We found several situations in which widely advocated priority rules perform poorly. We also confirmed that portfolio managers and project managers will prefer different priority rules depending on their local or global objectives. We summarize our results in two decision tables, the practical use of which requires managers to do only a rough, qualitative characterization of their projects in terms of complexity, degree of resource contention, and resource distribution.
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