Lilla Hortoványi

Strategy Without Templates

Adaptation in Digital Environments

2.1 Why Stable-Context Environmental Theory Becomes Insufficient

To understand why the stable-context assumption is weakening, it is necessary to revisit the historical foundations of strategic thought. Classical frameworks such as Porter’s industry analysis, contingency theory, and the resource-based view emerged in settings where the environment could reasonably be treated as a relatively durable and analyzable domain (Porter, 1980; Lawrence & Lorsch, 1967; Barney, 1991). Even when these traditions acknowledged uncertainty or complexity, they generally preserved the assumption that the relevant environment existed as an external object that firms could analyze and respond to.

This stable-context logic carries four strong assumptions.

It assumes externality. The environment is outside the firm and confronts it as a domain that can be assessed prior to action.
It assumes transparency. The relevant conditions of action can be read, mapped, and interpreted with sufficient clarity to support strategic reasoning.
It assumes separability. The environment and the firm may influence one another, but they remain analytically distinct enough for strategic fit to remain meaningful.
It assumes some form of equilibrium or at least temporary stability. Even when change occurs, the environment is expected to stabilize long enough for learning, planning, and adaptation to take effect.

These four assumptions, however, do not operate independently. They form an interdependent theoretical system grounded in a deeper ontological premise: that the environment functions as a stable referential structure. This premise implies not merely that environments change slowly, but that they retain sufficient structural integrity to serve as an object of knowledge that can be analyzed prior to action. The environment, in this sense, is not just “out there” – it is epistemically usable.

The environment serves as a reference point through three underlying epistemic mechanisms.

Categorical stability: the environment provides durable categories (e.g., industries, competitors, markets) that remain meaningful across time and actors.
Causal transparency: the relationship between action and outcome is sufficiently stable for learning to accumulate.
Comparative validity: firms can benchmark performance because they operate under structurally comparable conditions.

When these mechanisms hold, the four assumptions reinforce one another. Externality enables analysis because the environment can be treated as independent of firm action. Transparency enables interpretation because signals can be interpreted consistently over time. Separability enables the logic of fit because firm and environment can be analytically distinguished, even if they interact. Equilibrium enables planning because the environment remains stable long enough for designed action to unfold.

These assumptions are increasingly difficult to maintain in digital ecologies. The problem is not that earlier theories were mistaken. Rather, they were developed under structural conditions that are no longer generalizable. In digitally mediated settings, environmental change is not always external to the firm, signals cannot always be interpreted consistently over time, environmental structure is not always separable from interaction, and environmental dynamics do not necessarily converge toward equilibrium.

Crucially, these shifts do not occur in isolation. They emerge together and reinforce one another. Platform architectures make the environment partially shaped by firm actions, undermining externality. Algorithmic mediation obscures causal relationships, undermining transparency. Ecosystem interdependence generates feedback loops, undermining separability. Continuous reconfiguration prevents stabilization, undermining equilibrium. Each shift amplifies the others. As the environment becomes increasingly shaped by firm actions, consistent interpretation becomes harder. As causal relationships become opaque, analytical separation becomes more difficult to sustain. As feedback intensifies, equilibrium becomes structurally unattainable.

This systemic shift explains why incremental extensions of classical theory are insufficient. Attempts to preserve individual assumptions – such as maintaining equilibrium through “dynamic stability” in dynamic capabilities frameworks (Teece, 2007) – cannot address the collapse of the underlying referential structure. The environment ceases to function as a stable object of strategic knowledge.

This insufficiency becomes especially visible when strategy is framed as fit. The metaphor of fit presumes that firms can align themselves with an environment whose relevant features can be identified. Yet fit becomes problematic when the object of fit itself is moving, continuously altered through interaction, or only partially observable. The issue is no longer only whether the firm correctly interprets the environment, but whether the environment itself remains sufficiently stable and external to support that kind of interpretation.

For that reason, the relevant distinction is not simply between stable and dynamic environments. A more important distinction is between environments characterized primarily by informational uncertainty and those characterized by structural uncertainty. Informational uncertainty exists when structure remains intact, but actors lack complete knowledge. Structural uncertainty exists when the structure itself is unstable, continuously modified, or only partially accessible. Better information can reduce informational uncertainty, but it cannot resolve structural uncertainty when the environment itself is being reorganized through action.

Tartalomjegyzék

Kiadó: Akadémiai Kiadó

Online megjelenés éve: 2026

ISBN: 978 963 664 204 4

Gazdaság

What happens when understanding comes only after action has already begun?

Traditional strategy rests on the assumption that organizations can understand their environment before deciding how to act. Yet the conditions that once allowed organizations to rely on benchmarking, best practices, and proven strategic templates can no longer be taken for granted. Today, organizations increasingly face situations for which no clear roadmap exists. Established assumptions become less reliable, familiar reference points lose their clarity, and strategic decisions must be made before their consequences can be fully understood.

Strategy Without Templates explores how organizations learn, adapt, and navigate environments in which uncertainty is pervasive and established templates are absent or no longer sufficient. Instead of treating strategy as a process of prediction and planning, the book explores how strategic paths take shape through action, experimentation, adjustment, and learning.

A central insight in the book is that temporary solutions are often necessary. What begins as a practical response to an immediate challenge may gradually shape future possibilities in unexpected ways. Some solutions create new opportunities and sources of advantage. Others become constraints that are difficult to overcome.

Hivatkozás: https://mersz.hu/hortovanyi-strategy-without-templates//

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