Why Great Products Lose: Using Porter's Five Forces to Build Winning Product Strategy
Learn how competitive forces—not just competitors—shape product strategy, market positioning, pricing power, and long-term success.
Most product managers encounter Porter’s Five Forces as a slide in an onboarding deck, treat it as a relic of business-school case competitions, and quietly file it away as something strategists do rather than something builders use. This is a costly misreading. The framework that Michael Porter introduced in 1979 and substantially reaffirmed three decades later (Porter, 2008) is not a competitor-tracking exercise; it is a discipline for reasoning about where profit pools sit and why they persist. In the context of AI-native products, where the boundaries of an industry are being redrawn faster than most roadmaps can be reprioritized, that discipline matters more, not less. The intent of this piece is threefold: (1) to recover what the five forces actually claim, (2) to show how foundation models and agentic systems perturb each force, and (3) to translate the analysis into product decisions a PM can own.
Why Structure, Not Rivals, Is the Object of Analysis
The first thing extant practice gets wrong is conflating competitive analysis with competitor analysis. Porter’s (2008) central claim is that the long-run profitability of a market is governed by its structure, and that structure is the joint product of five forces: the intensity of rivalry among incumbents, the threat of new entrants, the bargaining power of suppliers, the bargaining power of buyers, and the threat of substitutes. The implication, which is easy to state and hard to internalize, is that you can win every head-to-head feature comparison and still operate in a structurally unattractive market where no participant earns durable returns. A PM who studies only the named competitor on the comparison grid is observing the weather while ignoring the climate.
The reason this lens has survived four decades is that it is mechanistic rather than descriptive. Each force operates through an identifiable channel: suppliers extract value when they are concentrated and switching is costly; buyers extract value when they are concentrated, informed, and price-sensitive; entrants compress margins when barriers are low; substitutes cap pricing power by offering a different way to accomplish the same job. Owing to this mechanistic character, the framework is portable across technological regimes, which is precisely why it can be re-run against the AI transition rather than discarded by it.
Competitive Intensity: When Differentiation Half-Life Collapses
Rivalry intensifies when competitors are numerous and similar, when growth slows, when exit barriers are high, and when products are perceived as undifferentiated. The defining structural shift in AI-enabled categories is that the half-life of feature differentiation has collapsed. When a capability is one prompt-engineering pattern or one model upgrade away from being replicated, the period during which a feature confers advantage shrinks from years to weeks. The 2023–2024 wave of “AI writing assistants,” in which dozens of products converged on near-identical summarize-rewrite-expand functionality within a single product cycle, is a clean illustration of rivalry escalating because differentiation evaporated.
The strategic implication for the PM is that, in the context of AI features, defensibility cannot reside in the feature itself. It must reside in something the rivalry cannot quickly copy: a proprietary feedback loop that tunes the model on usage no competitor can observe, a workflow the product owns end-to-end, or switching costs accrued through accumulated user context. The discipline here is to ask, before committing a quarter to an AI capability, not “can we build this” but “how long until parity, and what compounding asset accrues to us during that window.” Intensity is not a reason to avoid the build; it is a reason to design the build so that shipping it deposits something durable.
Supplier and Customer Power: The New Asymmetry of the Model Layer
The supplier force has been reshaped more dramatically by foundation models than any other. For the cohort of products that wrap a third-party model, the model provider is a supplier of unusual concentration and pricing latitude. When a small number of frontier labs supply the core intelligence on which your value proposition rests, you have, in Porter’s terms, accepted a concentrated supplier whose pricing, rate limits, deprecation schedules, and terms of service propagate directly into your unit economics and your roadmap. Products that discovered their margins inverting after a provider repriced tokens learned this the structural way. The mitigation is not to avoid the suppliers, which would be self-defeating, but to reduce dependence through model abstraction layers, multi-provider routing, and the cultivation of proprietary data that makes smaller or fine-tuned models viable substitutes for frontier capability on the workloads that matter.
Buyer power, meanwhile, has risen in a subtler way. Because generative tools lower the cost of evaluation and even of in-house construction, sophisticated enterprise buyers increasingly treat “build it ourselves with an API” as a credible alternative to purchasing. This is buyer power expressed as a substitution threat from the demand side. The product response is to widen the gap between what a buyer can assemble from raw components and what your product delivers as an integrated, governed, supported system, since the value that survives this comparison is the value buyers cannot cheaply reconstruct.
Substitutes: The Force Most PMs Underweight
Substitutes are the most underestimated force because they originate outside the industry’s competitive set and therefore outside the PM’s habitual field of view. A substitute is not a rival product; it is a different means of accomplishing the customer’s job. The cautionary cases are well known: incumbents in photography, navigation, and travel agencies were displaced not by stronger versions of themselves but by general-purpose platforms that absorbed the job entirely. In the present moment, the most consequential substitute for a large class of single-purpose software is a general-purpose agentic assistant that can perform the underlying task without the specialized interface. When a knowledge worker can instruct an agent to draft, schedule, reconcile, or summarize, the question every PM should sit with is uncomfortable but clarifying: what is the job my product does, and can a sufficiently capable agent now do that job through a different surface. Naming the substitute early is the precondition for designing against it.
Translating the Forces Into Product Decisions
The strategic implications of the framework become actionable when the PM converts each force into a recurring question attached to roadmap and positioning decisions. Rivalry asks what compounding asset a feature deposits before parity arrives. Supplier power asks how exposed the cost structure and roadmap are to upstream providers and what reduces that exposure. Buyer power asks what value survives the buyer’s build-versus-buy comparison. The threat of entrants asks what barrier the product is raising over time, whether through data, integrations, or switching costs, given that AI has lowered conventional barriers such as capital and engineering scarcity. The threat of substitutes asks what job is being done and whether a general-purpose system can now absorb it.
It is worth stating the framework’s limits with the same care as its strengths, since extant critique is fair on this point. The five forces assume relatively stable industry boundaries and underweight the role of complementors, partnerships, and ecosystems, which is exactly where much AI-era value now forms. The pragmatic posture, therefore, is to treat Porter’s model as the analysis of the profit pool’s structure and to pair it with the ecosystem and platform lenses developed in later modules, which address the cooperative dynamics the five forces omit. Used this way, the framework remains what it has always been for the product leader who reads it correctly: not a verdict on who wins the next feature war, but a map of where durable value can accumulate and where it cannot.
References
Andreessen Horowitz. (2024). Who owns the generative AI platform? https://a16z.com/who-owns-the-generative-ai-platform/
Porter, M. E. (2008). The five competitive forces that shape strategy. Harvard Business Review, 86(1), 78–93. https://hbr.org/2008/01/the-five-competitive-forces-that-shape-strategy
Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. Free Press.