The Modern Approach to Project Management

Aviral Vaid

Aviral Vaid

Jun 08, 20232 min read

0

The Modern Approach to Project Management

In today's fast-paced world, project management has become a crucial part of every business. With the emergence of new technologies and methodologies, it's essential to keep up with the latest trends to stay ahead of the competition. Two popular approaches to project management are Agile and Project Portfolio Management (PPM), which can be combined to create a hybrid model. This essay will explore the benefits of this hybrid approach and how it can be implemented using machine learning.

The Google Way to Use Machine Learning for PMs

Google has been at the forefront of innovation for years, and their approach to project management is no exception. They have integrated machine learning into their PPM process, which has resulted in increased efficiency and better decision-making. By analyzing data and identifying patterns, PMs can make informed decisions, prioritize tasks, and allocate resources more effectively. This approach has enabled Google to complete projects faster and with greater accuracy.

Combining Agile and Project Portfolio Management - Hybrid Agile

Agile is a popular methodology that focuses on flexibility, collaboration, and continuous improvement. PPM, on the other hand, is a strategic approach that aligns projects with business goals. Combining these two approaches can result in a hybrid model that offers the best of both worlds. By using agile practices within a PPM framework, organizations can prioritize projects, allocate resources, and adapt to changing requirements. This approach can help organizations achieve their strategic objectives while maintaining agility.

Implementing Machine Learning in Hybrid Agile

To implement machine learning in a hybrid agile model, organizations must first identify the data sources they need to analyze. This could include project timelines, resource allocation, budget, and other relevant metrics. By using machine learning algorithms, organizations can analyze this data and identify patterns that can inform decision-making. For example, machine learning could be used to predict project completion times, allowing PMs to adjust timelines and allocate resources accordingly.

Conclusion

In conclusion, the modern approach to project management involves combining Agile and Project Portfolio Management in a hybrid model. By integrating machine learning into this model, organizations can achieve greater efficiency, accuracy, and agility. Google has demonstrated the benefits of this approach, and many other organizations are following suit. As technology continues to evolve, it's essential to keep up with the latest trends to stay ahead of the competition.

Resource:

  1. "The Google Way to Use Machine Learning for PMs", https://productschool.com/blog/product-management-2/machine-learning-google-pm/ (Glasp)
  2. "(12) Combining Agile and Project Portfolio Management - Hybrid Agile | LinkedIn", https://www.linkedin.com/pulse/agile-project-portfolio-management-manifesto-jean-dieudonne/ (Glasp)

Want to hatch new ideas?

Glasp AI allows you to hatch new ideas based on your curated content. Let's curate and create with Glasp AI :)