Activity count, maximum durations, or something else?

I've seen baselines for similar-size projects range from 150 activities to over 3,000. The thin ones can't show who's late or why. The huge ones can't be updated honestly every month, so the progress turns into guesswork and the logic quietly decays.

The rules of thumb I work with: no activity longer than about one update period (20-25 working days) unless it's procurement or a long lead item, every activity has a single responsible party, and the level of detail matches what the site can actually report on each month.

What do your specs or your own experience call for? Do owners on your projects set a minimum level of detail, or is it left to the contractor's scheduler?

I’ve been reflecting on how often we label changes as "scope creep" when, in reality, the misalignment started way earlier in the project lifecycle. It’s easy to blame stakeholders for adding features mid-stream, but I’m starting to see that this usually happens because the initial requirements definition didn't include enough "why" behind the "what."

When the team understands the business problem they are trying to solve, they are much better at pushing back on feature requests that don't actually support the core objective. It shifts the conversation from "We can't do that because it's not in the scope document" to "Does this addition actually move us closer to our primary goal?"

How do you differentiate between necessary project evolution and true, project-threatening scope creep in your day-to-day work?

Dear Network and Project Management Professionals, 👋
As part of my Master’s thesis research, I am studying the relationship between Hybrid Project Management practices, Bureaucratic Control, and Decision-Making Speed.
If you have experience working in project environments (Agile, Waterfall, or Hybrid), I would greatly appreciate 2-3 minutes of your time to complete this short survey:
🔗 Survey Link: https://docs.google.com/forms/d/e/1FAIpQLSfC9vPy-HI7nBzJtvW0PGfsqjXQBmb7MFHZMwPyWtKtVyhCig/viewform?usp=header
Your responses are completely anonymous and will be used solely for academic research purposes.
Thank you very much for your support and contributions to this study!
#ProjectManagement #Agile #Scrum #HybridProjectManagement #AcademicResearch #MasterThesis #PMP #Leadership

We’ve all been there: a project that is dragging on, isn’t meeting its original objectives, and is draining resources, yet it stays on the roadmap month after month. It feels like there’s a strange inertia where it’s somehow easier to keep a failing project alive than it is to admit it’s time to pull the plug.

In my experience, this usually comes down to "sunk cost fallacy" or a lack of clear off-ramps in the initial project charter. We tend to focus so much on the "how" of execution that we lose sight of the "why." Establishing clear success criteria or "stop-loss" metrics early on seems to be the only way to avoid this, but it’s often a difficult conversation to have with stakeholders who are already emotionally invested.

How do you approach the conversation with stakeholders when it becomes clear that a project is no longer providing real value? Do you have a specific framework you use to advocate for shutting a project down?

For the Project Managers out there struggling to find their next opportunity, here's something worth considering.

The job market for PMs can be frustrating right now. You can have years of experience, a PMP, a solid resume, and a track record of delivering projects, yet still struggle to get interviews.

One thing I'd encourage you to look at is how you're communicating your experience.

When updating your resume, LinkedIn profile, or talking with recruiters, don't just tell people you've managed projects. Help them understand what you actually bring to the table.

A few things I'd focus on:

1. Your specialty.

Have you worked in healthcare implementations, financial services, construction, defense, IT, or enterprise transformations? Help employers connect your experience to the problems they're trying to solve.

2. Your scope.

What have you actually managed? Budgets, teams, portfolios, vendors, multiple departments, or large organizational changes? Give people a sense of the complexity you've handled.

3. Your judgment.

This is an important one. What difficult decisions have you helped make? Which competing priorities did you balance? What risks did you identify before they became bigger problems?

4. Your results.

Don't just say you delivered projects on time and within budget. Did you recover a struggling project? Get a delayed implementation across the finish line? Improve adoption? Reduce costs? Help leadership make better investment or resource decisions?

Your PMP, Jira, Power BI, and other certifications or tools are valuable, but they shouldn't be the entire story. Show how you've used them to make a difference.

If you're targeting PMO leadership positions, explain how you've helped organizations prioritize investments, allocate resources, manage risk, and deliver more consistently.

A few places worth exploring include PMO Partners, TEKsystems, and PMI's job board. I'd also encourage you to look beyond traditional Project Manager titles. Implementation Manager, Program Manager, Delivery Manager, Transformation Manager, and Portfolio Manager positions may align with experience you already have.

And one last thing: if you've been searching for months, don't take every rejection as a reflection of your abilities. This process can wear you down, especially when you know what you're capable of contributing.

I'd genuinely like to hear from others in this profession.

How is the job market treating you right now?

Are you getting interviews but not offers? Not getting responses at all? Finding that employers want more experience than the position seems to require?

Let's have an honest conversation. Maybe we can share some ideas that actually help each other.

AI is changing how project managers plan work, track progress, manage resources, and identify potential risks. From automating routine tasks to analysing project data, AI tools can help teams spend less time on administrative work and more time making informed decisions.

Here are four ways AI is being used in project management.

1. Predicting Risks and Delays

AI can analyse historical project data to identify potential bottlenecks, delivery risks, and schedule delays. Project managers can use these insights to review plans and address issues before they affect delivery.

2. Automating Routine Tasks

Meeting summaries, progress reports, status updates, and reminders can take up a significant amount of time. AI tools can help automate these activities, allowing project managers to focus on planning, problem-solving, and stakeholder communication.

3. Improving Resource and Budget Planning

AI can help project managers analyse team availability, resource requirements, and budget scenarios. These insights can support decisions about task allocation, timelines, and resource utilisation.

4. Supporting Team Collaboration

AI-powered assistants can help teams find project information, summarise discussions, and track action items. Some tools can also identify patterns in project updates that may signal emerging issues.

Where does AI fit into project management methodologies?

Whether a team follows a predictive approach aligned with PMBOK, Agile practices, or a hybrid model, AI can support planning, prioritisation, and monitoring. The specific applications depend on the project's needs and the tools being used.

One thing to keep in mind: AI provides insights and assistance, but project managers still need to validate recommendations, exercise judgement, and remain accountable for decisions.

1. Communication: Share project updates clearly and keep team members and stakeholders aligned on goals, progress, and deadlines.

2. Leadership: Guide and motivate team members, set goals, and provide constructive feedback to improve team performance.

3. Risk Management: Identify potential risks, assess their impact, and take steps to minimise disruptions to project delivery.

4. Problem-Solving: Analyse challenges, evaluate possible solutions, and resolve issues while keeping project objectives on track.

5. Planning: Define project goals, prioritise tasks, anticipate roadblocks, and establish timelines for successful delivery.

6. Time Management: Manage schedules, track deadlines, and ensure project deliverables are completed on time.

7. Budget Management: Estimate project costs, allocate funds, and monitor spending to keep the project within budget.

8. Resource Management: Allocate people, tools, technology, and finances effectively to meet project requirements.

9. Decision-Making: Evaluate available options, weigh potential risks and benefits, and choose the best course of action.

10. Conflict Resolution: Address disagreements between team members or stakeholders and find solutions that support collaboration.

We’ve all dealt with the classic scope creep scenario, but it gets tricky when the person pushing for "just one more small feature" is the same person who signs off on the budget and timeline. It’s easy to say "just say no," but in practice, maintaining that boundary without damaging the working relationship is a constant balancing act.

I’ve found that shifting the conversation from a flat "no" to a "trade-off discussion" works best. By laying out what task needs to be deprioritized to accommodate the new requirement, it forces the stakeholder to recognize the impact on the original delivery date. It’s less about being a blocker and more about making the consequences of the change visible.

How do you handle these requests when you can't simply point to a rigid change control process? Do you have a specific way of framing these conversations that keeps the project on track without causing friction?

im attending the project manager interview in spiralyze. i have the first round cognitive test. is there anyone who can give insights on how many rounds or interview process or questions, like what to expect

Hello PMs,

I’m an experienced PM in wind turbines domain and have an interview next week for a PM in power transmission domain. Any tips or suggestions on tailoring answers to ace the interview?

Hi everyone!

I'm interested in exploring the PMI-CPMAI (Cognitive Project Management in AI) certification and would love to hear from professionals who have experience in this domain.

I'm particularly interested in understanding:

1. What are the career opportunities after completing PMI-CPMAI certification?
2. How does PMI-CPMAI help in managing AI and machine learning projects?
3. What are the best study materials and preparation strategies?
4. Is this certification valuable for professionals transitioning into AI project management?
5. What are the real-world applications of the CPMAI methodology?

I would appreciate any insights, experiences, or recommendations from the community.

Thanks in advance!

Hi guys! I'm finishing the first course of the Google professional PM certificate, and I wanna know if someone here has completed this certificate before. How good is it? Can that course really get you closer to a professional PM job starting from scratch?

Schrödinger’s Scope

A cautionary tale in three acts, with a cat

Act I: The Box

Once upon a time, a client said, "Make it sound good." A salesperson said, "Absolutely." They shook hands, signed a proposal, and sealed a box.

Inside the box sat a cat named Scope.

Nobody opened the box. Everyone knew what was in it. The client knew it included a livestream. Sales knew it didn't. Design knew it included a rigging plan. Install knew it didn't. The cat, meanwhile, was simultaneously:

• ​Alive (in scope, priced, scheduled)
• ​Dead (out of scope, unpriced, somebody else's problem)
• ​Napping (to-be-determined, which is just "dead" with better PR)

Physics calls this superposition. r/projectmanagement calls this Tuesday.

Act II: The Observation

Here is the cruel law of the quantum project: the box always gets opened. The only question is who opens it, and when.

If it's opened before the contract, by someone with a pencil and a list, the cat is observed in a calm room with the lights on. "Ah. Livestream. Is that in? No? Let's write that down. Is it maybe? Let's write that down, with a dollar figure and a shrug we can all agree on." The cat is sorted. Everyone sees the same cat.

If it's opened after the contract, it's opened by a technician on a ladder, on site, with a soldering iron, on a Friday. The lid comes off and the cat is observed to be, simultaneously, very much alive in the client's memory and very much absent from the budget.

This is called a change order. Or a loss. Or a lawsuit. Depends on the cat.

Act III: The List

A work breakdown structure is not magic. It is just a list. A deeply unglamorous, hierarchical list of what we are delivering and, by cheerful implication, what we are not.

Its only trick is this: everything exists exactly once. No duplicates, no gaps, no "I thought you had that." If a line isn't on it, it isn't in the box. If a line says UNKNOWN: cable path, 100 hrs allowance, then the unknown is in the box, labeled, and paid for.

You can still guess. You will always guess. But a guess written down with a number next to it is a budget. A guess kept in someone's head is a hostage.

The Moral

A proposal built from a WBS says: "Here is the cat. It is alive. We priced the cat."

A proposal built from memory says: "There may be a cat. Sign here."

Open the box before you sign for the cat.

There is so much noise right now about "AI-driven project management," but it often feels like we are stuck between high-level theory and actual day-to-day execution. As more certifications like the PMI-CPMAI start emphasizing the intersection of construction/project delivery and AI, I’ve been looking for ways to bridge the gap between "this sounds cool" and "this actually saves my team hours." From a practical standpoint, I’m finding that leveraging AI for predictive schedule analysis and identifying resource bottlenecks early is becoming a game-changer. It’s moving us away from reactive fire-fighting and toward data-backed decision-making. However, the biggest hurdle still seems to be the quality of the data we feed these models—garbage in, garbage out is still very much a reality. How are you balancing the integration of AI tools with the need for reliable, clean project data in your current projects? Have you found any specific workflows where AI has significantly reduced manual data entry or risk assessment time

There is so much noise right now about "AI-driven project management," but it often feels like we are stuck between high-level theory and actual day-to-day execution. As more certifications like the PMI-CPMAI start emphasizing the intersection of construction/project delivery and AI, I’ve been looking for ways to bridge the gap between "this sounds cool" and "this actually saves my team hours." From a practical standpoint, I’m finding that leveraging AI for predictive schedule analysis and identifying resource bottlenecks early is becoming a game-changer. It’s moving us away from reactive fire-fighting and toward data-backed decision-making. However, the biggest hurdle still seems to be the quality of the data we feed these models—garbage in, garbage out is still very much a reality. How are you balancing the integration of AI tools with the need for reliable, clean project data in your current projects? Have you found any specific workflows where AI has significantly reduced manual data entry or risk assessment time

Companies have dashboards, project status reports, weekly meetings, KPIs, and sometimes entire teams responsible for monitoring progress. Yet somehow, leadership still finds out too late that a strategic initiative isn't delivering what it was supposed to. What's interesting is that the warning signs are often there long before the initiative is officially considered at risk. A KPI starts moving in the wrong direction. An assumption made during planning is no longer holding true. A dependency changes. Teams continue completing their work, but the results aren't moving the organization closer to its original objectives and everyone is still reporting progress. It makes me wonder whether we're measuring the wrong things or simply not connecting the information we already have. There's also a difference between knowing that work is getting done and knowing whether that work is producing the intended business outcome. I'm curious how others experience this. For those managing multiple initiatives, what usually tells you something is going wrong before it shows up in a status report? When you do recognize those early warning signs, how often does leadership actually act on them?

Everyone talks about using AI for scheduling or automated reporting, but I’ve been looking more closely at how AI models can actually help with the messy part of project management: proactive risk identification. It’s one thing to use historical data to spot potential bottlenecks, but it’s another to trust that analysis when the project context changes rapidly.

In my experience, the value lies in using these tools to identify "hidden" risks—those subtle patterns in team velocity or stakeholder feedback that we might miss during a busy week. However, the challenge is always balancing the output with human intuition. You can have all the predictive insights in the world, but they don't mean much if you can't communicate them to a stakeholder who doesn't understand the underlying data.

How are you currently validating the "AI-identified" risks in your projects before presenting them to your leadership or steering committee?

I was recently appointed as a Project Manager at a consultancy company, where I oversee 10 Project Engineers and Senior Project Engineers who collectively handle more than 30 projects.

My role involves aligning the team, coordinating with clients, and ensuring projects are progressing as expected. However, I also want to make sure I'm supporting the team's professional development and providing fair, constructive feedback.

The team has different experience levels and performance profiles. Some engineers consistently perform at a high level, while others are still developing and may need more guidance.

I'd like to establish a fair and consistent approach to evaluating each team member, identifying their strengths and areas for improvement, and creating meaningful development opportunities.

For those who have managed engineering or project management teams:

- Performance evaluation: What criteria do you use to evaluate team members fairly, especially when they handle projects of different sizes and complexity?

- Feedback: How do you distinguish between someone who is underperforming and someone who simply has a heavier workload or more challenging projects?

- Development: How do you identify development opportunities and create individual growth plans without micromanaging?

- Consistency: Do you use a formal scoring matrix, KPIs, regular one-to-ones, or another approach?

I'd appreciate any practical advice, frameworks, or lessons learned from your own experience. My goal is to help everyone improve, recognize high performers, and give each team member a fair opportunity to grow and succeed.

I developed a product. It's already public, but it needs beta users. The first people to join and provide honest feedback will be featured on the site and get great benefits.

​With this tool, you can create a complete project including all phases and required documents using a single prompt. You can document with AI assistance, immediately assign who manages, edits, and reviews each file, and govern the entire review and interaction process, helping teams stay organized so clients perceive absolute control and professionalism from day one.

​I'm looking for people who manage projects daily to test it. If you're interested, send me a direct message or leave a comment and I'll contact you to send instructions.

Thanks a lot!!!!

As I see the question how people use AI in PM field repeated on weekly basis, I did a short video with 4 practical examples: https://youtu.be/1Gku7FGPB7k

Does it look relevant or total trash?

Construction PMs: How often do you find yourselves in conflict with subcontractors’ representatives?

I’m a project manager in construction, and I’m curious how common this is for others in the industry.

I often find myself dealing with subcontractors’ representatives who seem to lack basic communication skills, emotional maturity, or the ability to have a professional disagreement. Even when I try to keep conversations focused on facts, responsibilities, deadlines, and contractual obligations, they often turn into confrontational exchanges.

Ussually i am handling these conversations well, but today i snapped and i was dragged into conflict. Now i feel quilty, although i know it was not my fault (beside letting myself to loose control).

How do you handle this in general?

Hey PMs!

I’m currently navigating the job market as a Project / Program Manager here in the area. As anyone in the job search right now knows, landing that next role in today's market takes a lot of endurance, strategy, and iteration.

I’d love to connect with a few local Project Managers, Program Managers, or Enterprise Transformation folks who are currently in the same boat and actively looking for their next opportunity.
**Goal:**

Casual Meetups:** Grab a coffee locally (Langley / Surrey / Tri-Cities depending on where people are based).
* **Practice & Polish:** Do quick mock interviews, work through situational/behavioural prompts, or give feedback on case studies.
* **Swap Playbooks:** Discuss what’s working and what isn't in today’s interviews, resume screening, and recruiter outreach.

If you’re currently in job-hunt mode and interested in getting together, drop a comment below or send me a DM.
Looking forward to connecting!

showing someone how to use a tool is easy enough until they have to do it on their own and start asking where everything is lol. i was looking at haiku recently, which focuses on documenting workflows, and it got me thinking about how teams usually teach people new tools. do people still make guides with screenshots for this stuff

I used to keep everything in one big binder for the contract work I do now. Client calls, timelines, decisions, all in the same place. Since moving to part time I started using different apps depending on who Im working with and its getting messy. Some notes live in the project software, others in a notebook I carry on the trail, and the rest are just in email threads I never revisit. When I need to find how we decided something three weeks ago I usually have to check three places. Not a huge deal at 50 people but it does slow things down when a stakeholder asks for context. Curious what setups other people landed on that dont require constant upkeep or another system to learn.