Project Management With Artificial Intelligence & Machine Learning

By Anil Ranjan, DGM-IT at Macawber Beekay Pvt Ltd

The project manager plays a critical role in ensuring that all project task is completed on time and with perfection. Choosing automated project management software for a manufacturing industry is not easy and that will have far reaching positive effect in future. Project teams that will take advantage of project management software with artificial intelligence will move faster and with more accuracy than to those that don’t. Project management AI is an integrated system that can administrate projects without requiring human input. Usage of Machine learning in project management can help project managers in fore casting Stakeholder behaviors, revenue and risks based on historical data and organization knowledge base.

Some feature that will help project-based company by using AI & ML automated project management software.

a. Artificial Intelligence software have advance capabilities that can-do day-to-day project management without any specialized person and can save time.

b.Intelligent Project & Risk Management: AI systems can perform complex tasks and make strategic recommendations which will improve the overall project outcomes. Automated project management software utilizes the power of machine learning and AI to predict the outcome of projects and project status using the data at hand and past project data, such as planned start and end dates to predict realistic timelines for future projects. Artificial intelligence can support quantitative risk management by understanding the risk thresholds in a particular project.

c. Operational efficiency: it can ensure that all tasks & activities are running as per project plan. Artificial intelligence is a smart solution to get complete operational efficiency and streamlining the project. Future visualization techniques, feasibility reports, and risk-calculation are some advanced techniques that can be achieved  by automated project management software.

d.  Resource Management: AI can use past projects data and give real-time analysis report on resource engagement. Based on this, we can even add extra hands or take people off the project. Artificial intelligence can also help to track the progress of project activities in the real-time so that allocations of future resource can be managed in time. Additionally, predictive analytical tools contain the exception handling feature, which can guide us regarding excess or shortage of the right resources.

e. Forecasting & Estimation: Automated project  management software systems can have a specialized module such as machine learning that can help in determining the best cost estimation. Forecasting  techniques are used to fine-tune project execution to make sure all tasks complete at planned schedule.

f. Knowledge based decision system: As an experienced project manager, we know that unplanned changes to project scope can cause failure/delay/loss. A Knowledge based decision system consists of project manager’s experiential knowledge, previous successful/ failed projects lesson learning database and multiple conditional statement like IF-THEN, WHILE…. Which helps in getting conclusions for the planning and scheduling phases of the project.

g. Artificial Neural network can calculate cost overrun, behind/ahead of schedule, identify the longest and shortest path to complete an activity based on critical path network diagram.

h. Project manager can use machine learning to analyze social networks like twitter feeds, Facebook comments ,web reviews to understand the end-user feedback ,concerns ,perceptions for a product which is rolled out to a mass market.

But AI can’t replace the human project manager as it can’t motivate to project team. Especially, the areas where sympathy and compassion are essential.

As a project manager we know that there is 5 Project management process and 10 Knowledge areas.

Project Management process (Project Initiation, Planning, Execution, Monitoring and Controlling, Closing);

Knowledge areas (Project Integration, Scope, Time, Cost, Quality, Human Resource, Communication, Risk, Procurement and Stake holder Management);

1. Project manager are over confident and doesn’t follow project management complete life cycle on document.

2. Sometime project manager uses the project management software due to contractual obligation as customer/client demands project schedule, CPM/Gannt chart and a brief project plan from a specific software.

3. There is no Project plan for Quality, Risk, Communication& stake holder management.

4. Not breaking down the deliverables into a detailed set of tasks

5. Not curtailing scope expansion based on the project’s scope statement

6. Not adjusting future estimates based on estimating error trends

7. Not adjusting future work based on current reality and its impact on project completion

8. Not tracking external dependencies

9. Not to follow CPM chart which encourages a logical discipline in the planning, scheduling, and control of projects, All project personnel can get a complete overview of the total project….etc

10. There is no Project Management Office (PMO) which is a centralized management structure for a group of projects in an organization, aimed at ensuring standardization, reducing duplication and leveraging resources such as people, technology, and communication.

Project Management software with AI can help in above scenario but there aren’t many project management tools with machine learning and artificial intelligence. Some such software, I have heard about CLICKUP & RESCOPER.

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