You're right to want the cool PMO tech, but you're probably not ready for it...

Have you ever worked on a project where the PMO seemed more of a roadblock than a roadmap? If so, you're not alone. This week, I’ve been speaking with project professionals who are still struggling with the fundamental basics of Project Controls and PMO. While I’ve been in this profession for quite some time, it’s important to recognise that it remains a relatively young field. Many organisations are still grappling with the concepts of PMO and Project Controls, often due to past experiences where attempts to establish them didn’t work out. As a result, these crucial functions have been placed in the “too difficult” box.

There is no shortage of smart and advanced technologies in the market - tools like SymTerra, nPlan and nodes&links (to name a few) are incredibly impressive and add significant value. However, before an organisation can fully embrace digital transformation, it must first ensure that its analogue foundations are solid. No amount of advanced technology can compensate for poor fundamentals.

This brings me to an essential point: we need to focus on doing the basics extremely well. Just as the mighty All Blacks of 2015 and the current Springbok rugby teams emphasise “Brilliant Basics,” organisations must adopt the same principle when establishing and managing their PMOs.

How many organisations truly prioritise getting the basics right when setting up a PMO? How much effort is put into aligning the PMO and its objectives with the organisation’s strategic goals? Are the fundamental principles of Cost Management, Scheduling, and Risk Management deeply understood before moving on to more complex processes? It is only once these elements are firmly in place that organisations should consider implementing advanced KPIs, Earned Value Management, or even, dare I say, advanced data analytics and AI.

As a wise man, Paul Goodge , once said on a Project Chatter Podcast episode: “Garbage in, gospel out.” This sentiment rings especially true in Project Controls. If the foundational data and processes are weak, then even the most sophisticated systems and analyses will be flawed.

Just as the strongest buildings require solid foundations, so too do successful PMOs and Project Controls functions. Let’s ensure we are laying the groundwork correctly before reaching for the next big innovation.

That's the wrong baseline...

This brings me to another topic that has stumped many project teams—the baseline.

When people mention 'the baseline,' they often mean different things. Let me offer up a simple breakdown of the key types:

• Scope Baseline – The agreed-upon scope of the project, documented and approved.
• Schedule Baseline – The planned sequence of tasks and activities bundled into work packages and linked in a logical sequence.
• Resource Baseline – The planned allocation of manpower, materials, and equipment, often determined through resource levelling and smoothing.
• Cost Baseline – The estimated financial plan, including labour costs, materials, and other project-related expenses.
• Financial Year Baseline – The budgeted costs aligned with the organisation's financial reporting structure, which can differ from the project’s original cost baseline.
• Contractual Baseline – For projects using frameworks like NEC, the last accepted programme often serves as the baseline, impacting how performance is measured and managed.

I bet some of you reading this will disagree with the above, which already proves my point! Understanding these different perspectives and agreeing definitions on baselines ensures that all stakeholders are aligned and that expectations are clearly managed from the outset.

Whenever I hear someone talk about "the baseline," I ask them what they mean,

And if you do want to go digital...

If you think you've nailed analogue, we recently held our first open discussion in the Movar Discord community about AI basics, where we explored what AI is made up of at its core. We discussed how, in its simplest form, a Large Language Model (LLM) predicts the next word (or token) in a sentence by analysing vast amounts of text data and reducing errors as much as possible. This statistical approach helps AI generate human-like responses, making it a powerful tool for learning and communication. The Movar Discord community is open to all, but there are strict rules in place to ensure meaningful discussions. If you’d like to get involved or listen in, speak to Yash Desai for more information.

This discussion got me thinking about how jobs will change (and yes, they will), and how those who continuously upskill and adopt a growth mindset will remain relevant. One of the most effective ways to stay ahead is by leveraging Large Language Models (LLMs) like ChatGPT to learn about industry trends, develop new skills, and explore career insights. LLMs can be powerful learning tools when used strategically. Here are a few tips on how to use them effectively:

1. Ask Specific Questions – Rather than vague prompts, refine your questions to get the most relevant insights. For example, instead of asking “How does AI work?” try “What are the key components of a machine learning model?”
2. Use AI for Skills Development – Whether you’re improving project management methodologies or learning to code, use AI to get explanations, practical examples, and recommended resources.
3. Simulate Real-World Scenarios – Engage AI in role-play scenarios to practice problem-solving, negotiations, or stakeholder management.
4. Stay Updated with Industry Trends – Ask LLMs about the latest developments in your industry to stay ahead of the curve.
5. Enhance Critical Thinking – Use AI as a sparring partner to challenge assumptions, refine arguments, and gain fresh perspectives.

The key is to be proactive in upskilling and exploring how technology can complement your professional growth. Take, for example, a project manager who leveraged AI tools to streamline scheduling and resource allocation. By integrating AI-driven forecasting models, they reduced project delays, demonstrating how a combination of industry expertise and technology can create tangible benefits. Proactively using AI in this way ensures professionals remain competitive in an evolving job market.

The Future of Work: Presence vs. Productivity

JP Morgan recently made headlines by requiring all staff to return to the office, citing the need for greater in-person collaboration (Read more). This got me thinking - where do we draw the line between the value of physical presence and being more productive in an environment of our choosing?

A team sport requires everyone to be on the same pitch, but that pitch can be physical or digital. In a work setting, a 'digital pitch' might take the form of virtual collaboration tools, real-time project tracking systems, or shared cloud workspaces where teams coordinate seamlessly regardless of location. While some roles require a site-based presence, most knowledge-based jobs that primarily involve working on a computer could likely be done remotely. But then comes the next question - if most of your work is done on a computer, does that put you at greater risk of automation replacing your role? (If so, refer to the previous section!)

This is where adaptability, continuous learning and a growth mindset become essential. The future of work is evolving, and those who embrace continuous learning will thrive.

Mental Health in High-Risk Industries

This week, one of my LinkedIn posts that received a lot of engagement was about mental health. It featured a video of Barry Hilton , a well known South African comedian, who has opened up about his struggles with depression. It got me thinking about how many people are still suffering in silence and whether we have yet to see the full impact of COVID lockdowns on mental well-being.

If we want to make a difference, we need to create spaces where people feel they can talk without fear of judgment. A bit of laughter might just be a stepping stone to opening up about a tough topic. Mental health is not a weakness, and seeking help should never be seen as failure. If you or someone you know is struggling, please reach out - you are not alone.

Your turn!

I’d love to hear your thoughts...

• what’s the biggest mistake you’ve seen when setting up a PMO?
• How do you ensure the fundamentals are in place before adopting advanced solutions?
• And how are you leveraging AI to stay ahead?

Share your insights in the comments!

Thanks for reading.

Dale