D-Wave Systems: Building a Quantum Computer

Alan D. MacCormack; Ajay  Agrawal; Rebecca  Henderson

Case | HBS Case Collection | April 2004

D-Wave Systems: Building a Quantum Computer

by Alan D. MacCormack, Ajay Agrawal and Rebecca Henderson

Abstract

D-Wave Systems is a start-up seeking to commercialize a quantum computer. Its business model is unique: as of 2003, it had very few technical resources within the firm. Instead, it financed a series of projects undertaken at universities and government labs. In return for partial funding, these organizations gave D-Wave the ownership of--or exclusive rights to--intellectual property developed in the project. Geordie Rose, CEO of D-Wave, wonders how long this model is appropriate in contrast to the alternative of centralizing the research in an in-house facility, with all the costs this would incur.

Keywords: Business Model; Business Startups; Engineering; Investment; Intellectual Property; Product Development; Research and Development; Commercialization; Computer Industry;

Format: Print

28 pages

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Citation:

MacCormack, Alan D., Ajay Agrawal, and Rebecca Henderson. "D-Wave Systems: Building a Quantum Computer." Harvard Business School Case 604-073, April 2004.

Other Article | Academy of Management Annual Meeting Proceedings | 2017

Designing an Agile Software Portfolio Architecture: The Impact of Coupling on Performance

Alan MacCormack and Robert Lagerstrom

The modern industrial corporation encompasses a myriad of different software applications, each of which must work in concert to deliver functionality to end-users. However, the increasingly complex and dynamic nature of competition in today’s product-markets dictates that this software portfolio be continually evolved and adapted, in order to meet new business challenges. This ability – to rapidly update, improve, remove, replace, and reimagine the software applications that underpin a firm’s competitive position – is at the heart of what has been called IT agility. Unfortunately, little work has examined the antecedents of IT agility, with respect to the choices a firm makes when designing its “Software Portfolio Architecture.”
We address this gap in the literature by exploring the relationship between software portfolio architecture and IT agility at the level of the individual applications in the architecture. In particular, we draw from modular systems theory to develop and test a series of hypotheses about how different types of coupling impact three specific dimensions of agility: the ability to update, remove and replace software applications in the firm’s portfolio. We test our hypotheses with data from a financial services firm, encompassing over 1,000 software applications and 3,000 dependencies between them. We capture data at two points in time, allowing us to identify changes in the software portfolio, and hence to develop robust measures of IT agility.

Keywords: Software; Design; Organizational Change and Adaptation; Performance Effectiveness;

Citation:

MacCormack, Alan, and Robert Lagerstrom. "Designing an Agile Software Portfolio Architecture: The Impact of Coupling on Performance." Academy of Management Annual Meeting Proceedings (2017). (doi:10.5465/AMBPP.2017.297, ISSN 2151-6561.) View Details

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Employing software metrics, such as size and complexity, for predicting defects has been given a lot of attention over the years and proven very useful. However, the few studies looking at software architecture and vulnerabilities are limited in scope and findings. We explore the relationship between software vulnerabilities and component metrics (like code churn and cyclomatic complexity), as well as architecture coupling metrics (direct, indirect, and cyclic coupling). Our case is based on the Google Chromium project, an open source project that has not been studied for this topic yet. Our findings show a strong relationship between vulnerabilities and both component level metrics and architecture coupling metrics. 68% of the files associated with a vulnerability are cyclically coupled, compared to 43% of the non-vulnerable files. Our best regression model is a combination of low commenting, high code churn, high direct fan-out within the main cyclic group, and high direct fan-in outside of the main cyclic group.

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D-Wave Systems: Building a Quantum Computer

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