Project portfolio management (PPM) ensures organizations direct resources toward the right projects at the right time. This guide includes expert advice on the top six PPM best practices, a downloadable project portfolio heatmap template, and tips for using AI in PPM.
Project portfolio management best practices include aligning projects to business strategy, using objective criteria, managing resources and risks, practicing adaptive governance, and engaging stakeholders early. These practices ensure that organizations invest in the right initiatives and that portfolios are balanced.
Below, you’ll find more detail about these top six PPM best practices:
1. Align Projects to Business Strategy
Choose only the projects that directly support your organization’s strategic objectives.
“Every project should serve business goals. Every project in the portfolio should directly connect to shared business objectives. Otherwise, it drains resources without adding real value.”
For example, if a company is trying to grow market share, it might prioritize funding the development of a new product over upgrading internal office software since the new product directly supports that growth goal.
2. Use Objective Criteria
Prioritize projects using clear, organization-wide criteria, rather than relying on departmental preferences.
“A key mistake I see in PPM is that projects are often selected by individual departments based on local benefit, not overall organizational strategy. This pits groups against one another instead of sharing strengths, which keeps the organization from achieving its full vision.”
This practice is not just about having criteria, but about making sure you’re selecting the right criteria. “It’s common that the only metrics used to track and measure projects are ‘on time and on budget,’ instead of the actual business value and strategic outcomes achieved,” says Schuberth. “We must continue to assess impact during and after a project is delivered to best understand ongoing needs and investment priorities.”
Having clear, objective criteria keeps the focus on the initiatives that matter most. “Companies need to establish clear selection frameworks, specifically focusing on value creation, not politics or noise,” says Nagaralawala.
3. Manage Resources and Dependencies
Every portfolio is more than a collection of separate projects. Since projects in a portfolio are related, leaders need to monitor the project interdependencies and resource constraints. Regularly assess resource demand versus capacity across projects to prevent overloading team members and to sequence work realistically. Nagarlawala stresses the importance of this practice.
Nagarlawala stresses the importance of this practice. “Portfolios fail not because projects are bad,” he says, “but because organizations overstretch people, budgets, or technology without proper sequencing.”
4. Assess Risks and Value
In addition to resources and dependencies, portfolio managers need to oversee risks. Maintain a mix of projects and initiatives in a way that optimizes ROI while managing risks and constraints. Rebalance as conditions change.
To do this, Jacob Kalvo, Founder and CEO of Live Proxies suggests monitoring outcomes with regular reviews.
“My company uses extensive real-time data and performance dashboards to make sure our portfolio decisions are captured in short-term deliverables as well as long-term growth.”
Standardize who can approve decisions. By doing so, prioritization and resource allocation remain consistent and transparent throughout the organization.
Governance should support agility rather than rigidity. “There is a need for regular reviews and flexibility, especially for those industries that change quickly, like cybersecurity and data infrastructure, since priorities can shift fast based on new threats or market needs,” says Kalvo.
Regular reviews also allow leadership to make tough but necessary calls about how to allocate resources. “Organizations are often hesitant to stop investing in failing projects or projects that have delivered adequate value over including final shiny touches,” says Schuberth. “This wastes resources instead of leveraging them to bring more value to your organization or your customers through new initiatives.”
Nagaralawala suggests building in kill criteria: conditions that signal when a project should be stopped or re-evaluated before further investment.
6. Engage Stakeholders
Ensure that management transparently communicates project goals, status updates, and decisions across all levels of the organization. By engaging stakeholders early, you build trust and encourage faster, smarter decision-making.
Smartsheet project portfolio management software helps you standardize processes, track performance in real time, and make smarter decisions across your entire portfolio.
Teams can use this template to quickly compare multiple projects across key risk and value criteria. It’s designed for portfolio managers, PMOs, or leadership teams to spot which initiatives need attention or carry the greatest risk. Simply enter details about each project and a score for the listed criteria, and the color-coded cells will display project health at a glance.
Project Portfolio Management Case Study
Below is a real-world project portfolio case study shared by Schuberth. In this situation, two PMOs merged without any resource visibility or strategic alignment. The table below explains how Schurberth’s team implemented a prioritization framework; this approach can be used by any size or type of team to standardize project selection and resource allocation.
“It reflects the challenges and solutions common to a scaling organization navigating significant change, a key area for Cheryl Worldwide,” says Schuberth.
Challenge
Situation
Solution & Impact
Post-Acquisition Chaos
Two PMOs merged, resulting in more than 150 legacy projects, poor resource visibility, and zero alignment on strategic value. Teams were burned out and stuck.
Schuberth’s team introduced a single, transparent prioritization framework (with weighted scoring of strategic fit, risk, and ROI) to evaluate every project.
Resource Bottlenecks
Critical subject matter experts (SMEs) were unknowingly allocated to 150 percent of their capacity across projects in both organizations.
Her team established a centralized resource capacity model on the platform. The PPM team held transformative conversations with executive leadership to force a stop/defer/go decision on the bottom 40 percent of the portfolio.
No "Kill Switch"
Projects that were failing or no longer strategically relevant kept consuming budget due to political inertia.
Schuberth implemented a quarterly portfolio review rhythm to objectively measure projects against their strategic outcome. If a project missed its key result, the default decision was to terminate it unless the sponsor presented a compelling, pre-approved case to adjust the strategic outcome and secure new resources.
“Within six months, the organization reduced its active project count by 35 percent, completing the strategic integration initiatives three months ahead of schedule by reallocating $1.2 million in capital freed from the cancelled projects,” says Schuberth. “The PPM practice became the engine for operationalizing the vision for the newly merged entity.”
Make a business case for Project Portfolio Management
Best Practices for AI-Driven Project Portfolio Management
Best practices for AI-driven project portfolio management include aligning AI tools with business strategy, ensuring data quality, and integrating predictive analytics for more accurate forecasting. Start with pilot projects, invest in change management to drive adoption, and balance AI insights with human judgment.
PPM works best when managers choose projects not just for their individual benefits, but for how well they support organizational strategy. AI can process large quantities of data to spot patterns and predict which projects will create extra value when combined — something humans might miss.
However, in a 2024 study on the use of AI by project, program, and portfolio managers, “Artificial Intelligence and Project Management: Empirical Overview, State of the Art, and Guidelines for Future Research,” researchers advise caution while adopting AI methods. While they found portfolio management use cases in automated forecasting, risk assessment, resource allocation, and data-driven decision support, they also found significant drawbacks, such as poor data quality, lack of transparency in AI decision-making, and limited strategic impact.
Nagaralawala and Schuberth both echo this sentiment. “AI struggles with context, politics, and cultural nuances — areas where leadership and human experience are irreplaceable,” says Nagaralawala. “For example, deciding to continue or cancel a project often depends on stakeholder trust and strategic timing, not just numbers.”
Similarly, Schuberth explains that at Cheryl Worldwide, AI is viewed as an “execution accelerator,” but is not used for tasks that “require human intervention, judgment, and emotional intelligence.”
Here are her top four best practices for using AI in PPM:
Start With the Data Foundation: AI is only as good as the data it analyzes. Standardize data fields (risk ratings, status codes, resource roles) across PM and PPM systems before implementation.
Define the "Why": Use AI to solve a specific business problem (e.g., "We are consistently late in resource assignment," or "Our data is untrustworthy"), not just to have the latest tech.
Embed Human Oversight: Treat AI recommendations as decision support, not decision replacement. Every high-stakes AI output (e.g., a portfolio rebalancing suggestion) must be reviewed, vetted, and signed off by a human portfolio manager.
Prioritize Transparency: Leaders must be able to explain how the AI arrived at its recommendation to build trust across the organization. People need to understand the "why" of the algorithm.
Ultimately, when used with human oversight, AI is a powerful tool in portfolio management. For example, Smartsheet AI offers a suite of features designed to blend automation, analytics, and intelligent assistance. It provides data-analysis and formula generation capabilities, as well as AI agents and workflow automation. These tools not only help plan projects and flag risks, but can step in to carry out tasks — with employee approval — and automate multistep processes at scale.
AI Features for PPM Software Comparison Chart
To make the most of AI in intelligent project portfolio management, teams should understand not only what tools are available, but also how to apply them responsibly. The table below highlights key AI features available, as well as practical guidance for using each effectively.
AI Feature
What It Does
Best Practice for Use
Predictive Forecasting
Analyze project performance and resource data to predict delays or overruns.
Use as an early-warning system. Always validate forecasts with team input.
Risk Identification and Scoring
Flag potential schedule, budget, or dependency risks based on patterns in historical data.
Regularly update data sources to maintain accuracy; combine with human risk reviews.
Resource Optimization
Suggest how to allocate or reassign resources across projects for best portfolio efficiency.
Review AI recommendations in the context of team capacity and skills before approving.
Automated Reporting and Dashboards
Compile and summarize project data for leadership visibility.
Customize dashboards to focus on only a few, decision-relevant KPIs; avoid overloading with metrics.
Workflow Automation
Execute routine project tasks, reminders, or approvals.
Start small by automating repeatable tasks first; ensure human review for exceptions.
Smartsheet project portfolio management software helps you standardize processes, track performance in real time, and make smarter decisions across your entire portfolio.
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