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Enhancing the efficiency and effectiveness of application development

Most large companies invest heavily in application development, and they do so for a compelling reason: their future might depend on it. Software spending in the United States jumped from 32 percent of total IT corporate investment in 1990 to almost 60 percent in 20111 as software gradually became critical for almost every company’s performance.2 Yet in our experience, few organizations have a viable means of measuring the output of their application-development projects. Instead, they rely on input-based metrics, such as the hourly cost of developers, variance to budget, or percent of delivery dates achieved. Although these metrics are useful because they indicate the level of effort that goes into application development, these metrics do not truly answer the question: how much software functionality did a team deliver in a given time period? Or, put another way, how productive was the application-development group?

Flying blind

With big money and possibly the company’s competitiveness at stake, why do many application-development organizations fly blind without a metric in place to measure productivity?

First, with every metric comes some level of overhead to calculate and track that metric. With some metrics, the overhead has proved larger than the benefits afforded by them. The second reason is that in many application-development organizations there is a lack of standardized practices for calculating metrics. For example, it is difficult to deploy output measurements if application teams are following different approaches to capturing functional and technical requirements for their projects. Finally, and perhaps most important, there is often a certain amount of resistance from application developers themselves. Highly skilled IT professionals do not necessarily enjoy being measured or held accountable to a productivity metric, especially if they feel that the metric does not equitably take into account relevant differences among development projects. As a result, many organizations believe there is no viable productivity metric that can address all of these objections.

Although all output-based metrics have their pros and cons and can be challenging to implement, we believe the best solution to this problem is to combine use cases (UCs)—a method for gathering requirements for application-development projects—with use-case points (UCPs), an output metric that captures the amount of software functionality delivered.

For most organizations, this path would involve a two-step transformation journey—first adopting UCs and then UCPs. While there might be resistance to change from business partners and, not least, application developers, we believe the journey is well worth the effort.


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