A Case Study on Utilizing Predictive Analytics in CPM Applications
Program: Data Science Master's
Location: Not Specified (onsite)
Student: Christopher Bielinski
My capstone project is a case study on utilizing predictive analytics in financial budgeting & forecasting processes in corporate performance management applications systems (corporate performance management – CPM, is also referred to as business performance management – BPM or enterprise performance management – EPM). The focus of this project is to test the difficulty of utilizing predictive analytics in CPM applications by creating a predictive analytics model process.
Many organizations with CPM applications do not utilize advanced forecasting methods like predictive analytics due to:
1. The difficulty of integrating predictive analytics.
2. The perceived cost of development along with associated additional application costs.
3. A belief that predictive analytics models are not transparent.
This project tested the difficulty of creating a general-purpose predictive model process that could determine the most accurate model using low or no cost options, that would be understandable to those working in the CPM applications space. The overall objective of this case study is to attempt to determine if it is operationally efficient and cost effective for organizations to introduce predictive analytics into their CPM applications.