What is project data analytics?
Project data analytics, at its simplest, is the use of past and current project data to enable effective decisions on project delivery. This includes:
Descriptive analytics presenting data in the most effective format
Predictive analytics using past data to predict future performance
Artificial intelligence (AI)
This refers to the study of ‘intelligent agents,’ autonomous non-human entities that can take in information from their environment and act upon their environment in a way that enables them to succeed in their goals.
Intelligent agents need to have mastered machine learning and aspects of predictive data analytics in order to be able to do this. In a project context, some people have speculated that an intelligent agent could enhance or change the roles and status of many project professionals.
This is the name given to computer algorithms that ‘learn from doing’. In project terms, machine learning has, at its centre, algorithms that are used to spot patterns between some characteristic of projects or programmes and some aspect of project performance.
This process gets more accurate the more it is used. Machine learning is a fundamental part of predictive project data analytics.
This refers to extremely large bodies of data (or datasets). In project terms, this often refers to the historic ‘data plumes’ of legacy data that are created from the use of project control or enterprise management systems.
Project data analytics (both predictive and descriptive) uses big data.
The current use of project data analytics
When considering the current adoption of project data analytics, it is useful to distinguish between:
- Predictive and descriptive analytics
- Analytics that happen within an organisation and across organisations
In order to understand the current state of the art and science of Project Data Analytics, an investigation was undertaken that pooled the existing knowledge of researchers at Manchester, Southampton, Sheffield and Warwick and supplemented this by interviewing key stakeholder groups ( e.g. relevant APM special interest groups; Data Analytic SMEs; Conventional Project Control consultancies; PMC user organisations) Interviewees were asked two key questions:
- What are you doing with Project Data Analytics now?
- What will you be doing next?
The diagram below produced by researchers from the Universities of Manchester, Sheffield, Southampton and Warwick explores this further.
The current use of project data analytics
24 Feb - 🕑 50 mins
PODCAST - How to make better use of project data
This episode features contributors from academia and industry talking on the issue of project data analytics, what it means for project management and how it can benefit the delivery of successful projects. The data theme is an extension of ideas and discussion points from APM’s Projecting the Future campaign and more recently, APM’s Data Analytics Working Group, including the report Project Data Analytics: the state of the art and science.
Project data analytics also features as one of the Dynamic Conditions for Project Success, launched at the Power of Project Conference in June.
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 three on-going research fund projects around project data analytics with all due to be published during summer and 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.
Data Advisory Group
APM have convened a Data Advisory Group which brings together professional bodies including the APM and the Major Projects Association (MPA), the Infrastructure and Projects Authority (IPA), academics, funding providers such as UKRI and leading organisations in the field of project data and analytics for example Projecting Success and Sir Robert McAlpine amongst others.
The group aims to improve ‘data literacy’ enabling individuals and organisations to understand how they might be able to make better use of data, signposting developments and sharing learning.
Big data, machine learning, data mining, data trusts and the Internet of Things (IoT) … a common list of concepts that would be potential subjects for most thought leadership pieces ... read blog
March suggested that “next year could be a turning point for project management and AI”. ... read blog
Power of Projects
7–11 June 2021 | ONLINE
Our flagship virtual conference, hosting the launch of our new Dynamic Conditions for Project Success research report. Enjoy topics such as data, agile and sustainability.
3-4 June: Project: Hack 9
7-11 June: Power of Projects 2021
How can I get involved in this work?
- Taking part in any project data analytics research or thought leadership – we have a number of studies and activities that you can take part in which can include surveys, case studies, workshops or helping to review publications. For more information on any of our current research or to get involved please visit our research opportunities webpage
- Attend project data related events - we have developed a regular series of project data related events more on which can be found in the relevant section below
- Raising awareness of project data analytics - we are keen to enhance data literacy and awareness so please feel free to share any of the content items on this site including blogs which If you or your organisation would be interested in producing please get in touch.
- Partner initiatives – we are working with a number of partner organisations including the PDA Taskforce, Project X and many others so please take time to find out about their initiatives below or make us aware of any that you believe the profession could benefit from knowing more about.
- Get in touch – we are always keen to hear from you in terms of ideas and feedback so please feel free to contact us.