Introduction

Strategy can be understood as a disciplined simplification of reality that enables people to act in a coordinated, collective manner. In a complex world overflowing with information and interdependence, neither individuals nor organizations can attend to every detail or react to every contingency. Instead, they construct simplified representations of the world – mental models, frameworks, and narratives – that capture what they deem most relevant while filtering out extraneous complexity. This paper develops a framework for strategy as such a simplification process, rooted in cognitive science (how humans simplify reality to decide and act), systems theory (how simplification delineates units and relationships in complex systems), and organizational strategy (how shared simplifications guide collective action). We formalize five fundamental “primitives” of strategic simplification – Units, Relations, Priorities, Commitments, and Loops. We also introduce the concept of event boundaries as the points where people and organizations detect significant change, prompting updates to their simplified models. Finally, we argue that effective strategy is not a static plan but a living sensemaking loop that continuously adapts shared simplifications in real time.

Simplification at the Individual Level: Cognitive Foundations

Human cognition evolved to handle a torrent of sensory input and complexity by simplifying reality. Psychologists have long noted that the mind constructs “small-scale models” of reality to understand and anticipate events. Rather than representing every detail of the world, our mental models contain “only selected concepts, and relationships between them” that stand in for the real system. As system dynamics pioneer Jay Forrester observed, “Nobody in his head imagines all the world… He has only selected concepts, and relationships between them, and uses those to represent the real system.” This selective modeling is not a flaw but a necessity: the brain has finite processing capacity and memory. Classic research on bounded rationality by Herbert Simon showed that the “world you perceive is a drastically simplified model of the real world.” In decision-making, “administrative man” (as opposed to the unrealistically omniscient “economic man”) “makes his choices using a simple picture of the situation that takes into account just a few of the factors that he regards as most relevant and crucial.” In other words, individuals satisfice rather than optimize, using simplifications to focus on manageable aspects of a complex reality.

This cognitive simplification is evident in everyday life. We form categories and chunks: for example, a driver perceives a moving car as a single unit (not as thousands of components) and notices only the cars and road features relevant for navigation. We rely on schema and heuristics – mental shortcuts that ignore most details – to make quick decisions under uncertainty. The mind’s limited working memory further forces us to abstract and group information. Our perceptions are filtered by selective attention: a mental model “is an information filter that causes selective perception, [so that we perceive] only selected parts of information.” For instance, when engaged in a goal, we screen out irrelevant stimuli (one might not notice background chatter when focused on a task). In fact, research suggests that of the enormous volume of sensory data we receive (on the order of millions of bits per second), only a tiny fraction (perhaps tens of bits) reaches conscious awareness. The rest is pruned by unconscious filtering. This exemplifies how discipline – a guided focus on what matters – is integral to cognitive simplification. Rather than random ignorance, effective simplification is structured: our brains drop details systematically, keeping what seems relevant for our purposes and discarding what seems negligible.

Crucially, simplification does not imply inaccuracy so much as abstraction. Mental models strive to capture the structure of a situation without its full complexity. Johnson-Laird’s theory of mental models, for example, argues that these internal representations are like scale models or diagrams: they are analogous in structure to the situations they represent. By preserving key relationships in simplified form, we can reason and plan without being bogged down by irrelevant minutiae. Of course, any given simplification can lead to blind spots or biases – a model may omit factors that later prove critical. Cognitive biases (like confirmation bias or overconfidence) often stem from clinging too rigidly to a simplified schema. Nonetheless, the alternative to simplification is not viable: as Simon noted, “the capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems… in the real world.” Perfect, logically omniscient rationality is beyond human reach. Thus, humans satisfice, constructing a workable simplified model of the world and making “good enough” decisions within its bounds. The art of judgment lies in simplifying reality in ways that are useful – discarding noise while retaining signal.

In sum, individual action is enabled by cognitive strategies of simplification: selecting units of attention (concepts, objects), understanding relations among those units (cause-effect links, spatial or temporal patterns), focusing on priorities (goals, needs, salient cues), and committing to choices (deciding on a course of action) rather than endlessly deliberating. These cognitive primitives (units, relations, priorities, commitments) form an initial sketch of the framework we will formalize. Additionally, individuals operate in loops of perception and action – continually sensing feedback and updating their mental models. Before turning to those concepts in detail, we will see how similar principles manifest at the collective level: how groups and organizations form shared simplified models to enable coordinated behavior.

Shared Mental Models and Organizational Simplification

What one mind does through a mental model, a group of people must do through a shared mental model or collective framework. Organizations – whether they are companies, teams, or entire societies – face even greater complexity than individuals, and thus rely on shared simplifications to align understanding and action. A classic insight in organizational behavior is that organizations are fundamentally sensemaking and learning systems. People in organizations jointly construct an understanding of “what is going on” and “what we should do” by communicating and refining shared assumptions. Peter Senge, in The Fifth Discipline, famously identified “mental models” as one of the core disciplines of a learning organization. He defines mental models as “deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action.”. In an organizational context, these shared mental models might include beliefs about the market (“our customers are price-sensitive” or “technology X is the future”), about the organization’s capabilities (“we are an innovative company” or “we are efficient but not creative”), and about cause-effect relationships in their business environment (“if we cut prices, we’ll gain market share”). Such collectively held simplifications allow different individuals to coordinate their decisions because they are “on the same page” about what matters.

Research on team cognition shows that shared mental models improve group performance, especially in high-stakes or complex tasks. When team members have a common understanding of their situation and goals, they can anticipate each other’s actions and fill in gaps smoothly. Shared mental models enable a “common understanding of aims, strategies, and expected behaviors, ultimately enhancing coordination”. For example, in an emergency response team, a shared model of the standard operating procedure (what each role should do, what cues indicate danger) lets members act rapidly and in unison without needing explicit instructions for every step. In business organizations, a shared strategic mental model might mean that employees across departments understand the company’s priorities and approach – say, they all know that “customer service comes first” and thus can take initiative in their own roles to uphold that priority.

One way to think of an organization’s shared mental model is as its dominant logic or collective mindset. C.K. Prahalad and Richard Bettis introduced the concept of a dominant logic to describe the common cognitive map shared by top managers about how the business works. They noted that in successful firms, the dominant logic guides critical resource allocation and problem-solving, serving as a “shared cognitive map and strategic mindset of the top management team or the dominant coalition.” This dominant logic is essentially a simplification of the complex environment – highlighting certain variables (customers, core competencies, key performance metrics) and relationships (such as how product quality affects customer loyalty, or how market share leads to economies of scale) that management believes are crucial for success. While a strong dominant logic can align decision-making and create powerful focus, it can also become a blind spot if the environment shifts and the logic is not updated. Indeed, Prahalad and Bettis warned that a dominant logic can turn into a liability if managers cling to an outdated simplified model when facing a novel situation.

Organizations also embody shared simplifications in their culture and routines. Edgar Schein’s work on organizational culture, for instance, describes culture as a set of shared basic assumptions learned by a group as it solved problems of external adaptation and internal integration. These assumptions are taken for granted over time because they worked, and they amount to a simplified worldview that new members are taught as “the correct way to perceive, think, and feel” in the organization. In daily operations, companies use standard operating procedures and checklists that simplify decision-making for members – by design, they remove the need to consider a vast array of possibilities, focusing attention on a bounded set of actions. In effect, procedures and rules are codified simplifications that ensure everyone approaches recurring situations similarly.

From a systems perspective, we can say that organizations define a system boundary and an environment as part of their simplification. According to general systems theory, any system can be understood as a set of elements interacting to achieve some purpose. An organization chooses what elements (units) to pay attention to and what relationships to monitor, effectively carving an abstract system out of the complex reality. For example, a company might define its competitive environment narrowly as “our industry and direct competitors” and monitor only those, ignoring distant industries – that is a simplification that makes strategy tractable. Similarly, strategic planning often involves analyzing a SWOT (Strengths, Weaknesses, Opportunities, Threats) matrix – a technique that simplifies the world into four categories and a limited list of factors in each. This discipline in focusing on a handful of key internal strengths/weaknesses and external opportunities/threats is what allows an organization to formulate a clear strategy rather than being paralyzed by complexity.

It is important to note that disciplined simplification at the organizational level is often deliberate and negotiated. Unlike individual simplification, which happens largely in our subconscious filtering and intuitive judgments, organizational simplification is frequently explicit. Strategic decisions are made via discussions, meetings, and documents where different perspectives collide and a common, simplified story is crafted. Karl Weick describes strategy formation as an ongoing sensemaking process in which people collectively interpret ambiguous signals and events. In this view, strategy is essentially an organized way of making sense of the world together. Managers articulate visions and models (e.g., “We will think of our business as a platform connecting users, not just as a product seller”) that help others reframe their understanding. Gioia and Chittipeddi (1991) introduced the tandem notions of sensemaking and sensegiving in strategic change: leaders first make sense of a change for themselves, then give sense to others by communicating a simplified narrative that others can align with.

Finally, organizations must balance simplification with requisite complexity. There is a principle in cybernetics, Ashby’s Law of Requisite Variety, which states that to effectively control or respond to a complex environment, a system (or model) must have enough internal variety to represent the variety in that environment. In other words, oversimplifying can leave an organization unable to cope with environmental complexity. The art of strategy is finding the sweet spot: a simplification elaborate enough to capture what is crucial (so the organization’s responses are adequate) but simple enough to be shared, understood, and acted upon decisively. The next section formalizes the components of such simplifications – our five primitives – and shows how they provide a disciplined structure for both individual and collective sensemaking.

Five Primitives of Strategic Simplification

We propose that any strategic simplification – from a mental model in one person’s head to an overarching strategy shared by thousands – can be described in terms of five fundamental primitives: Units, Relations, Priorities, Commitments, and Loops. These are the building blocks of the simplified “model of reality” that guides action. In brief: Units are the elements or actors we distinguish; Relations are the linkages or interactions among those units; Priorities are the value weights, preferences, or rank-ordering of goals and concerns; Commitments are the choices made and constraints accepted (i.e. the aspects of the model “locked in” as a basis for action); and Loops are the feedback cycles through which the model and reality interact over time (e.g. sensing and updating processes). Each primitive reflects rich streams of research, which we draw upon to clarify its role in strategy simplification.

1. Units

“Units” are the basic entities we decide to distinguish in our simplified representation of reality. In cognitive psychology, identifying units corresponds to chunking or object formation – segmenting the continuous world into discrete actors or elements. For example, when a person is reasoning about a social situation, they might identify the units as specific people or groups (e.g. Alice, Bob, Team X) and objects of interest (the project, the budget). All finer details about those people (their millions of neurons or individual actions) and about the objects (every penny in the budget) are aggregated into a handful of conceptual units. This abstraction is fundamental. Miller’s classic findings on working memory limits and later research on chunking show that experts learn to group details into higher-order units so they can remember and think about complex phenomena efficiently. In strategy, units could be market segments, business units, product lines, customer categories, or key resources – essentially the pieces the strategy game is played with.

Deciding on units is a disciplined act of drawing boundaries. It means saying, for instance, that for strategic purposes we will treat all customers of type A as a single category (“the retail segment”), or we will treat a certain set of activities as one function (“operations” versus “marketing”). Cognitive science indicates that the perception of distinct objects or events in the world already involves simplifying judgments – we decide where one object or event ends and another begins. The Gestalt principles of perception (like grouping by proximity or similarity) illustrate how our minds carve the world into units that “make sense” by simplifying visual input. Likewise, strategists conceptually carve up the competitive landscape: e.g., defining who the competitors are (and ignoring fringe players), or identifying which assets are “core competencies” (and de-emphasizing others).

Systems theory reinforces the importance of units. A seminal idea from Donella Meadows is that a system consists of elements (parts), interconnections, and a purpose. The elements are essentially the units. If you imagine drawing a systems map of a business, you begin by listing the key elements – perhaps suppliers, the company, customers – before drawing arrows for their relations. Choosing the units is thus step one in any modeling exercise. It determines the level of resolution of your model. Will individual employees be units in the model, or will “the workforce” be one unit? In war gaming or simulations, one often uses aggregate units (e.g. divisions instead of individual soldiers) to keep the model tractable. The same logic applies to mental models and strategies: a retail chain’s strategy might treat “each store” as a unit, or instead treat “the company as a whole” as the unit and lump all stores together – different simplifications that lead to different foci.

Significantly, the decision about units shapes what can be seen later. If your strategic model treats “the market” as a single undifferentiated unit, you might miss important distinctions among customer types. Conversely, if you define too many fine-grained units, the strategy can become unmanageably complex. The disciplined strategist thus defines units at a useful level of granularity. Empirical research in organizational decision-making (e.g., in scenario planning) finds that naming the actors and factors (units) sets the stage for what scenarios or strategies will be considered. It’s a bit like choosing the chess pieces before a game: you decide that kings, queens, bishops, etc., are the relevant units – not the individual pawns’ personalities or the atoms of the board – and this simplification allows you to plan moves.

One vivid illustration of unit simplification is the human tendency to personify organizations or countries (“Germany decided to…”) – here an entire nation of millions is treated as one unit, an “actor”, which is a huge simplification, yet often a useful one in geopolitical strategy. In summary, the Units primitive captures the who or what of a simplified model. It requires abstracting and packaging the sprawling reality into distinct components on which attention will focus.

2. Relations

Once units are identified, a strategy or mental model specifies Relations among those units. Relations can be physical connections, causal influences, flows of information or resources, hierarchies, networks of communication, or any link that the simplification deems important. Cognitively, humans excel at understanding relational structure once the units are set. We form cause-and-effect links (“pressing this button causes that light to turn on”), spatial maps (“this city is north of that city”), and social networks (“Alice is Bob’s manager, and colleagues with Charlie”). In mental models, it is the relationships that allow us to simulate how things will unfold: if A is connected to B and B increases when A increases, then we anticipate certain outcomes. Johnson-Laird pointed out that mental models are often iconic or analogical – they mirror the relational structure of what they represent. For example, a mental model of a company’s org chart is essentially a simplified relation (a hierarchy) connecting units (positions/departments). People use such relational models to infer how information will flow or where decision bottlenecks might occur.

In strategic simplification, typical relations include causal hypotheses (“if we increase advertising, sales will rise”), competitive or cooperative relationships (“X is our rival in segment Y; if they cut price, we may lose customers”), dependency links (“component A relies on supplier B”), and feedback loops (“increased user base leads to more value, which attracts more users” – a positive feedback in a platform strategy). The strategist’s disciplined task is to map the structure of the situation by specifying key relations while ignoring the myriad relations that exist in the real world but are judged less impactful. A classic example is a strategy map or a causal loop diagram in system dynamics, which might show how different factors like product quality, customer satisfaction, and repeat sales reinforce each other. Such diagrams explicitly lay out relations (with arrows for influence) among chosen units, but any good strategy implicitly contains a set of assumed relations even if not drawn out.

Relations often come with assumptions about direction and strength. For instance, a company might hold the simplified assumption that “price has a bigger effect on market share than does product variety.” This indicates a belief about the relative strength of certain relations (price–share vs. variety–share). It is impossible to calculate all interactions in a complex economy, so strategists zero in on a few critical cause-effect chains or interaction networks. This is where disciplines like systems thinking urge strategists to be mindful: sometimes a simplistic linear relation is assumed (e.g. more investment = more output, indefinitely) when in reality there could be nonlinear limits or delays. Disciplined simplification means checking that the assumed relations do not grossly violate known principles (like assuming infinite growth is possible in a finite market, which is an oversimplification that courts failure). Indeed, part of the value of formal strategy frameworks (like Porter’s five forces, or a value chain model) is that they enumerate certain relations that should be considered (e.g. supplier bargaining power is a relation between the firm and its suppliers).

In group sensemaking, establishing shared relations can be achieved through storytelling (“The market works like this: when interest rates drop, consumers do X, and that enables our business to do Y”), through diagrams and models, or through experience. A shared causal narrative is powerful: it not only simplifies but also motivates action (“Because we believe A leads to B, we will do A to get B”). However, a risk is when the relation is spurious or has changed over time – organizations can get stuck acting on outdated assumed relations. A known phenomenon in organizational learning is that managers often have simplistic cause-effect beliefs (sometimes called “folk theories”) about performance (“if we just pay employees more, motivation will soar”), and these beliefs guide their actions until evidence or reflection updates the model.

In short, the Relations primitive captures the structure of the simplified reality – the connections that bind the units into a coherent whole. Defining these relations is a core part of strategy formulation (essentially strategy is hypothesizing a structure for how to influence outcomes). It transforms a mere list of parts into an actual model with dynamics.

3. Priorities

Reality does not tell us by itself what to focus on; priorities do. The Priorities primitive refers to the ordering of importance, preferences, or goals that guide the simplification. Both individuals and organizations must decide what matters most. In cognition, this appears as attention and salience: out of all the units and relations one could consider, one attends to those that align with one’s goals or seem most pressing. Prioritization is a kind of value-based filtering layered on top of the structural simplification. Two people might have similar mental models of a situation (same units and relations) but different priorities – for instance, one focuses on maximizing speed, another on minimizing risk. Those differing priorities will lead them to simplify decisions differently (one might ignore potential downsides, the other might ignore minor benefits).

In strategic terms, priorities are often explicit as objectives or key performance indicators (KPIs). An organization might prioritize growth over short-term profit, or prioritize customer satisfaction over internal efficiency, etc. These choices act as a simplifying lens: they make certain facts “signal” and others “noise.” If increasing market share is the top priority, then metrics and information related to market share will be highlighted in reports and discussions, whereas other data (e.g. employee satisfaction, perhaps) might be downplayed unless it ties to that goal. This is crucial for coordinated action – if everyone knows what the top priorities are, they can make decentralized decisions that, while locally simplified, still align globally. Priorities simplify decision-making by providing a rule of thumb: given limited time and resources, focus on the actions that advance the top priorities and let secondary matters fall by the wayside.

Psychological research on goal-driven cognition supports the idea that our perceptions and memories adjust to our current priorities. For example, a hungry person will notice food cues more – their mental model temporarily weights food-related units as high priority. Analogously, an organization in a turnaround crisis might prioritize cash flow so heavily that every meeting and mental model in the firm revolves around liquidity (units like “cash on hand” and relations like “cash in vs. out” dominate thinking). Priorities can be seen as the settings of the filter: what gets through and what gets ignored depends on these settings.

Crucially, prioritization must be disciplined to be strategic. If an organization has too many priorities (the infamous list of top 10 priorities), then in effect it has none – there is no simplification because everything is labeled important, and the result is confusion and lack of focus. Strategic simplicity often comes from a clear hierarchy of what matters. One might recall the military adage “the commander’s intent” – a single overriding goal that, if troops keep in mind, will guide them even when detailed plans break down. Similarly, in business, Jim Collins and Jerry Porras popularized the idea of a “Big Hairy Audacious Goal” (BHAG) to focus organizational energy. The point is that a single rallying priority (or a very short list with explicit rank order) serves as a simplifying heuristic for everyone’s decision filters.

The interplay between priorities and the other primitives is also interesting: Priorities influence which units and relations we pay the most attention to. Simon noted that administrative decision makers consider “only a few of the factors… most relevant and crucial”. Relevance and cruciality are essentially about priorities relative to the goal. If profit is the priority, cost and revenue become crucial factors (units), while other aspects might be screened out as less relevant. Organizationally, priorities are often set through strategy processes (like deciding strategic objectives annually). Those decisions have enormous simplifying power: they direct collective attention in one direction rather than another (a form of sensegiving from leaders).

However, misplaced or outdated priorities are a classic cause of strategic failure. An organization might stick to a priority that made sense in the old environment but now is counter-productive (e.g., prioritizing increasing production volume in a market that has shifted to demanding customization and quality). This highlights that priorities themselves may need to adjust via feedback (which ties into loops, discussed shortly). But at any given time, a well-defined set of priorities acts as the North Star for the simplified model – it is the purpose or value dimension that tells the organization how to evaluate options within the simplified representation.

4. Commitments

The primitive of Commitments represents the element of fixation or irreversibility in strategy – the aspects of the simplification that are not just theories or preferences, but are decided and enacted, thereby constraining future choices. In strategy, committing means making binding resource allocations or choices of direction: once you build a factory, commit to a technology standard, or publicly announce a strategic intent, you have simplified your possible future actions by eliminating alternatives (at least for some time). Commitments are a form of active simplification: by committing, an organization deliberately narrows its focus and options to concentrate on a chosen path.

Pankaj Ghemawat emphasizes commitment as “the tendency of strategies to persist over time” – companies get locked into trajectories because of past commitments that are costly to reverse. He notes that strategic commitments often involve irreversible or difficult-to-reverse decisions that limit future options. For example, deciding to specialize in a particular technology can be a commitment; so can signing a long-term contract, or acquiring a company. These actions simplify the strategic equation by removing degrees of freedom – a company that has committed to a high-cost, high-quality product strategy cannot simultaneously pursue a low-cost mass-market strategy without undoing or reneging on its commitments.

From a game-theoretic perspective, commitments can also shape the expectations and actions of others (which is why Thomas Schelling famously called commitment a tool of strategy in conflict: by committing to a course, you simplify the opponent’s expectations of your behavior, perhaps to your advantage). Within an organization, commitments play the role of coordinating through constraints. If all units know that there is a commitment to, say, invest 15% of revenue in R&D for the next three years, they will simplify their internal debates by not considering cutting R&D below that line – it’s a fixed point in their mental model.

Importantly, commitments convert part of the abstract strategy into concrete reality. Until something is committed, a strategy can remain a fuzzy simplification in PowerPoint slides. But once commitments are made (money spent, policies enacted, public commitments declared), the simplification gains teeth – it shapes behavior and outcomes. Michael Porter underlined that strategy is fundamentally about choosing what not to do, and that requires trade-offs. Saying “no” to certain options is the essence of commitment. As Porter put it, “strategy requires you to make trade-offs in competing – to choose what not to do.” Every “no” simplifies the realm of possibilities, ideally allowing stronger focus on the chosen “yes.”

Commitments in cognitive terms can also be related to belief fixation and consistency. Once individuals commit to a belief or course of action, they tend to filter information to support it (confirmation bias) and to behave consistently (the principle of commitment and consistency identified by social psychologists). In a positive sense, commitment focuses the mind: having a coherent plan that one is committed to can eliminate the paralysis of indecision. But the downside is rigidity – an unwillingness to adapt the simplification when evidence warrants (this will again invoke the need for feedback loops).

In organizations, commitments include tangible investments (capital expenditures, hiring decisions, etc.) and also strategic policies (like “we will only source sustainably” or “we will not enter market X”). These create coordination by self-imposed constraints. Nobel laureate Thomas Schelling gave a striking analogy: he compared an organization’s binding commitments to burning bridges behind you so that you have no choice but to move forward in the intended direction – a drastic form of simplification that ensures unity of action. While real organizations rarely burn actual bridges, they often burn metaphorical ones (e.g., discontinuing an old product line to focus on a new one, thereby committing to the new).

The concept of commitment also connects to organizational inertia. Some commitments are unintended – they accumulate as bureaucratic routines or past strategies that the organization implicitly sticks to. One challenge of strategic leadership is recognizing which commitments to hold (for coherence and credibility) and which to change (to avoid stagnation). For example, a firm might be committed to a certain business model through years of habit and asset configuration; changing that requires overcoming not just cognitive simplification but real sunk costs and legacy structures.

In summary, Commitments as a primitive represent the fixed choices and constraints within the simplified model that enable concerted action but also reduce flexibility. Strategy being a “disciplined simplification” implies that discipline comes partly from commitment – once you choose a path, discipline means sticking to it and not second-guessing at every turn, which would reintroduce complexity and confusion.

5. Loops

Finally, Loops refer to the iterative cycles of sensing, sensemaking, and responding that keep the simplification aligned (or misaligned) with reality over time. While the first four primitives (Units, Relations, Priorities, Commitments) describe the content of a simplified model at a given time, Loops capture the dynamic process aspect: strategy as something you continuously do, not just a static schema. The term “loops” evokes feedback loops – a central concept in systems theory. A feedback loop exists when changes in a system propagate through a series of relations and eventually “feed back” to influence the original element. In organizations, classic examples are reinforcing loops (success feeds on itself, e.g. word-of-mouth increasing as more customers join, further increasing customers) and balancing loops (homeostatic mechanisms like when inventory shortage triggers increased production, which then alleviates the shortage).

The presence of loops in our primitive list emphasizes that a strategic simplification must be maintained and adapted through continuous learning. A static simplification in a notebook will become obsolete as the world changes. Instead, effective strategy works as a learning loop or sensemaking loop: observe changes, update the mental model, adjust actions, then observe outcomes of those actions, and so on. John Boyd’s famous OODA loop (Observe–Orient–Decide–Act) is a pertinent example of a loop model from military strategy, highlighting speed and continuous iteration. The OODA loop explicitly frames decision-making as an iterative cycle in which an entity (individual or organization) that runs the loop faster and more effectively can outmaneuver opponents. In Boyd’s formulation, after acting, one observes the new situation, orients (interprets it via a mental model), decides on next action, and acts again, in a continuous flow. This resonates with our thesis: strategy as a living loop rather than a one-time plan.

In organizational learning theory, Chris Argyris and Donald Schön introduced the concept of single-loop and double-loop learning. In single-loop learning, the organization modifies its actions to correct deviations (like a thermostat adjusting temperature) but does not question its underlying assumptions. In double-loop learning, the organization reflects on whether the current goals or assumptions are correct, and may change the mental model itself. Double-loop learning is essentially the strategic simplification adjusting its own structure (units, relations, priorities) when they prove mis-specified. This idea is directly tied to strategy as sensemaking: when outcomes consistently defy the predictions of the simplified model, it’s time to rethink the model – perhaps our units of analysis were wrong, or a relation works differently than assumed, or our priorities need to change. A learning organization is one that has deliberate loops for feedback and update, avoiding the trap of static simplifications.

One can see loops at work in many strategic practices. Scenario planning is effectively a loop of envisioning multiple futures, monitoring which signals are emerging, and adapting the strategy accordingly. Agile management and lean startup methodologies also center on iterative loops: build a simple model or hypothesis, act (experiment), gather data, update the model – repeating rapidly. Even traditional strategic planning often includes annual or quarterly review loops, where results are compared to expectations and strategies are tweaked.

From a systems point of view, thinking in loops prevents the oversimplification of linear cause-and-effect assumptions. It forces consideration of how the system’s output feeds back as input. For example, a company might simplify a situation by saying “increase sales leads to increased profit”. But a loop perspective would ask: what happens after increased sales? Perhaps it saturates the market or triggers a competitor response (feedback effects). By incorporating loops, the strategist acknowledges that the model must eventually grapple with its own consequences.

Importantly, loops also refer to the collective sensemaking loop in an organization. Karl Weick described sensemaking in organizations as an ongoing, retrospective development of plausible stories that rationalize what people are doing. It’s ongoing and iterative – people act (often in small ways), then retrospectively incorporate those actions into the shared story (sensemaking), which then informs further action. In this way, strategy is emergent over time (as Mintzberg also argued with his notion of realized strategy being a “pattern in a stream of decisions”). The strategy emerges from a looping interplay of intended plans and real-time adaptations.

To put it succinctly: the Loops primitive captures the temporal, ongoing nature of strategy. It reminds us that a disciplined simplification is not one-and-done; it must be continually disciplined through feedback. A good strategic model is perishable – it needs refreshment through learning. Loops ensure that simplifications remain grounded in reality, adjusting when discrepancies arise.

With the five primitives defined – Units (what we pay attention to), Relations (how those pieces interact), Priorities (what we seek or value), Commitments (what we lock in and execute), and Loops (how we adapt over time) – we have a framework to analyze strategy as a simplified representation of reality enabling collective action. Next, we explore the concept of event boundaries and how it plays a role in detecting change both for individuals and organizations, linking closely with the loop concept just discussed.

Event Boundaries: Detecting and Managing Change

One intriguing concept from cognitive science that enriches our framework is that of event boundaries. In our daily experience, rather than perceiving life as a continuous stream, we tend to segment it into discrete events. Psychologists have found that “meaningful changes in context create ‘event boundaries’, segmenting continuous experience into distinct episodes in memory.” When an event boundary is crossed, our brain effectively closes one “file” and opens a new one, which has profound effects on attention and memory. For instance, at event boundaries, people are less likely to mind-wander and more likely to notice changes in their environment. The classic example of this phenomenon is the “doorway effect”: when you walk from one room to another through a doorway, you often forget what you intended to do in the new room. The very act of walking through the door serves as an event boundary in your mind – your brain partitions the episodes (“before” and “after” entering the new room), causing details from the prior context to become less accessible. In experimental studies, participants who passed through a doorway were more prone to forgetting information they acquired before crossing the threshold, compared to those who traveled an equivalent distance within the same room. The Event Horizon Model of memory suggests that at event boundaries, the mental model of the previous event is flushed or compressed to make way for a new event model.

Why are event boundaries relevant for strategy? Because both individuals and organizations must detect when something has fundamentally changed such that the current simplified model might need updating. An event boundary is essentially a cue that “we’re in a new situation now.” For an individual, event boundaries help manage change by prompting a reorientation – at boundaries, we pay more attention, reset our working memory, and become open to new information. In organizations, one can similarly speak of event boundaries: these could be external events like a market disruption, a technological breakthrough, a sudden loss of a key client, or internal events like a leadership change or a reorganization. Such moments often trigger strategic rethinking – they are inflection points where the existing shared mental model is questioned.

Organizations sometimes formalize event boundaries in their processes. For example, companies have quarterly reviews, annual strategic retreats, or post-mortems at the end of projects. These are institutionalized boundaries in time that encourage stepping back and evaluating whether the context has shifted. Similarly, a crisis can serve as an unplanned event boundary that snaps everyone out of routine and forces re-examination of assumptions (“Our supply chain just got disrupted; we are now in a new event – how do our priorities and mental model need to change?”). In strategic management research, the idea of punctuated equilibrium has been used to describe organizations as evolving through long periods of incremental change punctuated by brief episodes of radical change (Tushman & Romanelli, 1985). Those “punctuations” are essentially event boundaries at an organizational timescale – after which the organization’s strategy might transform significantly.

One benefit of recognizing event boundaries is improved change detection. At a boundary, individuals become more sensitive to what’s different. In the same way, an organization that marks an event boundary can more clearly see what has changed in the environment or internal conditions. For example, consider a retail company that treats each season as an event in its strategy; when a new season starts, they explicitly review trends (perhaps noticing, “This spring, customers’ preferences have shifted towards sustainable products”). By segmenting time into seasons (with boundaries at seasonal change), they ensure a periodic refresh of their mental model, rather than a continuous drift that might overlook gradual change. Another example: some tech companies declare an “all-hands on deck” event (like a hackathon or a war-room situation) when a competitor launches a major new product – this acts as a boundary in normal work routines, signaling that the context for their strategy might have shifted abruptly, and thus they must gather and update their situational understanding.

Event boundaries also relate to how organizations manage attention. Nobel laureate Herbert Simon noted that a wealth of information creates a poverty of attention. Organizations, like brains, cannot attend to everything continuously; they need to allocate attention strategically. One way to do so is to respond to event cues. In effect, event boundaries serve as attention-reset points – moments when you reconsider what you are doing. If an organization fails to delineate events (i.e., treat everything as one long continuous effort), it may suffer from inertia or gradual drift. Members may carry on with outdated simplifications because there was never a clear trigger to stop and rethink. By contrast, if you create clear episodes (“Project Alpha phase 1 complete – pause and evaluate before phase 2” or “End of Fiscal Year – review and replan”), you are more likely to update simplifications appropriately.

There is a link here with sensemaking and framing. A frame is a context or a defined situation (like “we are in a turnaround situation” versus “we are in a growth phase”). When a frame-breaking event happens, it’s an event boundary: people must re-frame what is happening. Karl Weick described how in crises (e.g., the Mann Gulch fire disaster he analyzed), the inability to successfully collectively redefine the situation (to see a boundary and shift tactics) led to tragedy. High-reliability organizations (like aircraft carriers or emergency units) train to rapidly collectively shift frames when cues indicate an event boundary (for instance, a routine operation turning into an emergency – everyone must recognize “Now this is a different kind of event” and adjust behavior accordingly).

In our five primitives terms, event boundaries signal when the current Loop should enact a major update of the other primitives. Crossing a boundary might require identifying new Units or dropping ones that were relevant before, altering Relations (perhaps what used to cause success no longer does), reordering Priorities (e.g., in a downturn, cash might leap to top priority whereas previously expansion was), and even changing Commitments (sometimes event boundaries force organizations to abandon certain commitments – e.g., 2020’s pandemic was a global event boundary that caused many strategic commitments to be undone as companies pivoted to survive).

In practical strategic management, leaders often deliberately create what we could call “sensemaking events” – structured moments that serve as event boundaries to facilitate change. A compelling vision speech, a strategy offsite with key managers, a rebranding rollout, etc., are attempts to signal “this is a new chapter” and thereby encourage everyone to update their mental models. On the negative side, organizations can suffer event boundary failures: either not recognizing a boundary (and thus plowing ahead with an obsolete strategy) or seeing false boundaries (panicking at noise and changing strategy too frequently). The disciplined strategist must therefore calibrate event boundary detection – neither underreacting nor overreacting to changes.

Cognitively, individuals have a pretty good intuitive sense for major vs. minor changes (hence not every tiny change triggers a reset of our event model). Likewise, organizations use tools like environmental scanning and threshold rules (e.g., “if sales drop by more than 20% month-over-month, that’s a flag that something fundamental might have changed”) to decide when a change constitutes a new “event” rather than random fluctuation. Another concept in strategy related to event boundaries is trigger points in contingency plans: “If X happens, we will treat it as a scenario break and execute Plan B.” These triggers demarcate events.

In conclusion, event boundaries are the mind’s and organization’s way to simplify the flow of change into manageable episodes. They help detect when the current simplifications need overhaul. By understanding and using event boundaries, strategists can better manage the tempo of their sensemaking loops – knowing when to stick to the current model versus when to initiate a fresh sensemaking cycle. This concept underscores that strategy, to be effective, must remain sensitive to context shifts and guard against the complacency of a once-correct simplification in a now-altered reality.

Strategy as a Living Sensemaking Loop

Drawing together the threads of this framework, we arrive at a view of strategy as a living, continuous process of collective sensemaking rather than a static plan on paper. Earlier, we asserted the thesis: strategy is a disciplined simplification of reality aimed at enabling coordinated collective action. We can now refine that: strategy is an ongoing loop in which a group maintains and revises a simplified model (units, relations, priorities, commitments) of their world to guide their collective actions, in light of feedback and changing events. It is living because it must constantly interact with a changing environment and with the evolving understanding of organizational members.

Karl Weick famously said, “Organizing consists of the ongoing retrospective development of plausible meanings that rationalize what people are doing.” In this sense, strategy is one aspect of organizing – it is the deliberate part of that sensemaking where leaders and teams attempt to proactively shape a coherent direction. It is social and interpretive: “Strategy as a social process is a sensemaking process… whose outcome is dependent on the strategy makers, their identities, and their interactions.” The disciplined simplification we have described (with the five primitives) is essentially the content of the shared sense that people in the organization make. The process by which they make and remake that sense is the strategic loop.

One might visualize the strategic loop as follows: Observe the environment and organization (gather data, experience events) → Simplify and make sense (using the five primitives: interpret what units are involved, what relations explain the data, what priorities are implicated, what commitments we have, etc.) → Decide and act (formulate strategic decisions, implement actions – essentially commit to a simplified course) → Experience results (which leads back to observing new data). This is analogous to the OODA loop; indeed, the OODA loop literature notes that continuous feedback and iteration enable agility, whereas rigid planning does not. A key advantage of treating strategy as a loop is that it reconciles the classic debate between deliberate and emergent strategy (Mintzberg, 1987). In our framework, deliberate strategy corresponds to the intentional design of the simplification (setting units, relations, priorities, commitments by choice), while emergent strategy corresponds to the evolution of that simplification through loops as real-world feedback and grassroots learning inform revisions. A truly effective strategy process embraces both: it is deliberate about the simplification it currently uses, yet responsive to emergence via learning loops.

Another implication of the living loop view is that shared mental models must be sustained through communication. The collective aspect means strategy lives in the conversations, stories, and tools that organization members share. It’s not enough for top management to have a simplified strategy model in their heads; it has to be externalized (through vision statements, strategy maps, OKR frameworks, etc.) and socialized so that it persists* and guides action across the organization. This social process is ongoing – not just an annual announcement but continuous sensegiving. As new people join, as old-timers forget or drift, the strategic simplification must be re-communicated and re-enacted to remain a common guide.

Coordinated collective action is the litmus test of a strategy’s effectiveness. All the effort to simplify reality has the goal of enabling many individuals to act in concert toward a goal, with minimal confusion or conflict. When strategy is working well as a living loop, one should see alignment: decisions made in different parts of the organization complement each other and converge toward the overarching objectives, because they are informed by the same simplifying framework. If marketing and R&D and operations all understand the business in roughly the same simplified way, their independent choices will tend to be coherent. Conversely, when strategy fails, it often manifests as disjointed actions, mixed messages, or paralysis – signs that the shared mental model either isn’t shared, isn’t accurate, or isn’t being updated. Perhaps the units are ill-defined (teams talking past each other), or priorities are unclear (different parts of the org optimizing different metrics), or commitments are absent (no one is actually implementing the supposed strategy), or no learning loop exists (the organization sticks to an outdated plan despite clear signals).

An example (hypothetical for illustration): imagine a tech company that initially simplifies its strategy around the units “product” and “customer”, relation “product quality leads to customer satisfaction leads to growth”, priority “innovation first”, and commitment “invest heavily in R&D”. This works during early growth. Now suppose the market saturates and a low-cost competitor appears – an event boundary. If the company treats this as a new event and runs a sensemaking loop, it might update its simplification: maybe now “efficiency” becomes a unit of attention, the relation “cost leads to price advantage which leads to market share” is added, and the priority might shift toward “balance innovation with cost control”. If it doesn’t adapt (stays with the old simplification of just innovating), it may lose in the new context. The living loop concept underscores that strategy must continuously reconcile its simplifications with reality. Reality is too complex to ever be fully captured, so a strategy that isn’t kept live will eventually become a dangerously outdated caricature.

Finally, this perspective highlights the role of leadership in strategy as being less about dictating detailed plans and more about nurturing the collective sensemaking process. Leaders help set initial simplifying frames (providing vision and focus), ensure that the organization’s structure and culture support the primitives (e.g., making sure units and relations defined in strategy are reflected in org design and information flow), enforce discipline in commitments (holding the line on strategic choices and saying no to deviations that break the agreed simplification), and critically, they also act as stewards of the learning loop (encouraging feedback, admitting when assumptions no longer hold, and fostering adaptability). A strategic leader might say, “Here’s our understanding of the world and what we’re going to do” but also “we will keep watching and learning, and we will pivot if needed.” This resonates with the idea of strategy as a hypothesis – a simplification that is tested in the market and revised as needed, akin to the scientific method but in the realm of competitive action.

Conclusion

In this paper, we have presented a comprehensive theoretical framework viewing strategy as a disciplined simplification of reality for coordinated collective action. By examining how simplification operates at the cognitive level and extends to the organizational level through shared mental models, we anchored strategy in human psychology and systems thinking. We identified five primitives – Units, Relations, Priorities, Commitments, and Loops – that jointly characterize the structure and process of any strategic simplification. Units and Relations denote how we abstract and model the world’s structure in simpler terms; Priorities and Commitments inject direction and execution into the model, focusing attention and locking in choices; and Loops tie the model to reality through continuous sensemaking and adaptation. The concept of event boundaries was introduced to illustrate how humans and organizations segment continuous change into manageable episodes, allowing timely updates to their simplifications. Overall, strategy emerges not as a one-time analytic exercise, but as an ongoing sensemaking loop – a conversational, iterative process of constructing, testing, and refining a simplified collective worldview that guides action.

This theoretical perspective integrates insights from cognitive science (e.g. bounded rationality and mental models), decision theory (e.g. the need for heuristics and feedback loops in complex decisions), organizational behavior (e.g. shared mental models and learning organizations), and systems theory (e.g. the importance of system structure and feedback). By doing so, it highlights that effective strategy is neither purely top-down planning nor pure emergence, but a dynamic synthesis of both – a guiding model that is deliberately formed and collectively held, yet perpetually open to revision as new information and events warrant.

One practical implication is that strategists and leaders should cultivate both the discipline and the flexibility inherent in this view. Discipline in simplification means being clear and consistent about the chosen units of analysis, key assumptions, and trade-offs – in essence, clarifying the simple rules or narratives that everyone should follow. Flexibility in adaptation means establishing mechanisms (feedback loops, check-ins at event boundaries) that challenge and update those simplifications when needed. The balance is delicate: too rigid a simplification and the organization becomes blind and unadaptive; too fluid a simplification and the organization loses coherence and coordination. The five primitives provide levers to adjust this balance: for example, periodically revisiting what units we track or adding a new unit if something important emerges, or reordering priorities when the environment shifts, can refresh the strategy without throwing away all simplification (thus preserving enough continuity for coordinated action).

Another implication is the importance of communication and learning culture. Since strategy as simplification fundamentally happens in the collective mind of the organization, fostering shared understanding is paramount. This means investing in storytelling, visualization, and dialogue around strategy – essentially, ensuring everyone internalizes the simplification. It also means encouraging an open culture where feedback (loop input) is valued and where admitting errors in the model is not seen as failure but as learning (echoing Argyris’ double-loop learning concept). In short, organizations might aim to become “strategy learning systems”, not just strategy execution machines.

This framework is theoretical, but future research could operationalize these concepts. For instance, can we measure an organization’s use of the five primitives in its strategy documents or meetings? Do organizations that explicitly address units/relations etc. perform better in turbulent environments? How do event boundaries manifest in different industries – are there natural “event rhythms” (like seasonal changes in retail) that firms can leverage more intentionally? Investigating such questions can refine our understanding of strategy as disciplined simplification.

In conclusion, by seeing strategy through the lens of cognitive and systemic simplification, we gain a unifying understanding of what strategists actually do: they build and maintain a manageable model of an unmanageable world, in order to align many minds and hands toward common goals. The most successful strategies are not those that assume away reality’s complexity completely, but those that simplify in just the right ways – capturing the essence of the situation, focusing energy on the pivotal points, and evolving as the world moves. Strategy thus is not the antithesis of complexity, but a partner to it: a never-ending dance of simplifying to act, and complexifying (through learning) to adjust. In that dance, disciplined collective simplification – lucid enough to guide action, yet alive enough to learn – is the music that keeps everyone in step.