Service-oriented modeling and architecture (SOMA) has been used to conduct projects of varying scope in multiple industries worldwide for the past five years. We report on the usage and structure of the method used to effectively analyze, design, implement, and deploy service-oriented architecture (SOA) projects as part of a fractal model of software development. We also assert that the construct of a service and service modeling, although introduced by SOA, is a software engineering best practice for which an SOA method aids both SOA usage and adoption. In this paper we present the latest updates to this method and share some of the lessons learned. The SOMA method incorporates the key aspects of overall SOA solution design and delivery and is integrated with existing software development methods through a set of placeholders for key activity areas, forming what we call solution templates. We also present a fractal model of software development that can enable the SOMA method to evolve in an approach that goes beyond the iterative and incremental and instead leverages method components and patterns in a recursive, self-similar manner opportunistically at points of variability in the life cycle.
Since a series of academic case studies had revealed Toyota’s unique product development practices to the world, a flurry of research has been conducted into set-based design, also known as set-based concurrent engineering. In this paper, we review work related to set-based design across academic communities in efforts to find common themes and influences. After a review of this literature, we inductively arrive at two Principles of Set-Based Thinking: considering sets of distinct alternatives concurrently and delaying convergent decision making. These Principles allow us to articulate a working description of set-based design. We then examine these two Principles at work in a case example of a common theoretical construct in design.
An innovating organization faces the challenge of how to prioritize distinct goals of novelty and value, both of which underlie innovation. Popular practitioner frameworks like Agile management suggest that organizations can adopt an iterative approach of frequent meetings to prioritize between these goals, a practice we refer to as iterative coordination. Despite iterative coordination’s widespread use in innovation management, its effects on novelty and value in innovation remain unknown. With the information technology firm Google, we embed a field experiment within a hackathon software development competition to identify the effect of iterative coordination on innovation. We find that iterative coordination causes firms to implicitly prioritize value in innovation: Although iteratively coordinating firms develop more valuable products, these products are simultaneously less novel. Furthermore, by tracking software code, we find that iteratively coordinating firms favor integration at the cost of knowledge-creating specialization. A follow-on laboratory study documents that increasing the frequency and opportunities to reprioritize goals in iterative coordination meetings reinforces value and integration, while reducing novelty and specialization. This article offers three key contributions: highlighting how processes to prioritize among multiple performance goals may implicitly favor certain outcomes; introducing a new empirical methodology of software code version tracking for measuring the innovation process; and leveraging the emergent phenomenon of hackathons to study new methods of organizing.
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