How AI Can Help Solve Complex Project Portfolio Prioritization Challenges

Michael R. Wood is a Business Process Improvement & IT Strategist Independent Consultant. He is creator of the business process-improvement methodology called HELIX and founder of The Natural Intelligence Group, a strategy, process improvement and technology consulting company. He is also a CPA, has served as an Adjunct Professor in Pepperdine's Management MBA program, an Associate Professor at California Lutheran University, and on the boards of numerous professional organizations. Mr. Wood is a sought after presenter of HELIX workshops and seminars in both the U.S. and Europe.

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Topics: Artificial Intelligence, Construction, PMO, Portfolio Management, Strategy

One of the most complex functions large PMOs manage is the prioritization of the organization’s portfolio of projects. This complexity comes from the number of factors and variables involved in continuously prioritizing projects when new projects are added to the mix—and even more so when the entire basket or projects needs to be examined based on external disruption like the pandemic, extreme weather, and strikes.

Some of the factors that need to be considered (especially in the construction industry) when recasting the project priorities include:

• Talent resource availability (internal and external)
• Regulatory climate
• Extreme weather probabilities
• Potential and impact of industry strikes
• Potential and implications of supply chain disruptions
• Inflation and other cost-increasing situations
• Impact of missed contracted completion dates (on projects, penalty costs, etc.)
• Physical interdependencies between projects
• Competitive impact due to lost windows of opportunities
• Impact on industry reputation
• Impact on operating profit
• Impact on the missed realization of benefits related to achieving the organization’s strategic objectives

If each of these factors could be considered independent from the others, the portfolio prioritization process wouldn’t be overly daunting. However, because the above factors are usually …

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