Research in project data analytics
Research into project data analytics is in its infancy though reviews of current practice such as that undertaken by PwC and sponsored by the International Project Management Association (IPMA) are beginning to appear. Established annual project controls surveys undertaken by Logikal are also now reflecting project data analytics in the questions that they ask. APM has sponsored the following three on-going research fund projects around project data analytics due to be published autumn 2021:
Leveraging the value of lessons learnt through the power of intelligent agents
Dr Ronald Dyer, University of Sheffield
This investigation examines the application of intelligent agents to the critical area of learning lessons across projects. It will investigate the use of ‘chatbots’ to identify and disseminate lessons learnt. (A chatbot is a software application that emulates a human by ‘chatting’ either by text or speech to guide the user through a task.) It will use this experience to reflect more widely on the use of AI in projects. Intelligent agents won’t be badged as AI but as a tool in the project manager’s arsenal.
To what extend we can blackbox project management as a profession? - can AI learn to be a professional project manager?
Dr Ian Stewart, Dr Kun Wang, University of Manchester
This investigation takes as its starting point the professional status of project managers and the tapestry of knowledge, skills and attitude that it takes to achieve professional status as a project practitioner. The investigation attempts to ‘unbox’ this knowledge to see if and how artificial intelligence could be used to replicate the functionality of this knowledge. This will allow the researchers to identify how networks of humans and intelligent agent could co-exist in a way that would improve project delivery performance.
Artificial intelligence in project management: How to leverage big data mitigation in complex projects
Dr Nicholas Dacre, University of Southampton
This investigation provides an overview of the potential for AI in projects particularly through a big data perspective. As projects grow in complexity, project professionals increasingly are exposed to large swathes of big data across the three main attributes of volume, velocity, and variety. Professionals are tasked with managing the success-to-failure pendulum by applying an array of project data analytics throughout the project life cycle.