Two of the most common reasons for not implementing a risk management program are cost and benefit. This paper focuses on whether the benefits of intervention can be shown to justify the costs. A confounding factor is that the acts of intervention during a risk management program may alter the outcome in ways we cannot separate and therefore cannot cost out. A second confounding factor is response bias – the tendency of individuals consistently to underestimate or overestimate risk, resulting in interventions that may be ineffective or excessively wasteful. The authors demonstrate that signal detection theory (SDT) can be used to analyze data collected during a risk management program to disambiguate the confounding effects of intervention and response bias. SDT can produce an unbiased estimate of percent correct for a risk management program. Furthermore, this unbiased estimator allows comparison of results from one program to another.

B. W. Tuckman’s model of small group development proposes that groups progress through four formative stages widely known under the mnemonic “forming, storming, norming, performing.” This article analyzes 10 small software development teams classified by age, size, managerial and technical skill, reporting and communication structure, and process performance as assessed under the capability maturity model. Software development teams differ from the experimental groups studied by Tuckman and others in that they often remain together for years to develop, maintain, and enhance a product. The data suggest the need for an extended stage model of team formation that includes analogous decay stages: denorming, de-storming, de-forming. The data support a pattern of increasing and decreasing performance that mirrors the formation and dissolution of teams.

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