Why not to use Data Science for advanced project management?

Data science and big data analytics projects

These days there are a lot of on-going data science related projects that are promissing and delivering great benefits for the businesses in different domains (from telco to retail and so on).

However the project management itself is mostly not benefiting from the value of the data the project generates.

Project plan execution data

During the execution of each project plan there is a constantly growing dataset of accumulated project execution day-by-day metrics (these are: current task completion percentage, actual man/hours, velocity, estimated man/hours, current resource allocation/availability, etc.)

Usually there is some more or less static WBS (work breakdown structure) that organizes the units of work identified (tasks) and their functional relationships. The relationships between the tasks and resources assigned to them are tracked also.

There is also even more static calendar data that includes the resources availability with regards to the dates.

Whatever a process methodology (Agile, RUP, etc.) is the key factual underlying metrics and work structure and calendars are the pretty much the same.

Project plan execution with data analytics

In order to support the project management activities it is possible to automatically monitor and support the execution with data analytics technics that are widely considered to be a part of the Data Science methods.

The areas of project management decision-making support can be as follows:

1. Key project metrics forecasting (with Time Series Analysis, etc.).
2. Identifying the project data patterns and correlations based on history; proactive alarming using these patterns (Linear Regression, Logistic Regression, etc.)
3. What-if analysis (Linear Regression, etc.)

I believe this list can be much longer being elaborated/structured sufficiently. So let's make "The shoemaker's son always goes barefoot" irrelevant to the software project development itself :).