PPM, surely AI can do that better?

Opportunities for portfolio management with AI | A graduate study by Niels Bos

With the growing complexity of organizations and their project portfolios, it is becoming increasingly difficult to plan effectively.
Projects today require scarce manpower and resources, have dependencies, and must account for numerous other constraints.
This makes manual planning not only time-consuming, but also costly and error-prone.
With AI taking over many time-consuming jobs, the question arises: can we also leave portfolio planning to artificial intelligence?

PPM, no breeze

Portfolio management is a field full of challenges.
Organizations are faced with the task of efficiently deploying scarce and critical resources to achieve their goals.
At the same time, many variables and dependencies must be taken into account.
This challenge increases as the portfolio grows with the business.
Traditional planning methods often fall short because they cannot respond quickly enough to changes and therefore are not flexible enough to make real-time adjustments.
This can lead to delays, budget overruns and inefficient use of resources.

The need for a system that can manage and optimize this complexity is becoming increasingly urgent.
AI offers a solution here by processing huge amounts of data while analyzing different scenarios and their consequences.
This allows organizations to not only create the most efficient schedule, but also gain immediate insight into the impact of any changes.

About Niels Bos

Niels Bos is a Computer Science Master’s student at the University of Twente.
He specialized in software development during his master and developed a passion for smart and practical algorithms.
With this passion, for his graduation Niels did research on automating project portfolio management using AI.
With this, he showed how AI can be used to optimize complex schedules and improve efficiency within organizations.

Genetic algorithms: (R)evolution in planning point

Genetic algorithms are a class of optimization algorithms inspired by the process of natural selection in evolution.
These algorithms are particularly well suited for solving complex problems with a large number of possible solutions.
The scheduling algorithm being developed for Fortes Change Cloud starts with a large number of possible schedules.
Each planning is evaluated based on multiple criteria, such as cost, lead time, resource utilization and contribution to strategic goals.
In several generations, the best scenarios are always included.
This makes it possible to generate (near) optimal schedules and outline different scenarios within seconds, allowing organizations to respond to changes quickly and efficiently.

A good prospect

In the future, companies that embrace this technology can benefit from automated portfolio planning.
The efficiency and accuracy offered by AI will lead to better resource utilization, shorter lead times and lower operating costs.
Organizations can react more quickly to changing conditions and respond more flexibly to new opportunities and risks.
In addition, portfolio managers can focus their time and energy on strategic tasks and creative solutions instead of time-consuming planning tasks.

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