By 2025

a significant number of Project Management roles will disappear. Will yours be one of them?



By Martin Paver
CEO/Founder, Projecting Success Ltd

England, UK


Dr. Stephen Duffield
New South Wales, Australia



Data analytics is beginning to have a significant impact on a number of professions, but project management is a relatively late adopter. This paper outlines the potential impact on specific project management roles, ranging from supplementing current roles through to radically transforming them.   We highlight the need for project managers to acquire new advanced digital skills or face the risk of obsolescence as data scientists and analysts provide evidence-based insights tailored to the conditions of the project. 

Keywords: Project Management, Risk Management, Project Assurance, Cost & Schedule,  Project Planning,  Agile, P3M, Python, R, natural language processing, machine learning algorithms, Power BI, Benefits management


A statement from a prophet of doom or a realistic vision of the future? In this paper, we make the case that a transformational approach to project, programme and portfolio management will be required in the short to medium term or our profession will wither on the vine. We must adapt.

We have already seen that the introduction of agile method have transformed traditional project management roles and in some instances these roles have disappeared completely. As data science and analytics becomes increasingly accessible, does this pose a new threat to established project management jobs? This paper will examine how these roles are likely to develop over the coming years. Will data scientists and analysts begin to fulfil these new roles or will project managers reskill and adapt?


Project Support Officer   

Project administration roles typically provide the first step on the ladder for junior project management professionals. If these roles are significantly impacted there is potential to destabilise career progression for talented project managers unless we rethink the overall career path.

Within Table 1 we outline typical roles for a project administrator and how we envisage the potential impact of data science and analytics.

Table 1. Impact of advanced analytics on project support officer roles


Roles Potential impact of data science and analytics
Tracking and administration of contractual deliverables ·        Text analytics can be used to identify when a new deliverable is received. Topic modelling can be used to identify tags and summarise the document, prior to executing a workflow to assign reviewers.

·        Scripts can be developed to assess compliance against particular standards or contractual requirements and identify omissions.

·        Machine learning can be used to assess the quality of each section when compared against a body of training material.

Change control log ·        Potential for blockchain[1] approach to manage change end to end. Payments are automatically approved when defined conditions are met.

·        Change requests become increasingly workflowed and automated.

·        Algorithms check the change management documentation to ensure compliance, accuracy and compliance.

·        Risks with specific changes are compared against a known dataset of similar changes. Impacts statements are tempered accordingly.

·        Approvals are automatically crossed checked against centrally held levels of delegated authority.

Forecasting, budgeting, ·        Budgets and forecasts can be automatically developed from known benchmarks, amended to take account of the specific attributes of the projects. The role of the project manager will be to explain the rationale for the divergence from the benchmark and what action is being taken to improve delivery performance.

·        Cost data will be centralised. Tracking variance between forecast and outturn, enabling each project to work to a common set of (tailored) assumptions.

Development of briefs, reports and dashboards, ·        Capabilities such as PowerBI or Tableau can already autogenerate textural insights from data, adapting the insights in real time based upon applied filters.

·        Automatic text summarisation algorithms review documents and summarise the salient points. These algorithms can be tailored to focus on specific areas of concern.

·        Projects such as the A14, the UK’s largest road construction project, are moving away from powerpoint and narrative based reports to interactive business intelligence based on (near) real time data.

Meeting administration, minutes and actions. ·        Products such as Microsoft flow can be used to schedule, set up and invite attendees to a meeting, book meeting rooms. Chatbots and virtual assistants are easing the burden.

·        Voice recognition is already providing transcripts of meetings.

·        Virtual assistants can capture actions from a meeting and summarise them before the meeting closes.

·        Workflow automation can be used to track action performance and report Key Performance Indicators (KPIs) via Power BI.

·        Machine learning can be used to provide an indicator on the quality of the response to the action, identifying when intervention may be required and influencing / advising on a particular course of action.

Project history, ·        By identifying key events in the schedule, key meetings in the diary, key documents (e.g. all those sent to the project Sponsor) it is possible to automatically populate the project history.

·        By using a knowledge graph it is also possible to identify any related documents, decisions or artefacts.

·        By reviewing the cause and effect of major variance it is also possible to identify key risks, schedule decisions etc which led to the variance and use these documents to inform future decisions.

Monitoring resource utilisation, ·        Automatic review of timesheets and comparison of variance against budget.

·        Recommendations on resource allocation based upon operational priorities but tempered against evidence that illustrates the impact of working below irreducible minimums.

·        Workflows to progress chase outstanding time sheets.

·        Enhanced KPIs on areas such as open meeting actions, open risk management actions, frequency of schedule updates, schedule performance vs baseline or benchmark.

Quality reviews, ·        Python[2] can be used to identify frequency of updates of documents, the extent of updates and whether they are materially significant. Whether key policy documents have been updated. By comparing against a training data set it is also possible to characterise the quality of the narrative.

Within the insurance industry Artificial Intelligence (AI) is already reducing the administrative burden of a number of roles. AI can analyse documents to ensure they have been signed, completed and validated; linking with workflows to ensure that follow up actions are tailored to results. The impact of different campaigns can be measured and adapted in real time to improve participation, the quality of online support and autocompletion of fields. Medical insurance is moving towards automatically approving claims based upon the completeness and accuracy of the claim forms and supporting evidence, combined with comparisons against similar claims for known medical conditions.  In the legal profession McKinsey estimate 69% of time is automatable for paralegals and 23% of time is automatable for lawyers.

Project administration roles have the potential to repeat the history of the project typing pool unless they adapt.


To read entire paper, click here


How to cite this article:  Paver, M. and Duffield, S. (2018). By 2025 a significant number of Project Management roles will disappear. Will yours be one of them?, PM World Journal, Volume VII, Issue X – October; Available online at https://pmworldjournal.net/wp-content/uploads/2018/10/pmwj75-Oct2018-Paver-Duffield-significant-project-management-roles-will-disappear-by-2025.pdf


About the Authors

Martin Paver

United Kingdom



Martin Paver
, Data Scientist, Registered Project Professional, Chartered Engineer, BEng, MBA, MAPM, MIMechE, is CEO of Projecting Success Ltd. and Founder of the London Project Data Analytics meetup.

Martin is a Registered Project Professional with the APM and a Chartered Engineer with the IMechE. He is the CEO/Founder of a P3M and data science consultancy called Projecting Success who help project organisations to connect and understand their data for a more certain, evidence-driven project delivery by analysing historical and real-time data to discover insights and make recommendations with improved confidence in outcomes. He has 30 years of delivery experience spanning senior strategic roles across government and the private sector, led projects of up to $1bn, both client and supply side and he also led a PMO for a $multi-billion portfolio of ICT projects.

In late 2017 Martin established the London Project Data Analytics Meetup, the UK’s largest community that combines the cutting edges of data science and project management ranging from hosting talks, delivering hackathons through to influencing future thinking on project data science. He has also been instrumental in establishing a project data analytics work stream within the APM, helping to shine a light on the art of the possible and facilitate the development of a new cadre of professionals.

He is on a mission to leverage the benefits of advanced data science for the benefit of the project management profession, ensuring that we shape the direction of the industry and prepare us for a new future.

Martin can be contacted at [email protected]


Dr Stephen Duffield

New South Wales, Australia



Stephen Duffield
completed a PhD with the University of Southern Queensland and has a research interest in organisational knowledge and lessons learned. Stephen has 38 years’ experience with both the public sector (Royal Australian Air Force, Queensland Department of Transport and Main Roads, Queensland Health and the Civil Aviation Safety Authority) and private sector (British Aerospace, AWA and the Boeing Company) organisations with a major focus on program/project management, governance, risk and safety management.

Stephen can be contacted at [email protected]


[1] “The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.” Don & Alex Tapscott, authors Blockchain Revolution (2016)

[2] Python is a general-purpose programming language. It has a range of native libraries and 3rd-party frameworks to enable developers to perform a range of activities from scraping the content of web sites to cleaning data.