The technology with the strongest specification does not automatically become the technology around which customers, suppliers, skills and capital organise.
Executive teams often evaluate competing technologies as though adoption were an engineering contest. Performance, efficiency and technical capability are scored, a preferred option emerges, and the organisation assumes the market or enterprise will follow.
That assumption is dangerous when a technology depends on an ecosystem. Platforms, industrial equipment, AI tools, energy systems and enterprise software succeed not only because they work, but because investors fund them, operators learn them, suppliers support them, standards accommodate them, customers trust them and regulators permit them.
A 2017 study by van de Kaa, Kamp and Rezaei examined competition among biomass combustion, gasification and pyrolysis technologies in the Netherlands. The historical result was that gasification ranked highest in their model and technological superiority received the highest weight. More important for strategic leaders, however, is the structure of the model itself. The researchers identified twelve relevant factors spanning financial strength, operational capability, learning, technical performance, compatibility, flexibility, pricing, distribution, installed base, regulation, development-process effectiveness and stakeholder networks.
That list reframes technology selection from a product comparison into an adoption-system decision.
The Strategic Context
Technology investments increasingly create path dependence. Once an organisation commits to a platform, it builds skills, interfaces, data structures, supplier arrangements, governance and operating routines around it. Switching later can be expensive even when a technically better alternative appears.
This makes early selection consequential. The apparent question is, "Which technology is best?" The real question is, "Which technology can create a viable and defensible operating ecosystem under the conditions we face?"
The van de Kaa study applies the literature on standards battles to biomass conversion. It groups relevant influences into characteristics of the technology supporter, characteristics of the technology itself, support strategy and other stakeholders. That structure matters because adoption is partly technical, partly commercial and partly institutional.
The paper was based on a small expert set and a specific Dutch market in 2017. Its ranking should therefore remain historical. Yet the conceptual architecture travels well.
A technically superior industrial automation platform can fail if integrators do not support it. An AI product can underperform if staff cannot adopt it into workflow. A defence technology can be strategically weak if supply, interoperability or sovereign support is insufficient. A software platform can win despite weaker individual features because it has a large installed base and deep partner network.
What Leaders Commonly Misread
The first error is to treat technical merit as a sufficient condition for adoption. It is usually necessary, but not sufficient.
The second error is to assess the technology and ignore the strength of the organisations behind it. Financial resilience, service capability and learning capacity matter because enterprise technologies live for years. A buyer is exposed not only to product failure but to supplier failure, support withdrawal and capability stagnation.
The third error is to ignore compatibility. A technology that requires a complete replacement of existing interfaces, tools and skills faces a different adoption hurdle from one that can enter incrementally.
The fourth error is to treat installed base as historical noise. Installed base creates skills, spare parts, reference customers, complementary products and perceived safety. This can make an incumbent difficult to displace even when a challenger offers superior technical performance.
The fifth error is to assume the organisation is selecting a technology when it is actually selecting a transition path. The preferred future platform may be correct, while immediate full migration is not.
Related article: Technology Is a Means, Not a Strategy
Reframing the Issue
Technology selection should be reframed as an ecosystem viability test.
The technology itself is only one layer. Around it sit:
Sponsor strength → operating capability → compatibility → economics → installed base → partner network → regulatory position → learning velocity
Each layer can accelerate or block adoption.
This explains why some technologies remain technically impressive but commercially marginal. It also explains why organisations sometimes choose an apparently less advanced solution. They may be optimising for execution certainty, integration risk, supplier depth or transition cost rather than laboratory performance.
This is not an argument for choosing incumbents by default. It is an argument for making the full adoption logic visible.
Strategic Analysis: Compete on the Adoption System
Technology supporters are part of the product
For long-life assets and platforms, the supplier's financial and operational capacity becomes part of the risk profile. Leaders should examine whether the sponsor can maintain development, service installations, attract partners and respond to failures over the expected investment horizon.
This matters especially in emerging markets where a technically strong vendor may depend on continued financing or a narrow customer base.
Compatibility changes time to value
Compatibility can be technical, organisational or regulatory. A new platform may interface with existing equipment but require a completely new operating model. Another may fit workflow but create data-governance challenges.
The adoption case should therefore quantify what must change around the technology, not just within it.
A useful distinction is between core capability and ecosystem conversion cost. The best core capability can be outweighed by the cost, delay and risk of converting the surrounding system.
Learning orientation determines future competitiveness
The van de Kaa framework includes learning orientation because technologies evolve. A buyer is not only purchasing today's performance. It is betting on the rate at which the ecosystem will solve problems, reduce cost and accumulate operating knowledge.
This creates a portfolio question. Sometimes an enterprise should fund a smaller pilot in an emerging technology specifically to build learning and preserve future option value, even when the incumbent remains the short-term production choice.
Regulation can create or destroy market viability
The regulator appears as a factor because adoption is institutional. Standards, permitting, incentives, safety requirements and market rules can shift the economics rapidly.
Executives should therefore treat regulatory architecture as a strategic scenario variable rather than a compliance footnote.
Networks create positive feedback
An installed base attracts suppliers and skills. More suppliers reduce adoption risk. Lower risk attracts customers. More customers enlarge the installed base. Technology competition can therefore contain reinforcing loops.
This means timing matters. Once a market tips strongly towards one ecosystem, a technically superior challenger may require a materially better value proposition to overcome switching costs.
Related article: Innovation Capacity Is an Ecosystem, Not an R&D Budget
Decision Framework
A practical technology-adoption screen should evaluate eight dimensions.
1. Strategic fit. Does the technology support the operating model and capabilities the organisation intends to build?
2. Technical superiority. Is the performance advantage material in the actual use case rather than only under ideal conditions?
3. Compatibility. What existing assets, data, standards, skills and interfaces must change?
4. Sponsor strength. Can the vendor or supporting consortium sustain development, service and investment?
5. Ecosystem depth. Are integrators, suppliers, complementary products, training and talent available?
6. Economic transition. What is the full cost of migration, including downtime, parallel systems and capability development?
7. Institutional position. How exposed is the technology to regulatory, standards or policy change?
8. Learning trajectory. Is the ecosystem improving rapidly enough to strengthen the investment over time?
The output should not be a single static score. It should show which assumptions must remain true for the preferred option to succeed.
From Strategy to Execution
Immediate action is to expand technology due diligence beyond specification sheets. Map dependencies, supplier depth, installed base, compatibility and regulatory assumptions.
Medium-term capability building should create controlled experiments. Pilots are useful when they test adoption conditions, not merely technical function. Measure integration effort, workforce learning, support responsiveness and operating reliability.
Long-term strategic positioning requires portfolio thinking. Mature technology may carry the production load while emerging options are funded as learning investments. The organisation can preserve optionality without betting the enterprise on an immature ecosystem.
Governance should also identify exit conditions. If the vendor loses financial support, interoperability deteriorates or critical regulation changes, the technology thesis may need to be revisited.
Signals to Monitor
Monitor growth in installed base, partner participation, implementation lead times, talent availability, vendor financial resilience, standardisation progress, regulatory treatment and the cost of complementary components.
A particularly important signal is whether customers are adopting despite technical imperfections. That can indicate ecosystem momentum. Conversely, repeated technically successful pilots with weak commercial uptake may reveal an adoption barrier outside the technology itself.
Questions for the Leadership Team
- Which part of our preferred technology case depends on technical performance, and which part depends on ecosystem formation?
- What must we replace, retrain or renegotiate to make the technology operational?
- How dependent are we on one vendor's financial strength or intellectual property?
- Are we underestimating the strategic value of installed base and compatibility?
- What learning investment should we make now to preserve future options?
- Which regulatory or standards change could invalidate the adoption case?
Closing Perspective
Technical superiority matters. The 2017 biomass study itself ranked it as the strongest factor in its context. But technology becomes strategically valuable only when an organisation can finance, integrate, operate, support and scale it.
The leadership task is therefore broader than choosing the best technology. It is choosing, and sometimes helping to build, the ecosystem most capable of turning technical potential into sustained enterprise value.
Source References
- van de Kaa, G., Kamp, L. & Rezaei, J. (2017). Selection of biomass thermochemical conversion technology in the Netherlands: A best worst method approach. Journal of Cleaner Production, 166, 32–39.
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