We’re excited to announce that Rolls Royce will be setting one of the flagship challenges at our upcoming hackathon on October 21-22 in Derby! This event is shaping up to be a truly unique opportunity for professionals, students, and innovators to engage with real-world problems, collaborate, and showcase their skills.
The Challenge: Project Planners’ Struggles with Schedule Summarisation
Project planners often have to juggle complex schedules and provide high-level summaries for various stakeholders. With Rolls Royce’s challenge, participants will be diving into a common but crucial issue faced by planners: how to simplify and effectively communicate detailed project schedules without losing essential information. But why is summarising schedules such a critical task?
Here are three key reasons:
Stakeholder Integration
Project planners frequently need to integrate schedules from other teams, suppliers, or delivery partners. Summarising these inputs allows them to create a cohesive timeline that keeps everyone aligned.
Communication to Senior Stakeholders
Sometimes, providing a detailed breakdown of a schedule to senior stakeholders isn’t feasible. High-level summaries are essential for presenting key information succinctly, enabling informed decision-making.
Enhanced Project Understanding
Summarised schedules serve as powerful communication tools. They help the entire team understand project priorities and timelines, facilitating smoother project delivery without overwhelming team members with too much detail.
The Importance of Accurate Schedule Summarisation
Two things matter when summarising a schedule: ensuring it accurately reflects the detailed schedules from a sequencing and timing perspective and capturing the progress or performance of the detailed plan. Rolls Royce’s challenge invites you to propose solutions that tackle these pain points, bridging the gap between high-level reporting and detailed project management.
Why Should You Take Part?
This isn’t just another hackathon—it’s your chance to work on a real problem faced by one of the world’s leading engineering companies. Participants will have the opportunity to engage directly with Rolls Royce representatives, gain insights into the complexities of project management, and possibly see their solutions adopted in practice!
Submit Your Own Challenge
If you have a challenge that would inspire others or tackle a problem in your field, why not submit it? We’re always looking to broaden our range of challenges and welcome contributions that bring new perspectives to our events.
Future Events: Mark Your Calendars!
Can’t make it to this hackathon? Don’t worry—we have more events on the horizon! We’ll be holding major events in March and June next year, with more exciting challenges to come. Keep an eye on our website for updates, and don’t miss out on the chance to be part of something impactful.
Join Us and Make a Difference
Our hackathons are about more than just solving problems—they’re about building communities, sharing knowledge, and shaping the future of technology and project management. Whether you’re a seasoned professional, a student, or simply curious, we encourage you to join us and see what you can achieve.
Sign up now and be part of an unforgettable experience!
Authored by: ran cheng
In 2022, as a third-year PhD student, I came across Project:Hack 14, an online event hosted by Projecting Success on Eventbrite. Being intermediate in Python at that time, I was looking for hackathon opportunities to enhance my coding skills beyond my PhD studies. I chose the challenge of 'topic modelling' to enhance the bid team workflow and was fortunate to win first place, receiving an Amazon voucher worth £3,000, which I used to purchase a standing desk, a 4K monitor, and a new iPad Pro with full bundles.
My Project:Hack Journey
After winning my first-ever hackathon, I attended the in-person Project Hack 15 and 17, teaming up with friends from Imperial, UCL, other universities, and project professionals we had never met before. We secured second place at Project Hack 15. Although we didn't win at Project Hack 17, we still learned a lot and enjoyed the hack challenges, learning new tech stacks by addressing the challenges and presenting the solutions.
pHD studies and beyond
After these hackathons, I gained significant experience in planning, building, and delivering data-driven projects. Most importantly, I gained confidence in tackling any hackathon challenge. By the end of 2022, I came across advertisements for Smartathon, a hackathon hosted by the Saudi Arabian government. Teaming up with three friends from Oxford and Cambridge, I successfully led them to win second place and a cash prize of £20,000 among 20,000 participants for delivering a complete end-to-end computer vision system for detecting potholes on national roads in Riyadh
After finishing my PhD study in 2023, the hackathon experience from 2022 led me to join Projecting Success as a machine learning developer, where I continue to build AI solutions for digital transformation for our clients.
upcoming hackathons
Inspired by Ran's Story? Join us for our upcoming hackathon events:
In-Person Hack: 21-22 October at Rolls Royce Derby
Hackathons are exhilarating bursts of creativity and collaboration, offering a playground for problem solvers, tech enthusiasts, and innovators. At Projecting Success, we believe in the power of these events to drive innovation and personal growth. Here are some compelling reasons why you should consider participating in our hackathons:
Skill Enhancement
Hackathons propel participants beyond their comfort zones. Whether you’re a seasoned coder or a curious beginner, you’ll acquire new skills. Projecting Success provides an environment where you can fine-tune your coding, design, and teamwork abilities. From rapid prototyping to debugging, every challenge contributes to your growth.
Networking Opportunities
Our hackathons attract a diverse crowd, like-minded individuals with whom you can collaborate, exchange ideas, and forge lasting connections. Who knows? Your next collaborator or mentor might be sitting across from you during a late-night coding sprint. We employed our very own Ran after meeting him on a hack!
Unleashing Creativity
Hackathons thrive on unconventional thinking. In our working lives, we can’t always explore using novel techniques against the status quo, but in a hackathon you’ll discover innovative solutions to complex problems. Whether it’s a novel app feature or an elegant algorithm, you’ll surprise yourself with what you create.
Real-World Problem Solving
Our hackathons often tackle real-world challenges. From sustainability to healthcare, you’ll grapple with issues that matter. The skills you acquire can be directly applied to your career or personal projects.
Prizes and Recognition
Who doesn’t love a prize? Even if you don’t clinch the top spot, the experience itself is invaluable.
Project Exposure
Your hackathon project won’t gather dust. Projecting Success showcases winning projects, and industry experts take notice of our Solutions Centre. Imagine presenting your solution to potential employers or investors and being able to explain its real-world effects. It’s a chance to shine and demonstrate your capabilities.
So grab your laptop, fuel up on caffeine, and dive into the world of innovation. Who knows? Your next breakthrough might be just a hackathon away!
Join us for our upcoming hackathon events:
Project:Hack23 Kick Off and Info Session: Join us in person to network and find out more about our in-person hackathons
Project:Hack 23 at Rolls Royce Derby: Experience the energy and excitement of hacking in person.
Artificial Intelligence (AI) and Data Science are revolutionising industries across the globe. With advancements in automation, predictive analytics, and machine learning, businesses are using AI to transform decision-making and optimise operations. But what are the key AI and Data Science trends driving innovation, and how can professionals stay ahead in this rapidly evolving field?
In this blog post, we’ll explore the top AI and Data Science trends to watch in 2024 and highlight how you can upskill through our Level 7 AI Specialist Apprenticeship, designed to prepare you for the future of work.
1. AI for Business Decision Making and Automation
AI is transforming how companies make decisions, helping businesses analyze massive amounts of data quickly and accurately. In 2024, expect to see more organisations adopting AI-powered automation to streamline processes, reduce costs, and improve productivity. AI is especially valuable in industries like finance, healthcare, and retail, where data-driven decision-making is essential for growth.
To stay competitive, professionals need to be proficient in both AI technologies and Data Science techniques to help businesses leverage AI’s full potential. Upskilling in AI ensures you’re equipped with the tools and knowledge to lead data-driven initiatives.
2. Ethical AI and Bias Mitigation
As artificial intelligence continues to shape industries, ethical concerns around AI bias and fairness are becoming more prominent. AI algorithms, if not carefully designed, can perpetuate existing biases or create new ethical issues. In response, businesses are prioritiaing ethical AI development and ensuring models are transparent and explainable.
Organisations are also adhering to new AI regulations focused on fairness and transparency. Professionals who understand how to mitigate AI bias and ensure compliance with ethical standards will be in high demand.
3. AI-Driven Automation and the Future of Work
AI automation is expected to impact almost every sector, from logistics and manufacturing to marketing and customer service. While some fear that automation will replace jobs, it’s more likely that AI will create new roles and redefine existing ones. In 2024, AI will enhance workplace productivity by handling repetitive tasks and freeing up human workers for more strategic, creative tasks.
To thrive in this evolving landscape, professionals must embrace automation and develop expertise in AI deployment. Learning how to work alongside AI-driven systems will be a crucial skill in the workforce of the future.
4. Edge Computing and AI in IoT
The growth of edge computing is another trend to watch in AI and Data Science. Edge AI brings computing and data analysis closer to the source, rather than relying on cloud-based solutions. This reduces latency and enables real-time data processing, which is critical for IoT devices, smart cities, autonomous vehicles, and healthcare applications.
As the number of connected devices continues to rise, businesses will need AI professionals who can develop and deploy edge computing solutions to handle real-time data efficiently.
5. AI for Sustainability and Climate Action
AI’s potential to address global challenges like climate change is enormous. AI is being used to optimize energy use, reduce waste, and drive sustainable business practices. AI-powered sustainability initiatives are helping industries cut carbon emissions, improve resource management, and combat climate change.
In 2024, more businesses will turn to AI to help meet their sustainability goals. Professionals who specialize in AI for sustainability will be in high demand as companies seek to balance profitability with environmental responsibility.
Upskilling in AI: Why Our Level 7 AI Specialist Apprenticeship is Critical for Your Career
With AI and Data Science evolving rapidly, staying ahead of the curve requires continuous learning and upskilling. Our Level 7 AI Specialist Apprenticeship offers the perfect opportunity to gain cutting-edge skills in AI and Data Science while working on real-world projects. This program covers everything from AI ethics to machine learning algorithms, equipping you with the expertise needed to thrive in a world increasingly driven by data and AI.
Whether you’re a professional looking to enhance your AI skills or someone wanting to transition into the field, our Level 7 apprenticeship offers a comprehensive curriculum that combines theory with practical applications.
Conclusion
The future of AI and Data Science holds immense promise, with trends like automation, ethical AI, and sustainability at the forefront of innovation. By keeping up with these emerging trends and investing in upskilling, you can ensure your career remains future-proof in this rapidly changing landscape.
To learn more about how our Level 7 AI Specialist Apprenticeship can help you stay ahead in the AI revolution, get in touch with us today.
In today’s fast-paced project management landscape, the need for clear, actionable data is more critical than ever. Project delivery dashboards are a key tool in empowering decision-makers, but are your dashboards truly driving better outcomes, or are they overwhelming your users with too much information? In this blog post, we delve into how to transform your project delivery dashboards based on insights shared by Gerard Duggan, a data analytics expert from KBR, in his recent webinar, Breaking Bad: How Project Delivery Dashboards Need to Change. By following best practices in dashboard design and data visualisation, your organisation can avoid common pitfalls and create dashboards that deliver real value.
Why Effective Dashboards Are Critical for Project Delivery
For project managers, data is everywhere. Whether it’s construction, engineering, or another complex field, stakeholders at every level of an organisation need access to the right information to make informed decisions. Yet, many dashboards fail to provide the context necessary for quick, efficient decision-making.
A typical project delivery dashboard might show progress reports, cost breakdowns, or personnel statistics, but as Gerard Duggan points out, numbers alone aren’t enough. Without the right context, how can you know if being 40% complete is good or bad? Is a project ahead of schedule or dangerously behind? Without adding insights such as planned versus actual progress, or highlighting important deviations, these numbers are meaningless.
Key Challenges in Project Delivery Dashboards
Here are some common issues that plague project dashboards:
- Information Overload: Many dashboards throw too much information at the user, making it difficult to know what’s important. Gerard recalls his early days in dashboard design, where he would cram too many metrics and visuals onto one screen, confusing rather than enlightening the user.
- Lack of Focus: Gerard explains that dashboards must stay focused on key objectives. What do decision-makers really need to know to act? If you can’t answer that question, the dashboard will likely fail.
- Poor Visualisation Choices: Choosing the wrong type of visualisation can overwhelm users. Gerard advises using simple, familiar visuals like bar charts or line graphs. Complex visuals such as chord diagrams might look impressive but are often not user-friendly.
- Failure to Communicate the Story Behind the Data: A great dashboard tells a story. It provides a logical flow of information, starting with high-level insights and drilling down into more detailed data when needed. Gerard highlights the importance of structuring dashboards so users know where to start and what action to take next.
How to Build Effective Dashboards for Project Delivery
If your dashboards are suffering from any of the challenges above, here are the steps you can take to improve them:
1. Understand Stakeholder Needs
Before you begin designing your dashboard, you need to understand your end users. What information is most critical to them? As Gerard emphasises, stakeholder engagement is key to ensuring the dashboard delivers value. This is where your soft skills come in – engage with project managers, C-suite executives, and even operational staff to understand their specific requirements.
2. Use Context to Give Meaning to Data
Numbers by themselves can be meaningless without context. A progress bar showing 40% completion means nothing unless you know whether that’s ahead of or behind schedule. Including planned versus actual progress, benchmarks, and performance against key metrics can help users understand the story the data is telling.
3. Simplify Your Design
Avoid the temptation to use flashy, complex visualisations. Gerard’s advice is simple: keep it clean. Stick to visuals that your users can understand at a glance. A simple line chart showing progress over time or a bar chart comparing planned vs. actual performance is often more effective than a multi-coloured radial chart.
4. Prototype Before You Build
Rather than spending weeks building a dashboard that might not meet your users' needs, sketch it out first. Use paper, or a quick design tool, and show it to stakeholders before committing time and resources. Gerard advocates this approach as it allows you to iterate quickly and ensure that you’re on the right track before you invest heavily in development.
What Makes a Good Project Delivery Dashboard?
The best dashboards share a few common traits:
- Clarity: Every element on the dashboard should serve a purpose. Avoid clutter and unnecessary details.
- Actionable Insights: Your dashboard should lead users to take action. If something is falling behind schedule, make it obvious so the user can act quickly.
- Contextual Data: Always provide the "why" behind the data. Are the numbers good or bad? How does performance compare to the plan?
- Customisation for Different Audiences: As Gerard explains, dashboards are not one-size-fits-all. A C-suite executive might need a high-level summary, while a project manager might need granular data. Build different dashboards for different users.
The Power of Storytelling in Dashboards
Data storytelling is more than just a buzzword; it’s a critical aspect of effective dashboard design. Gerard highlights that dashboards should guide users through the data in a logical way, starting from high-level insights and allowing them to drill down into more detailed data as needed. By using visual hierarchy, colour theory, and cognitive science principles, you can lead the user through the data journey and help them make sense of complex information without being overwhelmed.
One important aspect of storytelling is colour usage. Gerard points out that colour should have a clear purpose in your dashboard. For example, use colour sparingly to highlight key points or areas that require immediate attention, rather than applying a rainbow of colours that competes for the user's focus.
Breaking Bad: How Project Delivery Dashboards Need to Change
In today’s fast-paced project management landscape, the need for clear, actionable data is more critical than ever. Project delivery dashboards are a key tool in empowering decision-makers, but are your dashboards truly driving better outcomes, or are they overwhelming your users with too much information? In this blog post, we delve into how to transform your project delivery dashboards based on insights shared by Gerard Duggan, a data analytics expert from KBR, in his recent webinar, Breaking Bad: How Project Delivery Dashboards Need to Change. By following best practices in dashboard design and data visualisation, your organisation can avoid common pitfalls and create dashboards that deliver real value.
Why Effective Dashboards Are Critical for Project Delivery
For project managers, data is everywhere. Whether it’s construction, engineering, or another complex field, stakeholders at every level of an organisation need access to the right information to make informed decisions. Yet, many dashboards fail to provide the context necessary for quick, efficient decision-making.
A typical project delivery dashboard might show progress reports, cost breakdowns, or personnel statistics, but as Gerard Duggan points out, numbers alone aren’t enough. Without the right context, how can you know if being 40% complete is good or bad? Is a project ahead of schedule or dangerously behind? Without adding insights such as planned versus actual progress, or highlighting important deviations, these numbers are meaningless.
Key Challenges in Project Delivery Dashboard
Here are some common issues that plague project dashboards:
- Information Overload: Many dashboards throw too much information at the user, making it difficult to know what’s important. Gerard recalls his early days in dashboard design, where he would cram too many metrics and visuals onto one screen, confusing rather than enlightening the user.
- Lack of Focus: Gerard explains that dashboards must stay focused on key objectives. What do decision-makers really need to know to act? If you can’t answer that question, the dashboard will likely fail.
- Poor Visualisation Choices: Choosing the wrong type of visualisation can overwhelm users. Gerard advises using simple, familiar visuals like bar charts or line graphs. Complex visuals such as chord diagrams might look impressive but are often not user-friendly.
- Failure to Communicate the Story Behind the Data: A great dashboard tells a story. It provides a logical flow of information, starting with high-level insights and drilling down into more detailed data when needed. Gerard highlights the importance of structuring dashboards so users know where to start and what action to take next.
How to Build Effective Dashboards for Project Delivery
If your dashboards are suffering from any of the challenges above, here are the steps you can take to improve them:
1. Understand Stakeholder Needs
Before you begin designing your dashboard, you need to understand your end users. What information is most critical to them? As Gerard emphasises, stakeholder engagement is key to ensuring the dashboard delivers value. This is where your soft skills come in – engage with project managers, C-suite executives, and even operational staff to understand their specific requirements.
2. Use Context to Give Meaning to Data
Numbers by themselves can be meaningless without context. A progress bar showing 40% completion means nothing unless you know whether that’s ahead of or behind schedule. Including planned versus actual progress, benchmarks, and performance against key metrics can help users understand the story the data is telling.
3. Simplify Your Design
Avoid the temptation to use flashy, complex visualisations. Gerard’s advice is simple: keep it clean. Stick to visuals that your users can understand at a glance. A simple line chart showing progress over time or a bar chart comparing planned vs. actual performance is often more effective than a multi-coloured radial chart.
4. Prototype Before You Build
Rather than spending weeks building a dashboard that might not meet your users' needs, sketch it out first. Use paper, or a quick design tool, and show it to stakeholders before committing time and resources. Gerard advocates this approach as it allows you to iterate quickly and ensure that you’re on the right track before you invest heavily in development.
What Makes a Good Project Delivery Dashboard?
The best dashboards share a few common traits:
- Clarity: Every element on the dashboard should serve a purpose. Avoid clutter and unnecessary details.
- Actionable Insights: Your dashboard should lead users to take action. If something is falling behind schedule, make it obvious so the user can act quickly.
- Contextual Data: Always provide the "why" behind the data. Are the numbers good or bad? How does performance compare to the plan?
- Customisation for Different Audiences: As Gerard explains, dashboards are not one-size-fits-all. A C-suite executive might need a high-level summary, while a project manager might need granular data. Build different dashboards for different users.
The Power of Storytelling in Dashboards
Data storytelling is more than just a buzzword; it’s a critical aspect of effective dashboard design. Gerard highlights that dashboards should guide users through the data in a logical way, starting from high-level insights and allowing them to drill down into more detailed data as needed. By using visual hierarchy, colour theory, and cognitive science principles, you can lead the user through the data journey and help them make sense of complex information without being overwhelmed.
One important aspect of storytelling is colour usage. Gerard points out that colour should have a clear purpose in your dashboard. For example, use colour sparingly to highlight key points or areas that require immediate attention, rather than applying a rainbow of colours that competes for the user's focus.
Conclusion
Effective project delivery dashboards can make or break a project. By focusing on simplicity, stakeholder engagement, and actionable insights, you can create dashboards that not only look good but actually help your team make better decisions. As Gerard Duggan’s webinar illustrates, the key to success lies in understanding what your users need and presenting the data in a clear, focused way.
Want to learn more? Watch the full webinar Breaking Bad: How Project Delivery Dashboards Need to Change or sign up for our upcoming hackathons to get hands-on experience in dashboard design.
Today’s webinar, The Future of Risk Management, delivered valuable insights into the evolving landscape of risk management and project delivery. Led by Martin Paver (CEO, Projecting Success) and David Turnbull (Enterprise Project Controls Manager, EDF) the session focused on how risk professionals can stay ahead of the curve by embracing innovative approaches and leveraging cutting-edge tools and skills.
Embracing the Future: A No-Brainer for Risk Professionals
Martin kicked off the session by emphasizing the critical importance of future-proofing in the risk management profession. "If I was in this profession, and someone offered to future-proof me, I'd bite their hand off," he remarked, underscoring the urgency for risk professionals to boost their CVs and become pioneers in the field. The message was clear: the future is here, and it’s an opportunity for professionals to lead rather than follow.
Reimagining Project Delivery at EDF: Mindset, Skillset, and Toolset
David Turnbull from EDF shared how his organization is reimagining project delivery through a holistic approach focused on mindset, skillset, and toolset. According to Turnbull, 2023 was the "year of the toolset," where EDF concentrated on building the infrastructure necessary to harness data effectively. This included the creation of data lakes, real-time information access, and ensuring the infrastructure was in place to utilize data in innovative ways.
Looking ahead to 2024, Turnbull described it as the "year of the skillset," where EDF is focused on upskilling both seasoned professionals and those already proficient in data analytics. By combining a robust infrastructure with enhanced skills, Turnbull believes the organization can change the mindset of its employees, ultimately transforming how projects are delivered. He highlighted the importance of using data to optimize processes, drawing an analogy to using real-time traffic data to avoid congestion and choose better routes.
The Importance of Changing Mindsets
David also spoke passionately about the need for a mindset shift across the UK’s project delivery landscape. He noted that the country has struggled with delivering major construction projects on time and within scope, with many projects stalling or failing to meet their original objectives. For Turnbull, the answer lies in reimagining how projects are delivered, starting with a more strategic approach to risk management.
Upskilling and Surfing the AI Wave
Martin provided further details on the future of risk management, particularly the role of apprenticeships in building critical skills. He discussed a 15-month apprenticeship program that combines online learning, hackathons, and off-the-job hours to help professionals build a strong portfolio. Martin also emphasised the importance of upskilling to stay relevant in an increasingly AI-driven world, noting that those who embrace these changes are likely to see significant career advancements and increased earning potential.
Paver’s advice to risk professionals was clear: don’t wait. He encouraged participants to actively engage with new technologies, learn continuously, and become pathfinders in their field. "It’s a perfect time to surf the AI wave rather than get crushed by it," Martin stated, encapsulating the essence of the webinar.
Conclusion: A Call to Action
As the session drew to a close, Martin and David reiterated the importance of embracing change and leading the charge in reimagining project delivery. They invited participants to join the conversation, get involved in the coalition, and explore the training opportunities available to become part of the future of risk management.
The webinar concluded with a call to action for risk professionals to take proactive steps towards upskilling, adopting new technologies, and transforming how projects are managed in the UK. The message was clear: the future of risk management is not just about surviving change—it’s about thriving in it.
To find out more about our risk management course, contact us now at enquiries@projectingsuccess.co.uk
We're also excited to introduce Project:Womxn, a women-led initiative focused on increasing women's representation and involvement in the tech industry. As part of this initiative, we'll hear from Zoe Bello, a data tutor at Projecting Success, and Lavinia Descaluțu from PMI UK. They'll share their experiences, challenges, and successes in leading projects and pushing for greater inclusion in tech.
Whether you've been managing projects for years or you're just starting, "Project Pioneers: Embracing Data to Lead and Succeed" is your chance to hear inspiring stories, pick up practical tips, and meet others who are passionate about advancing in the world of project management. Don't miss out on the chance to learn from the best and connect with people who share your vision for a more inclusive future!
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.
I’m Christoph Kuhle, Operations Director at Projecting Success. I’m thrilled to share the key highlights from yesterday’s dynamic webinar, which I had the pleasure of leading. The session featured valuable insights from Dave Turnbull of EDF and Gareth Parkes from Sir Robert McAlpine. Together, we explored the complexities of project data analytics and discussed the collaborative efforts propelling the PDA community forward.
Key Takeaway's from the webinar
1. Overcoming Challenges in Data Analytics
I emphasised the importance of overcoming challenges in data analytics with actionable strategies. Dave Turnbull shared a real-time example from EDF. The transition from monthly to weekly data updates in Primavera, visualized through Power BI, highlighted how presenting data to senior leaders can catalyse change. For instance, a milestone dashboard unveiled discrepancies in milestone baselines, prompting a shift in behaviour and better data integrity.
Gareth Parkes focused on the significance of bridging the gap between IT and business functions. By creating a Data Governance Board, Sir Robert McAlpine is aligning priorities and fostering collaboration between data owners and system managers, ensuring a holistic approach to data management.
2. Prioritising and Implementing Solutions
Both speakers discussed methods for prioritizing and implementing data solutions in large organisations:
- Dave Turnbull: EDF's approach involves integrating data inputs from various systems into a central data lake. This centralised approach supports real-time decision-making and helps address issues like grey IT, where unofficial systems might skew data reliability.
- Gareth Parkes: Sir Robert McAlpine uses a centralized IT function and Data Management Office to address detailed problems and ensure effective collaboration across business and IT professionals.
3. Moving from Descriptive to Predictive and Prescriptive Analytics
Vivian’s question about advancing from descriptive to prescriptive analytics sparked a discussion on industry readiness. Gareth acknowledged that while the construction industry is not fully there yet, efforts are focused on improving real-time reporting and predictive insights.
Dave highlighted the role of predictive analytics in decision-making, using historical data to forecast trends and enhance project delivery. His analogy of shopping behaviors across generations illustrated the shift from intuitive decision-making to data-driven approaches.
4. Educating Senior Leaders
Christoph asked about educating senior leaders, a crucial aspect for data-driven transformation. Dave noted the challenge of shifting mindsets, especially for senior leaders accustomed to traditional decision-making methods. By presenting data in a more predictive and visual format, EDF is gradually changing perceptions and improving decision-making.
Gareth emphasised the need for continuous education and the role of apprenticeships in building data literacy. The coalition’s focus on data-driven skills and collaboration across organizations is essential for advancing the industry.
5. The Coalition’s Impact and Future Steps
The discussion wrapped up with thoughts on the coalition’s role. Gareth highlighted the importance of data sharing and pooling, as outlined in the Belfast Paper and the manifesto for data-driven projects. He stressed the need for collective problem-solving and shared solutions.
Dave underscored the coalition’s value in fostering collaboration and leveraging collective knowledge. By solving problems together, organisations can avoid reinventing the wheel and drive more effective project delivery.
next steps
Thank you to Dave Turnbull and Gareth Parkes for their invaluable insights and to all attendees for their participation.
For further information on our apprenticeship courses, reach out to us at enquiries@projectingsuccess.co.uk