Project Management Central

Please login or join to subscribe to this thread

Topics: Benefits Realization, IT Project Management, Scheduling
Which part of PM should be better automated?
Network:73



In short, at the moment our team is working on a project management tool with a neural network which will be trained during the workflow to improve the accuracy of time estimation and sprint planning.

Recently I found a nice article "How AI could revolutionise project management" on CIO. Some their ideas overlapped with our ones, but there also were some new points of view on the issue. In this regard, I wonder if you can offer some other ways or areas where software and AI in particular could be helpful? Which project management tasks should be more automated and simplified with such a software?
Sort By:
Network:648



Kate -

I wrote an article about this a few weeks ago - I believe the shift which unsupervised machine learning can provide PMs is from automating administrative work (e.g. creating schedules following CPM or other scheduling approaches) to guiding project decision making based on a broad & deep knowledge of historical projects.

For example, whereas today you could use a Monte Carlo simulation tool to get a distribution of cost & schedule outcomes based on your providing a lot of inputs and spending a lot of upfront effort, a future Computer Assisted Project Management (CAPM) tool would look at the data already provided about a project and provide guidance regarding schedule or cost baselines.

I could also envision being able to ask a computer (a la Star Trek) what the recommended approach would be to deal with an issue.

Kiron
...
1 reply by Kate Lynska
Feb 23, 2018 5:18 PM
Kate Lynska
...
Thanks for the answer, Kiron, I support your views completely!
Network:706



HI,
All the KPI and others predictions tools can be produced automatically.
The "knowledge Area" Project Cost Management is concerned by the automation.
Another interesting point should be to automate or try to automate the risk management using some predictive models and lessons learned of similar projects.
...
1 reply by Kate Lynska
Feb 23, 2018 5:21 PM
Kate Lynska
...
Thank you for reply! We hope to automate risk management with some predictive models and gathered statistics of previous projects.
Network:1530



@Kate, if your team is working on that then you and your team know something basic: the final decision rest on the human being. I mean, the neural network will give you at the end three possibilities and somebody will choose from them based on probability. In your case like into other cases AI will perform the same work that "ancient people" like me performed by hand. So, you can use AI into any point of your project/program/portfolio management process. By the way, we created applications related to portfolio management based on AI.
...
1 reply by Kate Lynska
Feb 23, 2018 5:27 PM
Kate Lynska
...
Thanks, Sergio!

Of course, the role of man still remains significant in this area. We just want to reduce hand work as much as possible.
Network:73



Jan 22, 2018 11:14 AM
Replying to Kiron Bondale
...
Kate -

I wrote an article about this a few weeks ago - I believe the shift which unsupervised machine learning can provide PMs is from automating administrative work (e.g. creating schedules following CPM or other scheduling approaches) to guiding project decision making based on a broad & deep knowledge of historical projects.

For example, whereas today you could use a Monte Carlo simulation tool to get a distribution of cost & schedule outcomes based on your providing a lot of inputs and spending a lot of upfront effort, a future Computer Assisted Project Management (CAPM) tool would look at the data already provided about a project and provide guidance regarding schedule or cost baselines.

I could also envision being able to ask a computer (a la Star Trek) what the recommended approach would be to deal with an issue.

Kiron
Thanks for the answer, Kiron, I support your views completely!
Network:73



Jan 22, 2018 11:26 AM
Replying to Sylvain Costy
...
HI,
All the KPI and others predictions tools can be produced automatically.
The "knowledge Area" Project Cost Management is concerned by the automation.
Another interesting point should be to automate or try to automate the risk management using some predictive models and lessons learned of similar projects.
Thank you for reply! We hope to automate risk management with some predictive models and gathered statistics of previous projects.
Network:73



Jan 22, 2018 12:49 PM
Replying to Sergio Luis Conte
...
@Kate, if your team is working on that then you and your team know something basic: the final decision rest on the human being. I mean, the neural network will give you at the end three possibilities and somebody will choose from them based on probability. In your case like into other cases AI will perform the same work that "ancient people" like me performed by hand. So, you can use AI into any point of your project/program/portfolio management process. By the way, we created applications related to portfolio management based on AI.
Thanks, Sergio!

Of course, the role of man still remains significant in this area. We just want to reduce hand work as much as possible.
...
1 reply by Sergio Luis Conte
Feb 28, 2018 4:05 PM
Sergio Luis Conte
...
That is not about AI.
Network:1530



Feb 23, 2018 5:27 PM
Replying to Kate Lynska
...
Thanks, Sergio!

Of course, the role of man still remains significant in this area. We just want to reduce hand work as much as possible.
That is not about AI.
Network:57



I am currently working on developing models for AI tool development in the following areas:
- checking for consistency across project documents (using PMBOK® Table 4-1 as a reference)
- change request impact
- risk assessment and impact based on environmental factors

Please login or join to reply

Content ID:
ADVERTISEMENTS

I have made good judgements in the past. I have made good judgements in the future.

- Dan Quayle