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Implications of Artificial Intelligence on Project Management

The IIL Blog

For over a quarter of a century, the Standish Group has tracked, reported, and improved software-intensive project success rates. [1] The future of AI in project management will depend on how we implement, use, and govern it! Eugene Bounds is presenting at this year’s #IPMDay2023! Check out his presentation details here.

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Current State and Future Prospects of Scrum and Agile Development in Japan

Scrum.org

The paper presents successful examples of new product development projects by Japanese companies and lays out some of the characteristics these projects had in common. In other words, for most people in Japan, software development was and remained an exercise in box checking. But, once again, this palpable crisis triggered adaptation.

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Project Management Maturity Models: A Basis for Reaching Your Organization’s Business Success

Epicflow Blog

Assessment presents methods, processes, and procedures that a company can use to self-assess its maturity. . The first dimension present the 10 Knowledge Areas defined in the PMBOK Guide. Improvement outlines the way from a company’s current maturity level to a more sophisticated one. . Let’s take a look at these levels. .

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Misunderstanding Making Decisions in the Presence of Uncertainty

Herding Cats

The notion (as suggested in the quote) of shifting from accurate (what ever that means) ways of estimating to reliability shipping be a date is not physically possible since the irreducible and reducible uncertainties are always present. Hybrid–Agile Software Development Anti–Patterns, Risks, and Recommendations,” Paul E.

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Risk Management Resources

Herding Cats

Taxonomy-Based Risk Identification,” Marvin Carr, Suresh Konda, Ira Monarch, Carlo Ulrich, and Clay Walker, Technical Report, CMU/SEI-93-TR-6, Software Engineering Institute, June 1993. IEEE Transactions on Software Engineering , Vol. Software Engineering Institute, January 1996. De Meyer, C. Loch, and M.

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A Compendium of Risk Management Resources

Herding Cats

Taxonomy-Based Risk Identification,” Marvin Carr, Suresh Konda, Ira Monarch, Carlo Ulrich, and Clay Walker, Technical Report, CMU/SEI-93-TR-6, Software Engineering Institute, June 1993. IEEE Transactions on Software Engineering , Vol. Software Engineering Institute, January 1996. De Meyer, C. Loch, and M.

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9 Best Practices for Recruiting Developers With Skills Tests

Teamweek

What’s the problem with recruiting software developers? The demand for software developers far outweighs the available supply, making it a real challenge to find the right candidates. To make matters worse, top-notch software engineers know their worth and often expect handsome salaries.