How many people should I use on my development team?
- The size of code to be developed and reused
- The application complexity
- The degree to which schedule or cost is the overriding schedule constraint
The average Productivity Index (a measure that uses size, schedule and development effort in it's calculation) was calculated for each of the 5 data sets. The Productivity Index for the 1.5-3, 35 and 5-7 person data sets were very similar and had the highest level of efficiency. The "smaller teams" were 2 or more Productivity Indices higher than the "larger teams". The 5-7 person data set had approximately 9% less variation than the 3-5 person projects and 12% less variation compared to the 1.5 - 3 person projects. The variation is displayed using the high-low bars which represent one standard deviation from the average.
The schedule data shows that there is a decreasing trend in schedule performance as the team sizes get larger until the team size reach 9-11 people where the average time starts to increase. The schedule performance data show the 5-7 person data set as having the best performance, however the 3-5 person data set is a very close second.
The development effort statistics show that larger teams translate into more effort and cost. The trend appears to have a exponential behavior. The most cost effective strategy is the smallest team, however the extreme nonlinear effort increase doesn’t seem to kick in until the team size approaches 9 or more people.
The goal of our research was to find optimum team size for building medium-sized information systems. We conclude that a 3-7 person team has the best performance (3-5 would be the best, but 5-7 people is a very close second). Some possible reasons for this behavior are:
- This team size provides some protection against the loss of a key person.
- Individual performance is not overcome by group dynamics.
- Team size is probably close to optimum in building motivation and cohesion.
- There is minimum human communication complexity among team members.
- It doesn’t require significant management overhead.
Next time you are planning a project think hard about the optimum staffing levels because it can clearly have a significant impact on the overall results. This study gives you some insights into an application and size domain where many systems are being built today. Coupled with good peopleware practices you should be able to make a real impact on your organization’s bottom line performance.