Portfolio Outcomes and Investment Strategy

Strategy is an integrated set of choices that uniquely positions the firm in its industry so as to create sustainable advantage and superior value relative to the competition.

— A. G. Lafley, Playing to Win [1]

What is the purpose of a portfolio?

Portfolios govern an organization’s products, solutions, and strategic investments. Within each Portfolio, the Portfolio Leadership team is responsible for optimizing strategic alignment, maximizing the flow of value, and ultimately ensuring a return on investment, as shown in Figure 1.

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NOTE: Read the guidance “Outcome-Driven Product Development in AI-Native SAFe.” for more information on this approach and how it applies at every level of the Framework.

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This approach connects the portfolio’s declared outcomes with the customer and business value they create through investments in the products and solutions that run the business today, while also investing in those that will define it tomorrow.

Portfolio strategy has two parts (Figure 2). The first is the portfolio outcomes: what the portfolio pursues and how it is held accountable. The second is the investment strategy: how the portfolio allocates time, budget, and resources to achieve those outcomes. Together, they decide how the total portfolio budget is spent. 

Portfolio strategy and portfolio ambition are influenced by the budget.  A change in the budget may alter outcomes and the strategy. Because a finite budget binds them together, the work of portfolio leaders is to optimize the portfolio strategy as a system: the portfolio creates the most value when outcomes, budget, and investment strategy are balanced to deliver the best total return.

Moreover, there is a natural back-and-forth between Portfolio outcomes and investment strategy, as shown in Figure 2, as Portfolio Leaders assess options for affordability, feasibility, risk, and other factors as they strive to create a balanced portfolio that provides the best means for them to achieve a return.

Why AI necessitates accelerating the strategic investment cycle?

Portfolio management is a continuous operating and governance process. Portfolio strategy formulation and funding are episodic, taking as long as 6-9 months, and are typically annual. For example, an organization may initiate its strategy development and funding process in April or May for a fiscal year that starts in January. Unfortunately, this approach to planning typically results in a strategy that is outdated before it is even executed.  AI compounds this problem, as shown in Table 1, leading to strategies that have little chance of success. To counteract these challenges, a set of acceleration tactics can be applied, also shown in Table 1, designed to keep pace with the demands of competing in the Age of AI.

Dimension	The AI Reality	The Risk of Legacy (Slow) Cycles	Acceleration Tactics
Technology Velocity	AI capabilities evolve exponentially; tools can become commoditized or obsolete in months.	Investing in technology that is outdated by the time the annual budget is approved.	Quarterly Re-allocation: Treat budgets as dynamic investments with frequent adjustments.
ROI Predictability	High upfront uncertainty with asymmetric upside; exact returns are difficult to forecast using legacy methods and metrics.	Analysis paralysis; missing market windows due to a lack of a clear 5-year ROI.	Venture Capital Model: Place multiple small bets, fail fast, and double down on winners.
Competitive Dynamics	The “Data Flywheel” creates a winner-takes-most market where early deployment compounds advantages.	Competitors trigger their flywheel first, creating an unbridgeable capability gap.	Time-to-Value Focus: Prioritize speed of deployment and user-data capture over perfect product launches.
Resource Allocation	Talent, GPUs, and infrastructure demands shift rapidly and are highly contested.	Capital gets locked into rigid legacy IT roadmaps, starving AI initiatives of the critical resources they need.	Dynamic Resourcing: Maintain liquid capital reserves to seize infrastructure or talent opportunities instantly.

Table 1. The risk of slow strategic investment cycles in the Age of AI

How is a portfolio strategy formulated? 

Figure 3 shows the six key inputs that provide the strategic, commercial, and technical insight needed to formulate a portfolio and investment strategy. Descriptions and examples for each are provided below.

Organizational Vision – This is the north star that aligns all parts of the organization. It answers the question, “Why do we exist?” For example, Amazon exists “to be Earth’s most customer-centric company.” Netflix exists “to entertain the world.” The organization’s highest-ranking executives craft the organizational vision. It is long-lived, typically only changing after a significant event, such as a new CEO, a merger, a major acquisition, or a business model shift.

The Organizational vision includes the overarching core values, purpose, and mission. Core values are the uncompromising beliefs that serve as a foundation for the organization. The purpose is the long-lasting reason an organization exists. The mission is the compelling, clear, challenging, yet achievable goal that creates energy and focus across the organization. Together, these establish a strong ‘why’ for the company.[2]

Organizational Strategy – Outlines how the company will achieve its mission through its products and services, customers, financial position, people, business model, and partnerships. It is a directed course of action to put a company in a better position to win than its competition or, if a public or non-profit organization, to deliver on its mission. The organizational strategy answers the question, “What will we do to win the market?” For example, a strategy to expand into new markets could be expressed as “increase market share by 3% in targeted emerging markets through strategic partnerships and innovative product offerings.”

Portfolio context – Describes the current state of the portfolio’s products and solutions, the customers and markets they serve, and their performance. This is the baseline for delivering innovations within existing products and solutions, as well as for developing new products and solutions. For example, the portfolio context for a health insurance company would likely be its ecosystem of solutions supporting the sale of insurance products, enrollment of new customers, administration of investment vehicles, account servicing, and claims processing. Among these existing products, their comprehensive health insurance policies are performing poorly as customers seek to save.

Competitive environment – Strategies for developing and evolving products and solutions cannot be formulated in a vacuum. Portfolio leaders answer the question, “What competition do we face?” by conducting competitive analysis to identify the most significant threats to the business and opportunities for growth. For example, a competitive analysis of a financial services company might reveal that a robust in-person agent network creates growth opportunities in suburban communities. Yet, the lack of digital capabilities limits its ability to compete in rural communities.

Financial goals – Whether measured in revenue, profitability, market share, or other metrics, financial goals used to evaluate products are an explicit input to portfolio strategy formulation. Every organization is guided by a defined set of financial targets that answer the question, “How do we measure our performance?” For example, a financial goal might be to “achieve a 10% year-over-year increase in revenue.”

Distinctive competence – Effective strategies naturally leverage the unique advantages that differentiate the organization’s products from competitors’ offerings. The organization’s competitive edge is clarified by answering the question, “What are we better at than anyone else?” Portfolio leaders should consider how the portfolio strategy can leverage competitive strengths while addressing gaps. For instance, a telecom company may have unparalleled expertise in building and maintaining next-generation network infrastructure, but a comparative weakness in customer support capabilities.

How to create a balanced portfolio?

Just as a personal financial portfolio balances investments across asset classes, a SAFe portfolio balances its products and solutions across investment horizons to manage risk and maximize returns (Figure 4). Get the balance wrong, and the Portfolio can starve the future by over-investing in today or miss near-term opportunities by allocating too much to an uncertain future.

 

A balanced portfolio applies the horizon investment model to ensure an appropriate allocation of investments between short-term needs and long-term goals. It involves distributing investments across varying time frames and risk levels while optimizing for both immediate impact and future growth. Understanding horizon thinking is essential for achieving balance in strategic planning.

• Horizon 3: Create Future Options: This horizon aims to future-proof the organization through research and development. It’s for identifying entirely new businesses or disruptive technologies that may or may not prove successful. These initiatives are high-risk but have the potential for high rewards.
• Horizon 2: Grow emerging value: This horizon is for building new, emerging businesses. It involves exploring new markets, expanding product lines, or innovating to respond to market shifts. These investments are intended to generate a reliable return in the medium term.
• Horizon 1: Optimize and extend core: This is the core business. It involves maintaining and extending existing products and services that generate the majority of the company’s revenue. The focus is on improving performance, increasing profitability, and making incremental improvements.
• Horizon 0: Retiring/decommissioning products and solutions: This horizon focuses on retiring or decommissioning obsolete systems, platforms, or technologies. It includes planned, strategic “end-of-life” for solutions that are no longer providing value. The focus is on reducing operating costs and freeing up money and people to work on more valuable initiatives.

AI fundamentally changes the traditional horizon model

AI changes the horizon model in a few specific, structural ways, beyond just “faster analysis.” The most significant changes include:

• Exploration economics collapse. AI enables Horizon 3 probes to be built and validated significantly faster and at a dramatically lower cost. For example, a vibe-coded MVP can be created in days or weeks.
• Horizon transitions compress, creating more pressure on downstream functions. Because build-measure-learn is faster, promising products and solutions move from Horizon 3 to Horizon 2 to Horizon 1 sooner. This creates downstream pressure on sales, marketing, and service that the organization must account for in the overall budget.
• Accelerating the decommissioning of marginally performing H1 products. The consequences of the previous two bullets mean there are new opportunities arriving in Horizon 1 faster than before. This requires freeing up budget by moving marginally performing Horizon 1 products and solutions to Horizon 0 for decommissioning. AI-assisted migration and decommissioning reduce the cost of Horizon 0, accelerating legacy turnover. 

Balancing ambition and risk

A portfolio’s ambition is the boldness of the outcomes it commits to, expressed in the balance between the outcomes it must deliver and those it is willing to pursue but may miss. Its risk profile is the proportion of its budget it allocates to uncertain bets versus proven, near-term returns. 

AI-Native SAFe captures this choice in two terms borrowed from Google’s OKR framework: the Roofshot and the Moonshot. 

• A Roofshot is a conservative pursuit: lower-risk, with highly likely and tangible results. Optimization work fits naturally here.
• A Moonshot is a very ambitious pursuit that aims for an innovative step change. The risk is expected to be high, but the goal is not impossible. The point of a moonshot is to push past small, safe optimizations and revisit how the problem is solved today, in the hope of a 10x breakthrough.

In general, ambition and risk tend to flow in different horizons: 

• H3 products tend to be more Moonshot-focused.
• H2 products balance Moonshots and Roofshot-focused.
• H1 products tend to be more Roofshoot-focused.

It is a mistake to think that Moonshots are only associated with H3 or H2 products. For example: 

• Transforming a profitable H1 solution through innovative AI-Native features may be captured as a Moonshot. 
• Creating future options with a new solution based on a set of mature technologies may not be considered a Moonshot or a Roofshot.
• Some investments are not associated with Moonshots or Roofshots, such as the cost of running core Horizon 1 systems, which must still be accounted for in budgets.

From a portfolio perspective, the goal is to ensure the portfolio invests in outcomes that balance higher-risk innovations and more conservative investments.

How to formulate portfolio outcomes?

Based on the above inputs, organizational and portfolio leaders and stakeholders establish the portfolio strategy and write Portfolio Outcomes. While there is no set way to facilitate these discussions, arriving at these differentiated business objectives often involves an iterative cycle of ideating, refining, and finalizing.  

In AI-Native SAFe Portfolio, outcomes are expressed using OKRs: the ‘Objective’ defines the desired outcome, addressing the ‘What and the Why’. Key Results collectively answer the question, “How will we know we’ve achieved the objective?” They measure both progress towards the outcome and the success conditions for its fulfillment. For each objective, there are typically between two and five key results.

The guidance article “Outcome-Driven Product Development in AI-Native SAFe.” provides the details on crafting well-written Portfolio Outcomes expressed as OKRs and techniques for creating balanced key results, as shown in the example in Table 1 below. 

Portfolio OKR

Achieve a dominant position within the autonomous delivery market KR1: Increase serviceable market from 30% to 75% within 18 months KR2: Increase NPS from 35 to 60 KR3: Improve repeat business rates from 80% to 95%

Table 1: Example Portfolio outcome with a balanced set of key results

What is the influence of portfolio outcomes?

Figure 5, below, shows the AI-Native SAFe Outcome Tree. The outcome tree connects daily work to overall strategy, aligning team activities with portfolio goals. This alignment prevents teams and ARTs from running disconnected experiments, ensuring that each team’s contributions support the larger objectives. 

Portfolios define strategic outcomes that will span one or more years, while teams may define outcomes that can be realized in weeks or even days at the speed of AI. Left disconnected, those outcomes would pull in different directions. Therefore, forming and maintaining those connections is essential as outcomes and evidence evolve. As such, they guide behavior and decision-making throughout the portfolio as shown in Figure 6 and described in more detail below.

• Organizational Monitoring: Portfolio outcomes, aggregated across Portfolios, are used by the organization as evidence that the organization’s strategy is or is not working.
• Cross-Portfolio Alignment: In larger organizations where several portfolios serve a single organizational strategy, the outcomes of different portfolios may need to be reconciled by coordinating roadmaps, exposing dependencies and shared services, and aligning cross-cutting initiatives.
• Informing ART Outcomes: Portfolio outcomes translate the organization’s intent into portfolio-scoped targets that ARTs and teams align their outcomes with. They also shape the degree of ambition an ART should pursue and the level of risk it should accept as it realizes its objective. 
• Provide intent for ARTs and Teams: Portfolio outcomes ensure ARTs understand the context of the work they define and deliver. This clarity fosters stronger alignment and purpose.
• Portfolio Performance: Portfolio outcomes are used by the Portfolio as part of its ongoing governance processes, enabling Portfolio Leaders to provide appropriate support and steering and, ultimately, ensuring continual investment in the ART.

What is a portfolio investment strategy?

A portfolio investment strategy is the approach the portfolio uses to fund a balanced set of investments that convert its desired outcomes into products and solutions that accelerate innovation and deliver sustainable growth. The investment strategy should look to answer three questions:

• How will we allocate the total available Portfolio budget?
• What are our expected returns?
• What are the agreed metrics we will use to track our investments?

Allocating the available portfolio budget

Each Portfolio has a total Portfolio budget determined by organizational-level policies and practices. The goal for the Portfolio is to allocate this effectively to realize outcomes and maximize returns. An example of this approach is shown in Table 2 below. 

It is important to note that this allocation typically covers four categories of funding:

1. Investments in products and solutions
2. Investments in strategic initiatives
3. Foundational operational baseline covering costs such as software, licenses, infrastructure, etc
4. A strategic reserve that serves to fund investments in emergent opportunities 

These categories provide a recommended approach for allocating funding by separating the budget assigned to active strategic initiatives from foundational and more flexible buckets. An example of applying these categories is shown in Table 2. 

Investment [Category]	Classification	Allocation	Description
Next-Gen Mobile App [1]	Horizon 1: Investing (Core Growth)	15.0%	Expanding the features and capabilities of the primary revenue-generating mobile product to capture more market share.
Global Payment Expansion [1]	Horizon 1: Investing (Core Growth)	15.0%	Integrating a new regional payment gateway platform product into existing systems to scale international transactions.
Cybersecurity & Infra Hardening [2]	Horizon 1: Sustaining (Core Operations)	15.0%	Crucial “keep the lights on” strategic initiative to patch technical debt, ensure continuous compliance, and maintain baseline system stability.
Predictive Analytics Rollout [1]	Horizon 2: Emerging (Scaling Innovation)	12.0%	Transitioning a previously validated data prototype into an integrated, organization-wide internal product.
New AI products [1]	Horizon 3: Evaluating (Exploratory / MVPs)	8.0%	Funded H3 explorations include: Secure, air-gapped LLM based on open source models to provide a technical foundation that enables existing products to better leverage AI Common agentic skills for builders Customer service chatbot Developer API helper (sample source code files) Customer appointment scheduling agent Fraud monitoring agent Sales price quoting agent
Mainframe Decommissioning [2]	Horizon 0: Retiring (Decommissioning)	2.0%	Strategic initiative to safely shut down legacy data structures and migrate final workloads to modern cloud infrastructure.
Foundational Operational Baseline [3]	Fixed Costs, Overheads, Shared Infra & Software, etc	23.0%	Non-negotiable organizational running costs, including cloud hosting bills (AWS/Azure), engineering tool licenses (Jira, GitHub), and centralized support overheads.
Strategic Reserve [4]	AI Funding Buffer	10.0%	Liquid capital withheld from initial budgeting to allow Portfolio Leaders to adjust funding mid-year to take advantage of AI breakthroughs and emergent opportunities.
Total		100%

Table 2: A sample portfolio funding 

It is worth noting that Horizon 1 receives 45% of the overall portfolio investment. The portfolio expects Product Managers to allocate a substantial portion of their funding to evolving Horizon 1 products and solutions that are AI-Native. With this approach, the total investment in AI across the portfolio would be expected to range from 30% to 35%, with dedicated Horizong 3 funding at 8%.

The SAFe Strategic Investment Planning event is where stakeholders collaboratively allocate the portfolio budget, resulting in a plan similar to that shown in Table 2. While it is typical to run these on the Portfolio’s strategy investment cycle rather than continuously, Strategic Investment Planning events can be scheduled whenever adjustments are needed to capture opportunities or respond to unexpected market events. 

The shift from fixed IT overheads to variable token economics

Traditional IT budgets were largely fixed overhead. Salaries, infrastructure, agile contracts, and stable software licenses are generally predictable, which is why the cost of an ART across a Planning Interval has been easy to forecast. AI-Native solutions break that assumption. As AI shifts from human-paced query and copilot use to machine-paced, autonomous workflows and agents running at scale, a significant part of the budget becomes variable, driven by the economics of token consumption.

In this model, cost follows real-time usage, and in most AI use cases, this is the token-processing cost. To frame this in traditional terms, we pay a human via a paycheck. We pay an agent in tokens. A single request rarely processes only its visible prompt; it also carries tool use, system instructions, retrieved knowledge, and prior conversation history. That hidden context can turn what appears to be a simple prompt, API call, or workflow into a request that costs tens of thousands to hundreds of thousands of tokens. When multiplied across automated loops that process thousands of work items a day, costs can grow far faster than a fixed budget anticipates.

Providers of token-processing solutions (such as LLMs) introduce a second source of variability. Model prices change, licenses are renegotiated, and providers may deprecate the models a solution depends on, so the same workload can cost more from one quarter to the next without any change in scope. 

Variable costs are also introduced when vendors add AI capabilities to the products and solutions used by an organization, such as Product and Agile Lifecycle Management solutions that provide AI-Native forecasting. 

These shifts change what an ART and portfolio budget must account for. Product Managers and other budget owners should separate fixed costs from variable ones, forecast unit economics such as cost per inference or per transaction, set operating-cost guardrails on token spend rather than on development cost alone, monitor consumption continuously, and manage vendor risk through practices such as multi-model fallbacks.

Defining expected returns and measuring progress

Each product or strategic initiative within the investment strategy must be appropriately governed. To achieve this, there must be clarity around the expected returns, whether that is cost saving or revenue generation, and the metrics that will be used to ensure they are on track to deliver. Fortunately, much of this information is available is captured in the Portfolio outcomes. 

Specifically, well-written Portfolio outcomes will be organized into one of four categories as shown in Table 3 below. This then provides a path to forecasting those returns based on available data and customer and market insights.

Type of Return	OKR Category	Example Objective
Customer Facing – increase revenue and impact	Building Products and Services	Make autonomous delivery the option customers pursue first
	Scaling Growth	Win share in three new metropolitan markets
Internal Facing – decrease costs	Driving Operational Efficiencies	Lower the cost of every delivery while holding service steady
	Improving Quality / Mitigating Risk	Operate safely and within regulations as volume scales

Additionally, the Portfolio outcome example shown below has three associated key results that provide the means to track the investment over time. The progress against these key results will inform decisions on whether to maintain, increase, reduce, or stop investment altogether. It is also worth noting that the ART Outcomes related to this Portfolio Outcome, as shown below, provide additional granular detail for steering, interpreting progress, and decision-making.

Portfolio	Achieve a dominant position within the autonomous delivery market KR1: Increase serviceable market to from 30% 75% within 18 months KR2: Increase NPS from 35 to 60 KR3: Improve repeat business rates from 60% to 80%
ART	Streamline and accelerate the order-to-delivery process KR4: Reduce median order-to-delivery time from 90 to 30 minutes (Portfolio: KR2, KR3) KR5: Achieve 98% on-time, undamaged delivery (KR2, KR3) KR6: Raise the share of orders fulfilled autonomously from 40% to 80% (Portfolio: KR1)

In addition to key results specific to particular initiatives, the Portfolio will often define a set of KPIs to measure the combined impact of its investment strategy. This topic is not covered in this article, but more guidance can be found in the KPIs article.

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References

[1] A.G. Lafley, A.G and Roger L. Martin Playing to Win [1] Harvard Business Review Press, 2013.

[2] Collins, Jim. BE 2.0, Beyond Entrepreneurship 2.0: Turning Your Business into an Enduring Great Company. Portfolio, 2020.