Historical Data Analysis is a popular method of knowledge management that can be successfully used in task decomposition. The method makes it possible to decompose tasks into sub-tasks by following already existing rules that have been successfully used in previous attempts of developing task breakdowns and hierarchies. The key idea of this method is to make an attempt to understand past experience and apply it to managing current endeavors. In other words, we can re-use our existing knowledge and expertise to plan and manage our current tasks and hierarchies.
Historical data analysis is applicable only in cases when there is a portion of knowledge and experience that have been generated and used in the past. The method is best used in situations when a subject matter (e.g. decomposing a task) has the same or similar characteristics with other subject matters that have been discussed and addressed in the past.
A quick guide on how to decompose a task into sub-tasks through historical data analysis is given below:
- Check if there are past endeavors and projects dedicated to task decomposition
- Make a list of endeavors that have reached success in the past
- Review each of the endeavors and understand lessons learned
- Retrieve and understand what techniques and methods have been used for decomposing past tasks
- Figure out if past endeavors have similarities with the current decomposition project
- Run pilot test to check how the current project will operate with decomposition methods and techniques of past endeavors
- Check if the test has been successful
- Understand what didn’t work during the test; then try to develop workarounds if possible
- Test past methods and techniques once again and check whether workarounds fix the situation
- Decompose current tasks with use of past decomposition methods and techniques.