在系统开发中，人们总是希望寻求创新的解决方案，但事实上，即便投入大量人力物力，最终结果仍然不尽如人意。本文总结了一些在系统开发方面成绩突出的组织机构的关键成功因素，这些因素可能是技术、管理、人才、文化。

Critical Success Factors for Rapid, Innovative Solutions

Jo Ann Lane1, Barry Boehm1, Mark Bolas1, Azad Madni1, and Richard Turner2

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1 University of Southern California

Los Angeles, California, USA

{jolane,boehm,azad.madni}@usc.edu

bolas@ict.usc.edu

2 Stevens Institute of Technology

Hoboken, New Jersey, USA

rturner@stevens.edu

Abstract. Many of today’s problems are in search of new, innovative solutions.

However, the development of new and innovative solutions has been elusive to

many, resulting in considerable effort and dollars and no solution or a mediocre

solution late to the marketplace or customer. This paper describes the results of

research conducted to identify the critical success factors employed by several

successful, high-performance organizations in the development of innovative

systems. These critical success factors span technical, managerial, people, and

cultural aspects of the innovative environment.

Keywords: critical success factors, innovation, systems engineering.

1 Introduction

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Early Identification of SE-Related Program Risks

Barry Boehm, Dan Ingold, University of Southern California

Kathleen Dangle, Fraunhofer-Maryland

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Rich Turner, Stevens Institute of Technology

Paul Componation, University of Alabama-Huntsville

Abstract

This paper summarizes the results of a DoD Systems Engineering Research Center (SERC) project to

synthesize analyses of DoD SE effectiveness risk sources into a lean framework and toolset for early

identification of SE-related program risks. It includes concepts of operation which enable project

sponsors and performers to agree on the nature and use of more effective evidence-based reviews.

These enable early detection of missing SE capabilities or personnel competencies with respect to a

framework of Goals, Critical Success Factors (CSFs), and Questions determined from leading DoD

early-SE CSF analyses. The SE Effectiveness Measurement (EM) tools enable risk-based prioritization

of corrective actions, as shortfalls in evidence for each question are early uncertainties, which when

combined with the relative system impact of a negative answer to the question, translates into the degree

of risk that needs to be managed to avoid system overruns and incomplete deliveries.

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