Managing mega programs presents unique challenges that require specialized expertise and strategic planning. These large-scale projects are characterized by their complexity, high stakes, and global implications. The successful delivery of mega programs demands a blend of technical knowledge, adaptive management, and strong leadership to mitigate risks and maximize efficiency. This workshop offers practical insights and actionable strategies for effectively managing mega programs from planning through to execution and delivery. Delegates will gain tools, techniques, and knowledge to navigate the complexities of managing such high-pressure projects.

Join NATS and TPG to explore how one of the UK’s most safety-critical organisations transformed project delivery and portfolio governance at scale. Under pressure to improve visibility, compliance, and investment decision-making, NATS replaced fragmented systems with an integrated solution built on Microsoft Project Online, Power Platform, and TPG’s ProjectPowerPack and PSLink®. This session shares how the transformation enabled greater standardisation, automated reporting, and more strategic alignment—empowering PMOs with real-time insights and repeatable processes. You’ll hear from NATS and TPG The Project Group about the journey, challenges, and outcomes—focusing on business value and supporting tools. Ideal for PMO leaders, portfolio managers, and transformation leads seeking to simplify complexity, enable better governance, and deliver measurable results across project environments.

Business Intelligence (BI) for Cost Engineering The presentation aims to show a case study of a BI process for cost engineering. The process is divided into several steps: Standardization, Categorization, Normalization, Configuration, BI Creation, and Dashboards/Reports. Standardization means that the database should be formatted or should always have the required info (columns) in the same format. The reason is that BI should be able to read data from different projects, and this is only possible if the database has the same format. Categorization (e.g., cost and schedule) aims to reflect your process (e.g. Project Control for a period). It means that the database could be composed of different sources, such as schedule (e.g., P6) and costs (e.g., SAP). Normalization aims to clean, convert, remove outliers, etc. Partial of this step could be done in BI or out of the tool. Configuration is the first step in the BI tool. In this case, it is Power BI because the case study is based on my experience, but it could be a different BI tool (e.g., Tableau). Configuration means preparing and transforming the database, such as removing columns or rows, creating new columns, deleting empty rows, etc. BI creation is the phase of creating the dashboard, and it is crucial to know the process and data that you are using. You should know what and how you show the data. This will allow you to decide what types of charts to use and what levels of information the drill-down should occur at. The outputs are the dashboards and reports. The Dashboards can be published and shared with your organization. There are several benefits to recommending Bis, such as time optimization, allowing the user to have a dynamic view to navigate through the data and get their conclusions, and questions. Finally, some applications and challenges will be exemplified and discussed. LinkedIn post shows the topic that will be presented: https://www.linkedin.com/posts/helber-cunha-macedo_bi-powerbi-costengineering-activity-7319292229271891968-uF6V?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAvzG4ABEfQJ90MThnTj9nMONcG7UCEGp5g

This Presentation focusses on how Projects Controls professionals meet ethics in their everyday work. Whether working on UK or global projects, I will explain how and where PC professionals can play their part in improving project health. At the beginning, we will explore perceptions of ethics: I will ask the audience questions about situations that may have caused angst to lay the groundwork in an interactive way. They can then relax and listen whilst I will trace the history of ethics to the present day, and then explore the intersection between contract, law and ethics. We will then explore typical projects that Proj Con professionals work on. I will use Case Studies from my 25 years’ qualified practice to illustrate 21C dilemmas and challenges which are often experienced by Project Controls professionals, show how you solve these real-time real-life problems, and give you tips and tricks to take away so that you can play your part with confidence and competence. I will draw on established international research to explore and demonstrate the practicalities for those in project controls roles and responsibilities of adopting an ‘everyday ethics’ mindset: in doing business; acquiring and using key skills; being collaborative; and recognising an organisation’s ethical compass. I will then look-ahead to the ‘new workplace’: the emerging use of AI, its interface with ethics, and the areas where project controls professionals, and the wider industry as a whole, can have positive influence and meaningful impact. Finally, I will collate the evidence for how diversity makes a workplace more ethical, healthy and happy, and ultimately successful! I will give hope and instil renewed vigour on the approach to a new year! Note to organisers: This unique presentation is added to the tally of conference presentations, webinars etc on the broad topic of Ethics and Project Management, which Sarah is giving during 2025 on a probono basis for industry, principally for global PMI Chapters and industry associations. My purpose is for ProjCon attendees to: 1. Understand the matrix in which ethics meets projects and business 2. Gain tips on managing real-life ethical dilemmas 3. Recognise the benefit of a balanced, ethical and diverse workplace 4. Feel confident in using communication, clarity and purpose for ethical collaboration 5. Feel upbeat and prepared for the emerging AI-impacted workplace

Prospective Time Impact Analysis (TIA) is a crucial tool in construction project delay management, enabling stakeholders to assess the potential impact of delay events before they occur. Despite its proactive nature, implementing TIA presents several challenges, including limited data availability, subjectivity in forecasted progress, and stakeholder resistance. The Association for the Advancement of Cost Engineering (AACE) International’s Recommended Practices, particularly RP 29R-03, provide essential guidance for improving the accuracy and credibility of prospective TIAs. Enhancements such as using contemporaneous updates, clear documentation of assumptions, logical network revisions, and consistent baseline schedules are emphasized. The proposed presentation will explore these key challenges and outlines enhancement strategies to ensure TIAs are methodologically sound, transparent, and defensible. By aligning TIA practices with AACE guidelines, project teams can improve delay analysis reliability, reduce disputes, and foster better decision-making throughout the project lifecycle.

This presentation explores how integrating Visual Planning techniques with Earned Value Management (EVM) creates a powerful framework for construction project control. While Visual Planning enhances collaboration through accessible representation of project information, and EVM provides quantitative performance metrics, their combination addresses persistent industry challenges including schedule delays and cost overruns. We'll examine how this integrated approach—Visual Earned Value Management (VEVM)—transforms project delivery through enhanced accessibility of performance data, improved contextual understanding, faster issue identification, and more effective stakeholder communication. Case studies demonstrate significant improvements in schedule adherence, reduced cost overruns, and higher stakeholder satisfaction. Attendees will learn practical implementation strategies for this integrated methodology that balances analytical rigor with visual communication to drive superior construction project outcomes.

In today's rapidly evolving world, data has become a crucial asset for organisations across industries. However, managing vast amounts of data and turning it into actionable insights remains a significant challenge for projects and their project control teams. This is particularly true in the context of large infrastructure project organisations, where data can be scattered across various sources and systems. This presentation shares our journey from traditional reporting methods to implementing a data-first strategy that transformed the way we manage and analyse project data in Network Rail's Wales & Western Region. Our organisation manages over 2,700 miles of railway in Wales, Thames Valley, West of England, and the South-West Peninsula, with a £2.5 billion infrastructure renewal and enhancement program over a 5-year period. As part of the Advanced Analytics team, we led on modernising the reporting & analytics approach, developing systems, dashboards, and visualisations to enable project teams to access their project data centrally, review trends, and gain valuable insights into performance. In this presentation, we will share real-world case studies addressing specific problem statements and reveal how simple but effective technological solutions have transformed our organisation, including: 1. **Periodic Business Review Pack** A set of consistent self-service reports for the region, saving over 12,000 annual hours through streamlined access to project data. These reports eliminate the need for manual Excel generation and provide a standardised approach to performance reporting across projects and regions. 2. **Commentary Collector App** Communication and sharing of progress updates between teams was often cumbersome due to manual liaison and version control issues. We addressed this by implementing an commentary collection method, which eliminated these issues and saved over 4,800 hours annually. 3. **Change Control Database** Managing change papers manually was a time-consuming process for our project teams. We addressed this challenge by creating a consolidated database for all change papers, which significantly reduced manual effort and saved over 9,700 hours annually. This centralised solution improved the tracking and management of change requests across projects and ensures greater transparency and efficiency. 4. **Phase Readiness App** Ensuring that projects are ready for the next phase is crucial in maintaining project momentum. This app enables teams to review project readiness efficiently and effectively, allowing them to address potential issues proactively and save time. 5. **Data Mesh** To support this transformation, we adopted a back-end data mesh approach. This approach ensures that data is consistent and accessible across the organisation while allowing for flexibility and scalability. By democratising data access and enabling self-service analytics, teams can now focus on addressing project issues rather than dealing with errors or inconsistencies. Join us as we discuss these case studies in detail, sharing practical knowledge that can be directly applied to your own projects. Through this educational experience, you'll gain valuable insights into the benefits of a data-first strategy and leave with actionable takeaways that you can implement in your organisation.

I love presenting to other project professionals and would love the opportunity to do so at PC Expo. My dissertation topic for my MSc Strategic Management of Projects was based on my hypothesis that lessons learned, while ubiquitous, is never very effective in megaprojects and that people rarely act differently based on the learnings of others from previous projects. I have been asked back to UCL to present my findings to other masters candidates as it engages classrooms and drives conversation. I present on research I conducted on the variable definition of megaprojects, before discussing the concept of knowledge management and its nuances (including effective knowledge transfer through storytelling). Then, my research turns to the availability of knowledge and the varied availability of lessons, before exploring the mind of senior leaders and their likelihood (or not) of actually wanting to seek advice in the first place. I finish with a thought on heuristics and the value of instinct which poses a counter argument to Lessons Learned. Next the discussion turns to my findings gathered from interviews with senior leaders in megaprojects in the UK Finally I explore recommendations and thoughts on how to change for the better.

The project control industry, encompassing scheduling, cost estimation, risk analysis, and progress tracking, relies heavily on processing vast amounts of unstructured text data (e.g., contracts, reports, emails, and change orders). Transformer-based models like BERT, RoBERTa, GPT, and their variants offer powerful NLP capabilities to automate and enhance these tasks through fine-tuning. This session explores how pre-trained transformers can be adapted for project control applications, such as: 1. Contract Clause Extraction (identifying critical terms using NER) 2. Risk Prediction (classifying risks from project reports) 3. Schedule Delay Analysis (sentiment/context analysis in delay logs) 4. Automated Document Summarization (condensing lengthy reports) I will demonstrate practical steps for fine-tuning, including dataset preparation, task-specific architecture adjustments, and overcoming domain-specific challenges like limited labeled data. Finally, I will present a case study showing the capabilities and future directions.

Many challenges in construction project management and project controls can be attributed to our inability to ingest massive documentation generated by various teams involved, and use of non-standard systems and tools. For instance, updating schedules monthly does not allow Project Managers (PMs) to manage issues and blockers actively and timely, resulting in recognition of delays after they have impacted a project. The current state of Artificial Intelligence (AI) technologies can be used to ingest complex construction documentation to make project management simpler and connected. Large Language Models (LLM) have the capability to ingest and extract relevant information from domain-specific documents, and then respond in natural language. However, LLMs have limitations like limited memory/context, which makes their use for real-world applications challenging. There is a need for experts in the project controls industry and AI to work together so that we can target specific problems that LLMs can handle efficiently, bypassing their limitations while being practically useful for the field. We will present and describe how combining the expertise of the speakers led to the development of a solution for construction project management and constrols that can easily fit into existing workflows in the industry while improving the efficiency of project delivery and decision-making. A recent report by McKinsey Global Institute highlighted that nine out of ten infrastructure megaprojects face cost overruns in excess of 70% of the original budget. Many of these cost overruns can be attributed to delayed handling of issues and blockers, lack of advanced planning to handle risks, and lack of experts and knowledge to execute stricter contracts. We will show a demo of how AI can help automate the key problem of integrating time, cost and scope in construction project management to enable teams to understand the impact of issues and blockers timely and take necessary steps before this impact becomes a reality. The solution will ingest various sources of documentation in construction projects produced by different teams, build connections between them, process them to automate specific tasks and allow users to refer to task-specific documents when needed. The solution will highlight the possibilities and limitations of current AI technologies, including LLMs, thereby inspiring the next generation of innovators to use these technologies effectively for addressing challenges in their construction projects. Our approach to tackling this issue demonstrates how AI can improve the efficiency of construction projects. This demonstration is founded on the combined three decades of experience of the speakers in construction project management, controls, and AI-driven problem-solving for real-world challenges. Our talk will be a combination of a presentation with a demo of how AI can automate a specific problem that affects all construction projects. We will cover facts and figures that justify our approach and identify areas for improvement.

Construction projects are complex systems where disruptions can trigger cycles of rework, productivity loss, and cascading delays. These challenges often lead to cost overruns, schedule setbacks and disputes, issues that derail even the most carefully managed projects. This presentation explores strategies for proactively identifying risks, mitigating disruptions, and enhancing project outcomes.

The management of construction subcontracts differs significantly between the United Kingdom and the rest of the world, influencing cost predictability, risk allocation, and overall project control. Internationally, unit price contracts establish a structured approach where the Main Contractor assumes responsibility for engineering and quantity definition, while subcontractors commit to pre-agreed unit rates. This model enhances cost certainty for the Client, as construction expenses are largely predefined. Conversely, in the UK, NEC4 adopts a cost reimbursable framework that prioritizes flexibility but shifts financial uncertainty onto the Client. Construction Subcontractors are compensated based on predefined hourly rates rather than unit prices, shielding them from productivity risks. While this approach fosters collaboration and adaptability, it also increases the likelihood of cost overruns, making budget control more challenging. To address this, NEC4 incorporates a target price using a Pain/Gain Sharing Mechanisms: productivity gains generate shared savings (bonus), whereas overruns trigger a malus, distributed according to predetermined risk-sharing percentages. The accuracy of construction cost estimates is intrinsically linked to the maturity of engineering, as classified by AACEI standards. Estimates evolve from Class 5 (Order of Magnitude Estimate) , based on minimal engineering input (Conceptual) , to the Class 1 , requiring a highly detailed design. The progressive refinement of the Material Take-Off (MTO) throughout project phases (pre-FEED, FEED, and definitive engineering) plays a crucial role in reducing uncertainty and guiding contract selection. Through a comparative analysis of these contracting models, this presentation will explore their financial and operational implications, offering insights into optimizing subcontracting strategies based on project maturity and the client’s risk tolerance.