Investigate and correct missing data, zeros (for things
like number of hours to perform a task), really large or really small numbers.
2. Look for ways to normalize data across projects. For example, use ???defects by
size??? not just ???defects.???
3. Plot the data. Use a histogram to see if you have a normal or Poisson distribution.
Use a scatter diagram to see any correlations. Use a run chart to view
any trends. Use control charts once you find data that show promise.
4. Investigate the out of control points for their root cause. It is best to get
project team members involved with this analysis, since the recorded data
are likely to be incomplete. Put corrective actions in place to address the
root causes. (This is a good place to use the approach described in the Causal
Analysis and Resolution process area.)
Establish Organizational PPBs and
PPMs from the Project Data
Calculate the current and predicted process performance and capture that in a PPB.
Be sure to establish baselines that cover the life cycle for the types of projects that
you want to quantitatively manage.
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