What is project data analytics?
Definition
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
Definition from APM Pathfinder Report Project Data Analytics: the state of the art and science
Developing Project Data Analytics Skills
Data analytics and Artificial Intelligence in projects is sometimes described as ‘having another stakeholder in the room’. It can speed up simple tasks and offer new insights and perspectives to help with decision making.
Our latest guide, ‘Developing Project Data Analytics Skills,’ provides a practical outline of the skills and capabilities project professionals and organisations need today to get the most from emerging analytics and AI technologies whilst improving project success. It also offers a framework which will help organisations understand where they are in their journey and the steps needed to develop organisational capability and maturity.
Whether you’re a leader, project professional or data specialist working in a project environment, the ability to understand and apply data will be an integral part of a project professional’s skill set.
How we use data can change the way we deliver projects.
Data and technology can both help us manage our projects better – they support our decision making and enable project success. In fact, data and technology are a vital condition for project success; over 70 per cent of project professionals consider them important in the Dynamic Conditions of Project Success research. Find out more about the conditions that enhance project outcomes here.
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.
Machine learning
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.
Big data
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 current use of project data analytics
The diagram below produced by researchers from the Universities of Manchester, Sheffield, Southampton and Warwick explores this further.
Source: APM Pathfinder Report Project Data Analytics: the state of the art and science
Watch: Data analysis and storytelling for project success
Getting started in data
This guide aims to explain how data analytics can help projects and what you can do to get started.
‘Getting started in data’ is great for project professionals at all levels who wish to use project data to enable effective decisions on project initiation, delivery, and efficient automation of project tasks. It will also help you to use project data analytics to identify opportunities for improvement on a specific project or across your organisation.
As the Project Management community strive to obtain predictable project performance and better outcomes, project data can help professionals to gauge the likelihood of projects being a success.
Our ‘Getting started in data’ will help you to understand:
- What project data analytics is
- The technology and practices being used
- How to maximise potential and avoid pitfalls
- How to develop a project data strategy
This is part of a wider leading collaboration between the Data Advisory Group that we have convened with the PDA Taskforce including the Major Projects Association (MPA).
Research reports
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.
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.
Related reading
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. Project data analytics also featured as one of the Dynamic Conditions for Project Success, launched at our Power of Projects Conference.
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 or to get involved please view our current research opportunities.
- 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.
Useful links
We are keen to grow and develop awareness and understanding of project data analytics so please make us aware of any others you come across but other sites you may find useful include:
APM Body of Knowledge 7th edition
The APM Body of Knowledge 7th edition is a foundational resource providing the concepts, functions and activities that make up professional project management. It reflects the developing profession, recognising project-based working at all levels, and across all sectors for influencers, decision makers, project professionals and their teams.
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