Technology offers an incredible opportunity to improve project performance. This blog shares the latest research and how organizations are implementing AI into their project methodology. Come with an open mind, increase your knowledge, share your concerns, and become a project manager with new skills to offer an organization.
The critical path was used extensively in the 1960s to enhance the project methodology for the US space program. Project managers still look for that red line in MS Project to identify activities that, if one task slips, the project end date is delayed. This concept is in serious need of modernization. Using AI tools, the critical path becomes more meaningful. The red line only determines the longest sequence of tasks based on precedence factors. A new AI-based critical path incorporates additional criteria.
Are the resources applied to critical path activities adequate to complete all the tasks as scheduled? This analysis includes comparing the task requirements to the skills being applied by the allocated resources.
Have the risks on the critical path been properly evaluated and investigated? Risks are troublesome issues for a project manager. AI improves the analysis and ensures mitigation is applied to critical path activities.
Are there any constraints that will impact the critical path? The theory of constraints offers an interesting perspective on how any activity can be delayed based on bottleneck factors.
Are the precedence relationships accurate? As the project progresses, activity relationships may change. We incorporate the precedence concept to recover a schedule by crashing or fast-tracking activities. Based on data, AI reevaluates how activities are connected and the possibility of changes.
Are there activities not on the critical path that will inevitably cause a schedule delay? All of the above points apply to how the critical path might change over time.
The critical path is a fundamental and valuable concept in project management. With new technology, such as AI, it is time to rethink how the critical path is applied to projects. AI can process more data and provide faster analysis than a human project manager. AI tools assess all the factors in real-time and notify the project manager in advance of issues. This is an opportunity to update the critical path concept using new technology and increase our expectations that the red line provides more meaning to project managers.
Aaron PorterIT Project Manager| Blade HQPleasant Grove, Ut, USA
In my experience, most of project management only matters to project managers, and new tools don't necessarily change who needs what information. There are always exceptions, but the majority of the time people just want to know if you're done yet, and if not, when and how much it will cost. They have their own jobs to do and don't have the time or interest to peek behind the curtain.
Do project managers still use critical path? Some. I haven't needed it in a while; lately I've had more product-focus than project or used project approaches where critical path doesn't calculate (you can't calculate a path that doesn't exist, yet, and if there aren't any branches in the path calculating critical path becomes redundant). If I had need to use MS Project, I would likely also be paying attention to critical path. AI wouldn't change that need.
You wrote: "AI can process more data and provide faster analysis than a human project manager."
You're not technically wrong, but I don't typically do this by hand. If I'm using a tool, like MS Project, and keeping it updated, I usually only have to enter a little information and click a couple of buttons to see the critical path. I'm not tracking my projects in AI, and until I enter data and ask AI to do something, it's doing nothing. It's only faster if it has the data and somebody asks it to do something with the data.
A major shortfall of MS Project is it's reporting capabilities, at least for the desktop version. Add an AI to MS Project, to supplement it's existing capabilities, that allows non-PMs to ask for data and that would be interesting. At that point, project managers might be getting the critical path from the AI. Most other people probably wouldn't ask for it.
I think this statement might be overstating AI's current capabilities:
"AI tools assess all the factors in real-time and notify the project manager in advance of issues."
It might be more accurate to say that AI tools assess the information they have available to them and can raise both risks and opportunities, identifying potential impact, based on the information available to them. With enough information, an AI could possibly estimate how early a risk or opportunity might present itself, but unless you're talking about an Autonomous AI that contains all the data you need, somebody still has to enter the data and then ask the AI to do something with it.
Don't get me wrong. I'm not a luddite and I like new tools. It's interesting and fun, even, to imagine the possibilities. It just seems that, in a future where an Autonomous AI has the information it needs to give you the most likely date that a project will be finished, if it has been programmed to do so, it will run a PERT analysis and calculate the critical path then answer your question without telling you how it got the answer. Chances are that you'll only care how it got the answer if the answer was wrong or if you have to repeat the process on your own.
Eduard HernandezSenior Project Manager| Prothya BiosolutionsAmsterdam, Netherlands
Aaron makes very valid points; there is little left to add.
"This concept is in serious need of modernization." I disagree. This assertion is akin to suggesting that Pythagoras' theorem requires modernization due to its development over 2500 years ago. While critical path management does indeed need to adapt to modern tools and evolving environments, it requires no more than that.
Kwiyuh Michael WepngongSenior Accountant| Africa Eye Foundation; Magrabi ICO Cameroon Eye InstituteYaounde, Centre, Cameroon