I had the pleasure of delivering a talk to the Association for Project Management NW network on 13 November on Next Gen Project Delivery - Disrupting the Status Quo. The opportunities presented by advanced data analytics and AI are vast and truly transformative. The project delivery profession will look very different very soon. The pace of this change is no longer constrained by the tools and technology, there is an abundance of choice. It is constrained only by organisational ambition, vision, people with the skills to make it happen and sheer determination.

I was delighted to share the stage with the brilliant Kathryn Jones from United Utilities who shared the vision for the Project Data Analytics Coalition. Working together and pooling resources to really move the dial on project delivery through the power of advanced data analytics and AI.  

Free - The ChPP wizard to help people to prepare for the APM’s ChPP application process. Levelling the playing field for those who may not have access to the sort of coaching available within larger organisations. I haven’t updated it in a while so please let me know where you’d like it improved. 

Free - My book on Next Gen PMOs, moving PMOs towards being the Centre for insights.

Free- My book on Next Gen Risk Management, removing the mundane elements of risk management and moving towards variance analytics

Free (subject to government rules) – Training on how to supercharge your career and unlock the opportunities in Next Gen project delivery.

Discounted – A senior leaders course that I deliver with Andy Murray, Exec Director of Major Projects Association and lead author of PRINCE 2, on the opportunities that advanced data analytics and AI present for project delivery

Free – Follow us on LinkedIn and my personal account

Free – Our YouTube Channel with hack pitch videos and educational webinars.

Free – PDA Task Force website

Martin Paver is CEO and Founder of Projecting Success. He is an internationally recognised expert and thought leader in advanced project data analytics. He secured a DataIQ award for most influential people in data for 2 consecutive years. He founded the Projects Data and Analytics Community with >10000 members with the objective of cross fertilising skills in P3M and data science, transforming project delivery. He was instrumental in founding the Project Data Analytics Task Force in 2020 and the Coalition in 2024. He has written books on Next Gen Risk Management, Next Gen PMO and a soon to be published book on Next Gen Assurance. He is co-author of the PRINCE2 v7 AI Practice Guide. He is also a highly experienced and qualified professional Portfolio, Programme, Project Director/Chartered Project Professional, Strategist and change management consultant with >30 years’ experience across government and the private sector within senior strategic and transformational leadership positions. He is challenging the status quo, driving advanced data analytics to reshape an entire profession.  Plus, he loves it!

One-Day Course 9am-5pm: Tailored for Senior Leaders

Next Dates:

26 February, 2025

21 May, 2025

1 October, 2025

Location: Victory Services Club, London

Cost: The course costs £595 per delegate

There is a further 25% discount if you have a delegate on our PDA apprenticeship.

Food and Refreshments: Provided Throughout the Day
Taught by Industry Experts: Gain Insights from Leading Professionals

A one-day no-waffle tour of the world of AI and data analytics, to demystify what it is, how it can be applied to projects to transform project performance, and the critical actions senior leaders must take to make it happen.

Who this course is for

“In any given moment, we have two options: to step forward into growth or step back into safety” Abraham Maslow

Senior leaders have been telling us they are swamped with offers of help to improve their project performance through using the new oil of business (data and AI). They also tell us they find the jargon baffling and that it is different to the language of projects, it can sound far too like science fiction, the solutions being pitched may involve buying expensive licenses for yet another project management tool or add-on, there is a worry that it requires investment in supercomputers or there is rightly a cautiousness regarding data and cyber security. Senior leaders tell us they fear missing out, of not taking the opportunity to use the power of AI and data analytics to tackle the stubborn issues affecting project performance. But as luring as OpenAI’s ChatGPT and other Generative AI platforms are, they are equally concerned about reputational risk or unintended consequences of using it. It’s right dilemma.

If that sounds like you, then this is the course that will help you cut through the hype to gain clarity about what’s possible right now, what will very soon be upon us and what you can do. This course is specifically designed for senior leaders with the following remits:

· Head of PMO or Head of Centre of Excellence

· Head of projects or Head of Profession

· Head of associated functions, e.g. assurance, risk

· Portfolio director/manager or project/programme director of a major project

Join like-minded people who have the same curiosity and desire to be at the forefront of transforming the profession.

What you will learn

You will learn how to tackle some of the following key challenges:

· How to differentiate the hype from reality. What is project data analytics and AI, with examples?

· What does this mean for the project delivery function and future roles? How should teams prepare?

· What is the state of the market?

· Who owns the data, rights of access, how do we contract for it?

· How do we drive up data quality? How can we trust it?

· How do we get the massive data sets that we need to train the AI models? Can we do it with just our own data or do we need to pool data and if so, how?

· How do we develop a strategy, roadmap and implementation plan? How do we take people with us when it could mean a fundamental change to their job or role?

What you will get

The course is limited to 20 attendees as it is delivered in a participative hands-on workshop format. You will be provided with a workbook that will help with your sense-making of the possibilities of AI and Data Analytics, the readiness of your organisations to use it and the steps you can take to fully exploit it. You will leave with an outline action plan specifically for your context, whether that is applying it to your project, to your function or your enterprise as a whole.

Agenda

The one-day course starts at 09:00 and finishes at 16:45 followed by networking.

· Module 1 – Objectives and introductions

· Module 2 - Demystifying AI and data analytics

· Module 3 - Opportunities to transform project delivery

· Module 4 - It’s all about the data

· Module 5 – What about tools/systems

· Module 6 – AI and data literacy/skills

· Module 7 – Making it reality

· Module 8 – Summary & Networking

Hosts

The Senior Leaders AI Playbook course is hosted by Andy Murray, the executive director of the Major Projects Association and renowned author of the IPA’s project routemap, P3M3 maturity model and PRINCE2 (among others). Andy is joined by co-host Martin Paver, CEO of Projecting Success, the founder of the Project Data Analytics Task Force and often cited as one of the leading figures in driving the adoption of AI and data analytics by the project profession.

Each course includes a different guest expert speaker who will showcase an example of AI/Data Analytics being applied and their experience with it.

As the course is delivered in ‘workshop’ style we encourage all participants to contribute - you will connect others on a similar journey and have the opportunity to continue to work collegiately to exploit AI and data analytics. We can go faster together than alone.

Join us!

In the world of project management, risk management is a critical function that often involves time-consuming and repetitive tasks. However, with the advent of advanced technologies like machine learning and automated workflows, it's possible to streamline these processes, allowing project managers to focus on more strategic activities. Below are several ways to automate the mundane aspects of project risk management, transforming it from a tedious chore into a more efficient and insightful practice.

1. Suggesting Risks Using Risk Libraries and Machine Learning

 One of the first steps in risk management is identifying potential risks. Traditionally, this has relied on the experience and intuition of project managers and their teams. However, by integrating risk libraries—repositories of common risks associated with similar projects—into your project management software, you can automate the suggestion of potential risks. Machine learning models can take this a step further by analysing past projects and suggesting potential sources of variance that may not be immediately obvious. These models can scan through historical data, identifying patterns and anomalies that could indicate emerging risks, providing a proactive approach to risk management.

2. Automating Risk Updates with Workflows

Another mundane but essential task in risk management is ensuring that risks and their associated management actions are regularly updated. This often involves chasing down team members for updates, a task that can be automated using workflows. Automated workflows can be set up to send reminders and requests for updates at specified intervals, ensuring that risk information remains current without the need for constant human intervention. This not only saves time but also improves the accuracy and timeliness of the risk data.

3. Developing Automated Dashboards on Risk Status

Keeping stakeholders informed about the status of project risks is crucial, but manually compiling and updating reports can be laborious. By automating the development of dashboards, you can provide real-time insights into the status of risks, including which risks are most pressing, what mitigation actions are being taken, and where the project stands in relation to its risk tolerance thresholds. These dashboards can be tailored to different audiences, ensuring that everyone from the project team to executive stakeholders has the information they need, when they need it.

4. Analysing Who is Effective at Risk Management

One of the more advanced applications of automation in risk management is using data analytics to assess who within the team is particularly effective at managing risks. By analysing historical data, you can identify patterns that show which individuals or teams are most successful at identifying risks early and mitigating them effectively. This can inform future team compositions, training needs, and even recognition programmes, helping to build a culture of proactive risk management.

5. Monitoring Engagement and Effectiveness in Risk Processes

Finally, automating the analysis of engagement in the risk management process can provide valuable insights into how effectively your team is managing risks. Dashboards can be developed to track who is engaging with the risk management process, how often updates are made, and the outcomes of those updates. This data can be used to refine processes, identify areas where additional support or training may be needed, and ensure that the risk management process is as effective as

Pushing the Boundaries of Automation in Risk Management

These examples represent just the basics of what can be achieved by automating parts of the risk management process. As technology continues to advance, the potential for further automation—and the insights it can provide—only grows. Imagine a system that not only suggests risks but also predicts them with high accuracy, develops mitigation strategies, and automatically adjusts project plans to account for emerging risks in real-time. The future of risk management is one where data-driven insights take centre stage, enabling more informed, proactive decision-making and ultimately leading to more successful project outcomes.

By embracing these automated solutions, organisations can significantly refine their current approaches to risk management, making the process not only more efficient but also more effective. The future of risk management lies in leveraging technology to handle the mundane, allowing human expertise to focus on strategic decision-making and innovation.

In today’s dynamic business environment, effective risk management is crucial. Leveraging advanced data analytics and AI can significantly improve your ability to identify, assess, and mitigate risks. Here are five practical tips to elevate your risk management strategy:

1. Automate Workflows for Risk Status and Management Actions

Implement AI-driven workflows to streamline the updating of risk statuses and management actions. This automated process ensures that risk information is current and that management actions are tracked and adjusted as needed. Furthermore, use these workflows to create dynamic dashboards that not only provide a real-time view of risks but also highlight who within your organisation is proactively engaging with these risks. This visibility encourages accountability and ensures that risks are being actively managed by the right people.

2. Leverage Libraries of Common Risks with AI Assistance

Establish and maintain libraries of known or commonly occurring risks, drawing on historical data, industry benchmarks, and relevant reports like NAO (National Audit Office) findings. Enhance these libraries by creating a Large Language Model (LLM) to assist users in identifying potential areas of risk. This model can prompt risk managers on what to consider, offering tailored suggestions based on the specific context of their projects or operations. Where possible, train the LLM on lessons learned reports, NAO reports, or utilise a community-driven model like Marvin. This AI-powered guidance ensures a more comprehensive risk identification process.

3. Maintain a Repository of Mitigation Methods

Develop a repository of effective mitigation strategies tailored to specific risks. By cataloguing these methods, your organisation can quickly deploy proven responses to new threats. Advanced analytics can be used to continuously evaluate the effectiveness of these mitigation strategies, allowing for refinement and adaptation over time. This repository becomes a critical tool in ensuring that risk responses are both timely and effective, reducing the likelihood of repeat issues.

4. Utilise Predictive Analytics for Risk Forecasting

Leverage predictive analytics to anticipate potential risks before they occur. By analysing historical data, predictive models can identify trends and forecast threats, providing valuable foresight. This allows your organisation to take pre-emptive actions, reducing the likelihood and impact of unexpected disruptions. Predictive analytics ensures that your risk management is forward-looking, rather than just reactive.

5. Implement Real-Time Monitoring

Adopt AI-powered tools for real-time risk monitoring across all operations. These tools can provide instant alerts to emerging risks, allowing for immediate responses. Additionally, real-time monitoring should extend to tracking regulatory changes, cybersecurity threats, and operational anomalies. By staying informed in real time, your organisation can mitigate risks before they escalate, ensuring continuous protection against potential threats.

Conclusion

Integrating advanced data analytics and AI into your risk management processes can dramatically improve your organisation's ability to identify, assess, and mitigate risks. By automating workflows, leveraging AI-driven libraries and models, and utilising predictive and real-time monitoring, you can ensure that risks are managed proactively and effectively. Embrace these technologies to safeguard your organisation against the complex and evolving risks of today’s business landscape.

In today's rapidly evolving job market, staying ahead of the curve means continuously enhancing your skills and knowledge. For those looking to specialise in advanced fields like artificial intelligence (AI), a Level 7 Apprenticeship offers a unique and valuable pathway. But what exactly is a Level 7 Apprenticeship, and why should you consider enrolling in one? Let’s dive into the details. 

Understanding the Level 7 Apprenticeship 

A Level 7 Apprenticeship is a prestigious program equivalent to studying a master’s degree. It is designed to provide a high level of training and education in a specific field, combining practical work experience with academic learning. This type of apprenticeship is particularly beneficial for those who want to gain in-depth knowledge and advanced skills without the traditional full-time study route. 

The benefits of a level 7 apprenticeship

• Real-World Experience: One of the main advantages of a Level 7 Apprenticeship is the opportunity to gain hands-on experience in your chosen field. Unlike traditional education paths that focus heavily on theoretical knowledge, apprenticeships allow you to apply what you learn directly to real-world situations. 

• Earn While You Learn: Financial constraints are a significant barrier for many when considering further education. Level 7 Apprenticeships address this by allowing you to earn a salary while you study, making it a financially viable option. 

• Career Advancement: Completing a Level 7 Apprenticeship can significantly boost your career prospects. The combination of advanced skills, practical experience, and the academic rigor of a master's degree makes you a highly attractive candidate to potential employers. 

• Industry-Relevant Skills: Apprenticeships are designed in collaboration with industry leaders, ensuring that the skills you acquire are directly relevant to the current job market. This alignment with industry needs enhances your employability and readiness to tackle job-specific challenges. 

• Networking Opportunities: Being part of a Level 7 Apprenticeship program connects you with professionals and peers in your field. These networking opportunities can open doors to new career possibilities and collaborations. 

 

comparing to traditional education paths

While traditional master’s degree programs offer valuable academic knowledge, they often lack the practical experience component that is crucial in many industries. Level 7 Apprenticeships bridge this gap by integrating academic learning with on-the-job training. This holistic approach ensures that you not only understand the theory but also know how to apply it effectively. 

why you should consider a level 7 apprenticeship

Artificial intelligence is one of the most dynamic and impactful fields today. A Level 7 AI Specialist Apprenticeship equips you with the advanced skills needed to excel in this cutting-edge area. You’ll learn from industry experts, work on real AI projects, and gain insights that can propel your career to new heights. 

By enrolling in this apprenticeship, you’re not just learning AI; you’re preparing to shape the future of technology. The practical experience, combined with the depth of knowledge provided, ensures that you are ready to meet the challenges and opportunities in the AI landscape. 

get involved

If you’re looking to advance your career and specialise in AI, consider joining our Level 7 AI Specialist Apprenticeship program. It’s a unique opportunity to earn while you learn, gain valuable industry experience, and achieve a qualification equivalent to a master’s degree. 

Stay tuned for more information, and don't miss the chance to be part of this transformative journey. For those interested, please reach out, and let’s discuss how this program can help you achieve your career goals. 

Explore the future of Risk Management with our new book. Read how to mitigate the risk of your role being reimagined. Download our free E-Book today and let's transform the future of project delivery together.

I founded Projecting Success in March 2014. My vision was always to leverage the rich experience that we capture within projects and then use it to avoid the avoidable. My first foray into this world was via the route of knowledge management.  

At the same time as founding Projecting Success, I also co-founder of another business that I exited in 2016. Within this business, we employed 2 knowledge managers. My initial observation was that we weren’t doing enough as a profession to collect, curate, connect and leverage our knowledge from projects. I was convinced that knowledge management was the way forward.  

Pioneering Initiatives in Project Delivery

Along the journey I realised that knowledge management was failing to deliver. In times of organisational stress, knowledge managers were always an easy target. I had seen countless instances where organisations had invested in knowledge management, but when the champion left, the progress stalled or went into reverse. The pendulum often swung violently.  

In parallel I wanted to understand how project based organisations were leveraging their vast databases of lessons learned and whether there was a better way of curating this knowledge. I tried to get hold of these lessons learned, but repeatedly struggled. So I resorted to the only mechanism available to me; the Freedom of Information process.  

I knew that this would create issues and I discussed the implications at length with my team and mentors. But I knew that it was the right thing to do. I collated over 20,000 lessons learned and the insights from this work shaped my thinking considerably. I concluded that the process was fundamentally broken and we were approaching it the wrong way. 

That took me deeper into the world of data. I reached out to several large organisations to share the insights we had gathered, but they simply weren’t ready for it, plus they were often stuck in the challenges of the here and now. I saw that rather than try and change the profession alone, we should do it together, so in 2017 I established the Project Data Analytics community. It has since expanded to over 10,000 members.  

The following year we joined forces with Sir Robert McAlpine, via Gareth Parkes and Grant Findlay, and Microsoft to launch Project:Hack. A community hackathon with the objective of solving problems that we have in common, inspiring thousands of people along the way. On 11-12 June 2024 we are running our 20^th event. 

In 2020 I reached out to a number of kindred spirits who shared a passion for making a difference. They agreed to join me on the mission and together we founded the Project Data Analytics Task Force. The Task Force has written a white paper, manifesto and a guide to getting started in project data. A body of work that has helped to raise the profile of project data analytics across the profession.  

In 2020 we also launched the Project Data Academy, funded by the government apprenticeship levy. It was apparent to us that if we want to move the dial on project delivery we will need a small army of people with the depth of knowledge to deliver it. The pioneers, the people with a passion for data driven projects, those who aspire to re-imagine the way we work. We have trained up hundreds of people, many of whom have carved out new and exciting careers. New roles have emerged and some of our alumni have gone on to achieve some amazing things. 

Impactful Collaborations and Partnerships

In 2021 we worked with some visionary people to found the Construction Data Trust, a world first, with a mission to pool the data from construction projects. A quest to codify, collate and curate our collective hard won project delivery experience that is codified in data. We were proud to see it featuring centre stage in the Private Sector Productivity Playbook in 2022. The Construction Data Trust, Projecting Success and other key organisations also had a significant input into the report on Measuring Construction Site Productivity. 

In 2022 we were appointed as the lead developer for the Offshore Energy Data Trust. Collaborating with 7 other organisations to securely pool data to drive down the £45 billion cost of decommissioning 4000 wells in the North Sea. Another world first, with the objective of pooling data on projects to avoid the avoidable, drive up investment certainty, optimise and drive a portfolio level approach. In parallel, we also worked with the Project Data Analytics Task Force to release a Manifesto for Data Driven Project Delivery. A seminal document that established a collaborative approach.  

Community Engagement

In 2023 we launched Marvin, a community chatbot trained on over 1000 documents, including copyrighted books. Another part of our community endeavours. We also released our ChPP wizard, helping project professionals with their applications to become a Chartered Project Professional. Not to game the system, but to level the playing field for those who may not have the level of mentoring support of the larger corporates.  

In 2024 we published our book on Next Generation PMOs, open sourcing it for the benefit of all. Mapping out how we can reimagine PMOs by taking a data driven approach. The first in a series of books we are working on to fundamentally reimagine project delivery.    

As we celebrate our first decade, we're proud to have hosted 19 hackathons, with our exciting 20th hackathon on the horizon. Additionally, through our collective efforts, we've raised £11,000 for our chosen charities, further demonstrating our commitment to making a positive impact.  

We’ve always been driven by our vision to transform project delivery by leveraging the power of data and AI. To make major projects more invest-able, improve delivery confidence and drive change across society. To enable and accelerate the energy transition, drive economic growth and make the world a better place. By joining forces, we believe we can achieve more, faster, and reach further than we ever could on our own. 

Reflecting on our first decade, it's heartwarming to recap the achievements and the ripple effects we've ignited – and the best part? We're just warming up. As we embark on the journey ahead, I want to extend a heartfelt thank you to all our staff, learners, collaborators, and partners. Your unwavering support and dedication have been instrumental in our success over the past 10 years. Here's to the incredible journey we've shared and the exciting road ahead.

Thank you for being an integral part of our story.

How do we judge how good a project professional is at their job? Is it by the way they follow process? Or as Jeff Bezos reported “I want people who are right most of the time?” How do we measure how right someone has been?

We’ve been giving a lot of thought to this recently and believe that there is a lot that we can bring to the debate through advanced data analytics.

• Estimators. How good were you at estimating something compared to your peers? What is the difference between forecast and out-turn? How do we normalise this based around project complexity or emergence?
• Risk managers. How good were you at pre-empting risk? How effectively was the risk budget invested? How many issues sprang up out of the blue?
• Stakeholder managers. How much delay was created by challenges with stakeholder management and how does this compare with other benchmarks.
• Change managers. How much of the change could have been anticipated and tackled earlier? On a scale, how proactively is change managed? What is the impact of tackling change late? Are the change managers plugged into the lead indicators and picking up change at the earliest point possible?

This is the tip of the iceberg and there is a lot we can do. But is this just another set of KPIs that no-one is interested in?

By surfacing it we can help to move away from turning the handle on process and pivot towards a more evidence driven approach.

Formula 1 works on very fine margins. Every member of the pitlane and engineering team are measured against a set of KPIs. The driver’s performance is measured against every metre of the road and compared against their peers. But in project delivery we don’t even measure what these margins are or how we can optimise them.

This situation is no longer acceptable and change is coming. Only then will we really drive transformational change.

We work with >60 different organisations and have a deep grasp of where they are struggling and where others are outperforming them. We’ve boiled it down to the following key factors:

• Vision, strategy and ambition. They have a clear understanding where they want to get to and how quickly.
• Senior commitment. They have board level support who show an interest in driving through change. Having a nod from the board is very different to having clear support.
• Governance. Senior members of the organisation are involved with driving progress, unblocking obstacles and holding people to account. They tackle the cross organisational issues that often drag transformational projects down.
• Understanding of constraints. They have a good understanding of their constraints. But they don’t get suffocated by them. They work around them, use the evidence of impact to influence others and build momentum.
• Transformation. They understand that this isn’t the job of ‘someone in the data team’. It requires a data culture that runs deep into the heart of the project delivery organisation. As such, the organisation treats it as a transformation project rather than a bolt on. The organisation has a good understanding of the various strands of activity that need to be developed in parallel.
• Iterative approach. We’ve seen some organisations who try and tackle the challenge of data in a massive programme of change. But they often get bogged down in organisational design, consultation and much more beyond. Those organisations who are pulling away are running pilots and driving change in rapid spirals rather than a big bang.
• Developing talent. They recognise that some members of their project teams will become increasingly obsolete as new methods gain traction. Rather than trying to find data talent within an overheated market they invest in developing their own people. Step 1 is to highlight the need for change and the opportunities that it presents. Step 2 is to inspire them, create a fear of missing out, show them a path. Then sign them up to the Project Data Academy.
• Open source. The organisations who are making rapid progress tend to be those who are working on open source solutions. Clients are beginning to understand the opportunities that this provides, leaving them with solutions that they can iterate and build on for collective benefit.
• Data. The more advanced organisations are also beginning to understand that the data they collect and the problems that they aspire to solve aren’t always aligned. They are beginning to get to grips with how they close these gaps.

Most interesting, there are clearly organisations out there who are working within a walled garden, developing products and services to sell or differentiate themselves from others. But our sense is that those who work collaboratively will outperform their peers. Particularly those who are agile and responsive. They’ll move more quickly together than alon