The Beyond Planning Framework

Planning and control of large-scale projects in the age of AI
Dr. Matthias Tewes | Sebastian Lemm | Stephan Ruehl | Matthias Baum | Alexander Kuntz
8月 2020 | White Paper | 英语

The Beyond Planning Framework

Planning and control of large-scale projects in the age of AI

Large projects in any industry are characterized by uncertainties. Requirements change, interfaces are added or omitted, and at the same time there is often a lack of experience in dealing with highly complex projects. While the challenges in today's dynamic environment are increasing, the methods and tools in project management have hardly changed at all. Porsche Consulting has developed the "Beyond Planning Framework", which is based on insights gained from dealing with planning and control issues in major projects. 

This white paper illustrates the paradigm shifts associated with the framework. The framework dispenses with lengthy project planning entirely and instead uses artificial intelligence to process collected data into dynamic project plans. The framework consists of three steps: initial setup, implementation and control by artificial intelligence. In addition, the publication provides concrete recommendations on how companies can benefit from the framework and how to manage large projects.

9 out of 10

megaprojects exceeded budget in the last 70 years.

50

of the world’s leading organizations invested around 12 percent of their annual revenue in R&D to drive innovation.

3 principles

offer a way to overcome challenges of large-scale projects.

Management Summary
  • Uncertainties in large-scale projects are ubiquitous and cannot be disbanded. Smart project management is key to dealing with them
  • The Beyond Planning Framework combines human domain expertise and artificial intelligence as an alternative to manual or static planning approaches
  • The Beyond Planning Framework starts by defining the overall graph structure and gathering relevant data in a bottom-up approach
  • The heavy lifting of calculation is taken over by a deep-learning engine, which ensures a valid and optimal schedule at all times
  • Real-time feedback during project execution feeds the AI engine and is key to secure target achievement and optimal project results

Read the whole white paper now

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