Project Portfolio Management (PPM)

Realize the benefits of a mature PPM capability

The discipline of PPM is evolving. As organizations move from managing projects to also managing products, services, and offerings, it’s helpful to have a mature PPM capability to manage the organization’s work investments and realize the benefits of PPM:

• Financial efficiencies: Implementing demand management, project/program management, and resource management can give organizations the flexibility to cut their in-flight portfolio by as much as 30 percent or redeploy 30 percent of in-flight portfolio resources to more strategic initiatives.
• Portfolio alignment: Doing the “right” things and canceling the “wrong” things helps keep the portfolio aligned with the enterprise strategy.
• In-flight portfolio health: Bolstering important initiatives, as well as discovering, correcting, and canceling unhealthy initiatives improves the health of your portfolio.
• Portfolio efficiency: Increasing work management efficiency through visibility and governed accountability means less “junk” thrown into the demand funnel. Projects are done faster, and more projects succeed.
• Business partner culture: Fostering an organization that’s comfortable with the transparency and efficiencies enabled by PPM breeds a workforce of collaborative and informed leaders. Delivery organizations evolve from order takers to trusted advisers—earning a seat at the table and the confidence to “own it.”
• The gift of time: Delivering material efficiencies on processes like annual budgeting, dashboard reporting, and even data cleanup can save time and effort that can be redirected to other value-add activities.
  

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The future of PPM in the era of AI and machine learning

In the near future, bots will be used to automate the least value-add and most repetitive aspects of PPM. This includes tasks like status reporting, cost accounting, and resource allocation. Machine learning and artificial intelligence (AI) will impact each of the PPM capabilities in different ways:

• Work management: Machine learning can be used to identify risks in budget, schedule, and resources and generate notifications and action items for people to act on as appropriate.
• Demand management: Machine learning can organize work ideas, then prioritize and resolve the more common requests, leaving the exceptions for human intervention.
• Resource management: Machine learning can more effectively match talent supply with business demand and automate time entry and approval, allowing people to work on higher level tasks related to exceptions and pattern inconsistencies.

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​Meet the authors

Chris Garibaldi is the Deloitte Consulting LLP principal who built Deloitte’s PPM practice.

Michael Ravin is the Deloitte Consulting LLP Practice Leader for Project Portfolio Management.

Matthew Ku, Luke Losinski and Will Major are senior leaders in the PPM practice who have worked with Deloitte’s largest global clients on PPM strategy, implementation, and ongoing maturity.

Christopher Martin and Travis Parker specialize in PPM, application portfolio management, and organizational change management.