Article
July 7, 2026
Google, Product Manager, Pixel Phones
Member
Companies like Apple, Samsung, and Sony have built some of the most valuable and enduring global businesses on the back of consumer hardware. Others, like Amazon, Google, Microsoft, and Meta, use hardware as a gateway into their broader ecosystems where value is captured well beyond the devices themselves.
And yet, Silicon Valley continues to produce wave after wave of ambitious hardware startups that struggle to scale into large, independent companies. We have seen this across categories, from smart home devices and wearables to the latest generation of AI-native gadgets. Many show early promise. Some, like GoPro, build strong early momentum, while others, like Ring and Nest, even define new categories. Over time, however, the market outcomes begin to converge. Startups and smaller players either get absorbed by larger companies, or remain confined to niche market segments, or they eventually run out of capital and collapse.
In my experience as a product leader in the consumer hardware industry, I have often seen these outcomes explained as failures of execution. Hardware is hard, startups make mistakes, or the timing was wrong. That explanation is incomplete.
The exact forces that make consumer hardware enormously valuable also make it extraordinarily difficult for smaller players to capture that value independently. The industry often assumes that, similar to software, a hardware product with real user traction can eventually scale into a large standalone business. That assumption overlooks the structural dynamics of the consumer hardware industry.
Building a lasting consumer hardware business requires understanding and navigating constraints across four dimensions: product innovation, economics, customer adoption, and distribution.
Many hardware startups and smaller companies begin with a compelling product idea that feels novel and appealing to their target users. However, they quickly run into a fundamental constraint: the more they innovate, the more difficult the product becomes to build and scale.
Unlike software, innovation in hardware carries physical consequences. A new architecture with custom components or specialized sensors can unlock meaningful differentiation and improve the user experience. But it can also introduce scaling challenges like higher compute requirements, supply chain dependencies, manufacturing complexity, new quality and reliability risks, and the need for more specialized engineering resources. These choices compound quickly. For example, engineering challenges often translate into yield issues, meaning fewer units pass the quality bar. Lower yield drives cost. Cost constrains pricing and volume. What begins as a product advantage can turn into a scaling bottleneck.
Conversely, using off-the-shelf components simplifies development and reduces execution risk. It also makes the product easier to replicate, weakening its competitive advantage. Entrenched incumbents can move quickly because they already have strong manufacturing and distribution capabilities, and their ecosystem reach gives them access to customers that smaller players are still trying to earn.
This dynamic creates a persistent tradeoff. The more differentiated the product is, the harder it can become to scale. The simpler the product is, the easier it becomes for others to copy. For smaller hardware players, winning the product means building something new that can also survive the realities of scale.
In software, pricing is a strategic lever. Companies can introduce freemium plans to attract users in the short term and monetize later. In hardware, economics is a structural constraint.
Hardware startups often anchor their financial models on the core Bill of Materials (BOM) cost. In my experience, that view is far too narrow. The real cost of a hardware product goes well beyond the parts inside the device:
Unless the product justifies a subscription model, hardware typically creates a one-time revenue event, while many of these costs persist throughout the product lifecycle. Customer support, software upgrades, returns, repairs, and warranty obligations continue well after the initial sale. Product leaders need to account for that lifecycle cost burden early, because a seemingly profitable margin can become unattractive once the full cost to serve is included.
Established incumbents benefit from economies of scale in ways that are difficult for smaller players to match. Larger volumes lead to better component pricing and stronger supplier leverage, especially during component shortages or capacity constraints. Fixed costs are amortized across millions of units and multiple product generations. Scale also gives incumbents the confidence and capital to make deeper investments that improve product quality and manufacturing processes while lowering costs over time. This includes investing in costly new technologies, custom components, advanced tooling, and manufacturing automation that smaller players may struggle to justify.
Smaller players face the opposite dynamic. Until they reach critical production volume, their unit costs are higher than those of established incumbents, largely because their fixed costs are spread across a much lower volume. At the same time, they often lack the capital to make the upfront investments that would improve efficiency and reduce costs. This challenge becomes even harder to manage with AI devices. Unless cloud model inference and external API access costs are managed through usage limits or metered pricing, higher engagement can increase these recurring expenses and steadily erode margins.
Sustaining this pressure requires either significant sales volume or deep capital reserves to survive long periods of unprofitability. Most smaller players have neither.
In software, users can try a product before they trust it. In hardware, trust takes time to build. There are no free trials. Every purchase requires upfront commitment and confidence that the product will work over time. Even the smallest issues during first use can lead to returns. Once that happens, trust in the product and the brand is hard to recover.
Trust and brand are closely linked. In hardware, trust is built slowly through consistent and reliable product performance, along with the company’s ability to support the customer long after purchase. Over time, that trust translates to brand equity. Incumbents operating in the market for years carry a brand equity advantage that cannot be replicated quickly.
Brand carries immense weight because the cost of making a wrong decision is high for users. A customer buying a new device is taking a bet that goes beyond the feature set. They need to believe the product will last without issues, and that if something breaks, the company will support them. Newer hardware companies enter the market without this foundation. They are asking customers to take a massive leap of faith without the benefit of time.
A second force simultaneously works against adoption. Users do not adopt devices; they adopt habits. Habits remain incredibly difficult to change, especially when the existing solution works well. Most new devices are rarely competing with another company. They are competing with the smartphone, which continues to absorb new capabilities and remains the default interface for everyday tasks.
The walled gardens of ecosystems reinforce this behavioral friction. Users evaluate devices in the context of what they already own. A customer using an iPhone, Apple Watch, iPad, AirPods, and MacBook is not choosing a new device in isolation. They are deciding whether to step outside a system that already works seamlessly together. This creates a high bar for adoption. For a user to switch, a new product must offer a massive leap in utility or integrate seamlessly into the existing ecosystem.
For smaller hardware companies, these forces compound rapidly. Product leaders have to build trust before the company has history. They also have to make behavior change feel worth it, even when existing ecosystems are designed to keep users where they are. When that does not happen, adoption slows and scale becomes harder to achieve. The structural advantage remains with incumbents.
Discussions of distribution often focus on retail shelf space. In hardware, distribution entails much more than the point of sale.
Smaller players have to compete with incumbent giants across both physical and online channels. In retail, they are fighting for limited shelf space that incumbents already occupy. Online, the fight shifts to visibility and the fast delivery promise that has become table stakes for customers. Both paths carry significant channel costs that incumbents can absorb more easily than smaller players.
Distribution also requires precise execution behind the scenes. Companies must forecast demand accurately, build and store sufficient inventory across distribution centers, and ensure products reach channels and customers on time. That means aligning the global supply chain and manufacturing plan with inventory targets that reflect actual consumer demand.
The margin for error is small. Over-forecasting leads to excess inventory and high carrying costs, a structural trap that has forced companies like Peloton to pause production. Under-forecasting results in stockouts, leading to lost revenue and missed momentum at critical moments.
The challenge does not end at delivery. What follows is just as important: customer support, returns, repairs, replacements, and warranty handling. A hardware company must distribute both its product and its ability to support it at scale. This requires a robust reverse logistics infrastructure, including call centers, service centers, spare parts logistics, and trained technicians.
This requirement becomes even more critical in cost-conscious markets, where serviceability is a baseline expectation. Consumers want easy access to repairs that are both affordable and fast. Without this infrastructure, trust is harder to establish, slowing adoption. Large companies build these capabilities into their operating system over time. New players have to build them from scratch while trying to scale.
For product leaders, these are not downstream operational details to revisit later. They directly shape the customer experience, which makes them critical to the product and the brand.
When constraints across product, economics, customer adoption, and distribution begin to compound, the outcome is rarely a sudden failure. Instead, smaller hardware players tend to converge toward a limited set of outcomes. I call this pattern the Structural Convergence Effect.
This effect exists because the consumer hardware industry does not reward product strength alone. As companies grow, they also have to compete against incumbents with deeper scale advantages, ecosystem lock-in, brand trust, and more mature operating infrastructure. Those advantages narrow the strategic room available to smaller players.
Over time, these pressures tend to push smaller hardware companies toward one of three broad outcomes:
Some companies delay this convergence through strong product-market fit and brand momentum. However, as they scale and incumbents enter the category, the same structural constraints begin to apply. Companies like Oura Health are already facing pressure from ecosystem-driven incumbents like Samsung.
This pattern is not necessarily a failure of ambition or execution. It is what happens when a fledgling hardware company runs into the structural realities of the consumer hardware industry.
In my experience, the structural forces that drive this convergence can make or break a new product or company. Product leaders need to account for these forces from the moment they define the product, because they shape the business model and the realistic paths to success.
Consumer hardware will continue to create immense value and some of the most valuable companies in the world. For product leaders at hardware startups or smaller companies, the challenge is recognizing that a great product is only part of the equation. The path to scale is shaped by the structure of the industry itself.
The same forces that make hardware enormously valuable also make it difficult for smaller companies to capture that value independently. Hardware product leaders need to recognize these structural realities early and position their product accordingly. From there, the work is to build the capabilities required to scale while remaining flexible enough to adapt the strategy as new evidence emerges.
Success can take different forms: scaling independently, becoming part of a larger ecosystem, or building a durable position within a focused market. The task is to understand which path remains viable and adapt before the market makes that decision for you.
Disclaimer: The views and opinions expressed in this article are purely the author’s and do not necessarily reflect the official policy or position of Google or its affiliates.
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Akash Rathi is a Product Manager at Google, leading product strategy for Pixel phones at the intersection of AI and consumer hardware. He has led multi-billion dollar consumer tech products from concept through global commercialization, with his products receiving world-wide media acclaim. Akash holds an MBA from The Wharton School and a master’s degree in Industrial Engineering & Operations Research from UC Berkeley.
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