AI Product Manager (B2B) for PMI| Project Management Institute (PMI)Middletown, DE, United States
Hi PMI Community! I'm Kerry Brooks, a Product Manager at PMI, and we're looking to use your feedback to identify opportunities and gaps as we build a risk sentiment tool for project managers.
Risk management is widely considered one of the most important aspects of a project manager's role.
Effectively identifying, assessing, and mitigating risks can significantly impact the success of a project. It involves anticipating potential issues, analyzing their potential impact on the project's objectives, and developing strategies to minimize or eliminate these risks.
Imagine you have an AI-assisted risk application that can help you. How do you think it could be your secret weapon in handling risks?
From predicting hiccups to offering solutions, share your wildest AI-assisted risk management dreams! Saving Changes...
Senior Projects Manager | Field & Marten AssociatesNew Westminster, British Columbia, Canada
Kerry Brooks: Good Question. An AI-Assisted Risk Application can help in many ways but it will be so valuable if it can do the following:
1) Customized Risk Profile tailored towards different stakeholders. This will ensure that the RM Strategies are aligned to the priorities of the different stakeholders.
2) Scenario Planning and Simulation: Providing different scenarios will enhance decision making and allow the team to assess the potential impact of different responses.
3) Automated Risk Responses: Not for everything, but for certain mitigation measures, the automation will help reduce the time lag between risk detection and remediation.
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1 reply by Kerry Brooks
Mar 14, 2024 3:32 PM
Kerry Brooks
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Rami Kaibni I appreciate your thoughts and input on ideas. We'll take note of those for future exploration. Your third point though, does match up with a hypothesis we're testing around capturing team sentiment on project progress and meeting those goals, identifying risks to getting there and then providing recommended mitigation steps. We'll definitely need to learn and evolve the tool to support, but it's a problem we're trying to address.
Saving Changes...
George FreemanThought Leader | Author | Architect| Florida, United States
Hi Kerry,
An “AI-assisted risk application” will/can only provide generic value, as it would require the following to surpass generalities:
[1] Cross-functional SME-level knowledge of the domains that will be traversed in the project. [2] A life-cycle-based understanding (development and business) of the proposed and/or running project. [3] A contextual understanding of the intersection of [1] and [2] across all phases of the project
That said, the generic (i.e., non-contextual) value of an “AI-assisted risk application” can still assist a project manager by challenging deeper contextually based dives into the stated generalizations. However, if one accepted the generalities as their definitive risk statements, this “secret weapon” would lend itself to the mass destruction side of the equation versus the positively formed secret weapon you referenced.
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1 reply by Kerry Brooks
Mar 14, 2024 3:26 PM
Kerry Brooks
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George Freeman - absolutely! Generic can provide direction, but true context and understanding is key. We're hoping to develop an organizational tool, that teams, product leaders, and executives feel comfortable sharing their project, program, and portfolio info so we can summarize project risks based on team sentiment and provide mitigation strategies to thwart or reduce those risks. To start, the risk mitigation steps may be high-level, but leveraging our Infinity AI platform in the background will hopefully help us provide more robust responses.
Risk management is the poorest performed knowledge area across most organization and simply leveraging AI will not increase its effectiveness.
Dr. David Hillson brilliantly defines risk as "uncertainty that matters" and it clearly does not to many risk/risk response owners. Sometimes this is the fault of the PM or team in how they capture and communicate risk info but other times it is a result of low organizational maturity.
Assuming there is a reasonable level of risk management competency, then AI tools can definitely help with identification and assessment processes. And to make "risk matter", AI tools can help a PM refine the wording of a risk event description or a request to implement a risk response.
Kiron
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1 reply by Kerry Brooks
Mar 14, 2024 3:22 PM
Kerry Brooks
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Kiron Bondale - thanks for your thoughts on this topic. Identifying, managing and mitigating risks are so critical to the success of the project, yet, as you mention is a challenge for project leaders and their organizations. Our goal with our tool we'd like to test is to see if we can make that job a bit easier, build confidence in the project leader and organization around managing risks, and help them to mitigate risks early and often.
If we consider LLM support, as a prerequisite companies must have a large amount of data, especially on lessons learned. With that said, it would be useful to have a tool that can understand the new project's context and report every applicable lesson learned during project initialization.
Moving to the execution phase of a project, a tool that can alert on potential risks on the latest information on project status would be very useful (based on general purpose and dedicated knowledge base). Since we are dreaming, such a tool could propose very specific mitigations if there is already a risk response plan in place, or it could propose new mitigations if there isn't one.
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1 reply by Kerry Brooks
Mar 14, 2024 3:19 PM
Kerry Brooks
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Hi Riccardo Strusani - thanks for sharing your thoughts regarding the lessons learned piece. We're exploring that area and it has a strong connection to mitigating risks in the future. To your second point regarding the execution phase and alerts on potential risks, that's what we're trying to get at with a new tool we're thinking of developing and testing. Capturing team member sentiment on how they're progressing against project, sprint, or cycle goals and why they feel there are risks to meeting those goals or if they feel it's progressing positively. If there are risks, the tool, using AI can suggest mitigation strategies.
I will add a different perspective. I think there should be no 'secret' anything in AI.
Of course, AI can help with risks, but it should be transparent and responsible. To reduce manipulation potential.
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1 reply by Kerry Brooks
Mar 14, 2024 3:15 PM
Kerry Brooks
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Agreed Tomasz Grochowski. There should not be anything "secret" about risks or AI. We're looking at trying to solve the problem of surfacing unsaid issues and risks based on team sentiment. This may help the project leader identify issues sooner rather than later.
Saving Changes...
Sergio Luis ConteHelping to create solutions for everyone| Worldwide based OrganizationsBuenos Aires, Argentina
Because it give me the possibility to know three types of risks that can occur in projects: known-knowns, known-unknowns, and unknown-unknowns. Mainly the last ones.
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1 reply by Kerry Brooks
Mar 14, 2024 3:13 PM
Kerry Brooks
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Hi Sergio - thanks for your response. We are looking to test a tool that helps us get to the unknown-unknowns. Our hypothesis is if we can synthesize project team sentiment to get to those "underlying uneasy feelings and issues" about how the project is progressing, and provide mitigation steps to manage them early, we may be able to help our project leaders keep the project on-track.
AI Product Manager (B2B) for PMI| Project Management Institute (PMI)Middletown, DE, United States
Mar 14, 2024 6:03 AM
Replying to Sergio Luis Conte
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Because it give me the possibility to know three types of risks that can occur in projects: known-knowns, known-unknowns, and unknown-unknowns. Mainly the last ones.
Hi Sergio - thanks for your response. We are looking to test a tool that helps us get to the unknown-unknowns. Our hypothesis is if we can synthesize project team sentiment to get to those "underlying uneasy feelings and issues" about how the project is progressing, and provide mitigation steps to manage them early, we may be able to help our project leaders keep the project on-track.
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2 replies by Jari Anttila and Suraj Gade
Mar 15, 2024 11:05 AM
Jari Anttila
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Hi Kerry Brooks,Sounds very interesting when trying to capture risk based on project team sentiment. Do you have ideas on how to collect the data that could be used to identify risks?
AI Product Manager (B2B) for PMI| Project Management Institute (PMI)Middletown, DE, United States
Mar 13, 2024 9:27 AM
Replying to Tomasz Grochowski
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I will add a different perspective. I think there should be no 'secret' anything in AI.
Of course, AI can help with risks, but it should be transparent and responsible. To reduce manipulation potential.
Agreed Tomasz Grochowski. There should not be anything "secret" about risks or AI. We're looking at trying to solve the problem of surfacing unsaid issues and risks based on team sentiment. This may help the project leader identify issues sooner rather than later. Saving Changes...
AI Product Manager (B2B) for PMI| Project Management Institute (PMI)Middletown, DE, United States
Mar 13, 2024 7:39 AM
Replying to Riccardo Strusani
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Hi Kerry,
If we consider LLM support, as a prerequisite companies must have a large amount of data, especially on lessons learned. With that said, it would be useful to have a tool that can understand the new project's context and report every applicable lesson learned during project initialization.
Moving to the execution phase of a project, a tool that can alert on potential risks on the latest information on project status would be very useful (based on general purpose and dedicated knowledge base). Since we are dreaming, such a tool could propose very specific mitigations if there is already a risk response plan in place, or it could propose new mitigations if there isn't one.
Hi Riccardo Strusani - thanks for sharing your thoughts regarding the lessons learned piece. We're exploring that area and it has a strong connection to mitigating risks in the future. To your second point regarding the execution phase and alerts on potential risks, that's what we're trying to get at with a new tool we're thinking of developing and testing. Capturing team member sentiment on how they're progressing against project, sprint, or cycle goals and why they feel there are risks to meeting those goals or if they feel it's progressing positively. If there are risks, the tool, using AI can suggest mitigation strategies. Saving Changes...
Risk management is the poorest performed knowledge area across most organization and simply leveraging AI will not increase its effectiveness.
Dr. David Hillson brilliantly defines risk as "uncertainty that matters" and it clearly does not to many risk/risk response owners. Sometimes this is the fault of the PM or team in how they capture and communicate risk info but other times it is a result of low organizational maturity.
Assuming there is a reasonable level of risk management competency, then AI tools can definitely help with identification and assessment processes. And to make "risk matter", AI tools can help a PM refine the wording of a risk event description or a request to implement a risk response.
Kiron
Kiron Bondale - thanks for your thoughts on this topic. Identifying, managing and mitigating risks are so critical to the success of the project, yet, as you mention is a challenge for project leaders and their organizations. Our goal with our tool we'd like to test is to see if we can make that job a bit easier, build confidence in the project leader and organization around managing risks, and help them to mitigate risks early and often.
I'd definitely be interested in a risk-focused AI capability which could write risk event descriptions clearly articulating the cause and effect and in terms which would make risk response owners sit up and pay attention. It would also be ideal to have support in identifying hidden risks - shedding light on more of the unknown-unknowns.
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