Conditional Reality Tree

Pattern: A named solution to a recurring problem.

A reality-tree variant for mapping future UDEs under named conditions, especially when inaction or external change would make the system worse.

Also known as: Cond. RT; Conditional RT.

Reasoning mode: sufficiency-based logic under named starting conditions: the base condition gates whether the tree is valid; once it holds, arrows read if A, then B and multi-in-edge defaults to OR.

The Conditional Reality Tree is a late addition to the Thinking Process family. A Current Reality Tree diagnoses UDEs that exist now. A Future Reality Tree tests the desirable future caused by injections the practitioner intends to implement. Youssef and Mabin’s Conditional Reality Tree handles the gap between them: future UDEs expected when a condition holds and the system doesn’t take adequate action.

Context

The pattern belongs with the Thinking Processes because it keeps the same reality-tree discipline: entities stated clearly, arrows read aloud, and every causal claim open to Categories of Legitimate Reservations scrutiny. What changes is the reality being modeled. The tree is neither today’s current reality nor a desired future caused by a solution. It is a conditional future reality.

Youssef and Mabin developed the tool for situations the classical TP sequence handles awkwardly: a competitor entering a local market, a fast reservoir fill, a demand spike after another supplier fails, or leaders delaying action while warning signs accumulate. The tree asks what UDEs will probably appear if that condition becomes true.

The logic is mixed at the boundary and sufficiency-based in the tree. The starting condition has a necessity role: in order for this Conditional Reality Tree to be valid, the condition must hold. Once that gate is accepted, the diagram proceeds upward like a CRT or FRT, using if-then links from root causes and conditions to expected UDEs.

Problem

Practitioners often see a future problem before the system treats it as a current problem. The signs are visible enough to worry people, but not enough to force action: a chain competitor preparing to enter, a dam-fill decision approaching, or a deadline moving toward a system that isn’t ready. The UDEs are not current yet, so a CRT has no current entities to map.

The FRT is also the wrong tool. It starts with injections and tests whether they create desirable effects, then uses negative branches to trim side effects of those injections. In the conditional case, the primary cause is not the team’s chosen injection. It is inaction, inadequate action, or an external event.

The result is a blind spot. People wait until the UDEs exist, then run a CRT after avoidable damage has already landed. Or they argue from intuition: “if we don’t act, this will get bad.” Intuition may be right, but it doesn’t give a TOC-trained reviewer a shared logic path to scrutinize. The Conditional Reality Tree gives the warning a form.

Forces

• Future UDEs are easy to discount. Decision makers often treat a not-yet-existing effect as speculative, even when the starting condition is close enough to matter.

• The current-reality protocol is strict. CRT entities have to exist now. Loosening that rule to include future entities weakens the CRT rather than strengthening the analysis.

• The future-reality protocol is solution-centered. FRTs model the intended effects of injections. They don’t naturally model the bad future caused by not acting.

• External change changes the diagnosis. A condition outside the system can produce UDEs without being a current internal root cause or a chosen injection.

• Inaction has causes too. Zultner’s Change Matrix framing helps explain why decision makers may stay near the current state: the mermaid, alligator, crutches, rattlesnake, and missing gold nuggets can all keep action from becoming acceptable.

Solution

Build a Conditional Reality Tree when the question is: what UDEs are expected if this named condition holds and we do not make an adequate change now? Start by naming the condition or conditions at the base: an external event, a worsening trend, a do-nothing response, or a positive shock whose load the system can’t absorb.

Then construct the tree upward using sufficiency logic. Read each arrow as an if-then claim. If the condition holds, and the named current facts or root causes also hold, what follows? Where the causal link needs more than one cause, use an explicit AND-junctor. Where either branch alone is enough, leave the default OR reading visible through ordinary converging arrows.

Youssef and Mabin describe a four-step process: start with a CRT if one exists, state the future starting conditions at the bottom, revise the current tree around those conditions, and scrutinize the result with the CLR. The last pass includes the question the first draft often misses: what UDEs have not yet been foreseen?

The first small Conditional Reality Tree below shows the default-mode form. A single starting condition, a chain store entering the local trade area, is sufficient to trigger two independent paths in a retailer that has not prepared: rent pressure and customer-switching pressure. The two paths converge on a shared UDE, and the bare convergence keeps the sufficiency default.

flowchart BT
    C1[Chain competitor enters the local trade area] --> M1[Rents rise around the prime location]
    C1 --> M2[Customers compare prices against the chain]
    M1 --> UDE1[The owner's cash buffer shrinks]
    M2 --> UDE2[Daily sales fall]
    UDE1 --> UDE3[The retailer cannot fund the required repositioning]
    UDE2 --> UDE3

    classDef andjunctor fill:#A6894B,stroke:#3a2f1a,color:#fff,stroke-width:1.5px;

Diagram: Flowchart. The diagram contains these connections:

• Chain competitor enters the local trade area leads to Rents rise around the prime location.

• Chain competitor enters the local trade area leads to Customers compare prices against the chain.

• Rents rise around the prime location leads to The owner's cash buffer shrinks.

• Customers compare prices against the chain leads to Daily sales fall.

• The owner's cash buffer shrinks leads to The retailer cannot fund the required repositioning.

• Daily sales fall leads to The retailer cannot fund the required repositioning.

The override-mode form is different. In Youssef and Mabin’s business example, the severe future depends on the competitor entering and the owner refusing to change. Neither condition alone is the whole claim. The AND-junctor makes the joint condition explicit.

flowchart BT
    C1b[Chain competitor enters the local trade area] --> AndCond(("AND"))
    C2b[Owner refuses to change the current offer] --> AndCond
    AndCond --> M1b[The retailer keeps the same cost structure against a stronger competitor]
    M1b --> UDE1b[Cash runs out before a new position can be tested]

    classDef andjunctor fill:#A6894B,stroke:#3a2f1a,color:#fff,stroke-width:1.5px;
    class AndCond andjunctor;

Diagram: Flowchart. The diagram contains these connections:

• Chain competitor enters the local trade area leads to AND.

• Owner refuses to change the current offer leads to AND.

• AND leads to The retailer keeps the same cost structure against a stronger competitor.

• The retailer keeps the same cost structure against a stronger competitor leads to Cash runs out before a new position can be tested.

The two diagrams model the convention. The first uses the ordinary sufficiency reading under one condition. The second uses an AND-junctor when the tree’s validity depends on two conditions together. In both cases, the condition is not an injection. It is the state of the world the practitioner is warning about.

How It Plays Out

Youssef and Mabin’s water-dispute example shows the tool’s natural scale. A dam is nearly complete. The upstream country may fill the reservoir quickly. The downstream country may make no major change in response. A CRT cannot model the downstream UDEs because the fast-fill effects do not yet exist. An FRT cannot model them because no injection has been selected. The Conditional Reality Tree starts with the condition: fast reservoir filling occurs, and the downstream country does not make a sufficient response. From there, the tree traces expected UDEs in water availability, agriculture, electricity, public stress, and diplomatic conflict.

The same structure fits the business-owner case. The local shop’s present reality may be strained but survivable. The conditional future is triggered when a chain competitor opens nearby and the owner continues to protect the old location and old offer. The tree is not blaming the owner for the external condition. It shows why the old response set becomes unsafe under the new condition.

Youssef and Mabin also note the positive-shock case. A competitor goes out of business, sales spike, and the remaining firm celebrates. The Conditional Reality Tree asks what UDEs may appear if the firm lacks protective capacity, supplier reliability, or service discipline. The condition is positive in ordinary language; the modeled future may still be negative if the system can’t absorb the load.

Warning: A Conditional Reality Tree is not a license to dramatize every risk. If the starting condition is weak, if the future UDEs are stated as fears rather than observable effects, or if the arrows don’t survive CLR scrutiny, the diagram is advocacy dressed as logic. The point is to make the warning testable.

Consequences

Benefits. The pattern lets a practitioner reason about future UDEs without violating the CRT’s present-entity rule or forcing the situation into an FRT. It gives decision makers a shared diagram for the cost of inaction and makes external-change scenarios reviewable by TOC peers. It also preserves the rest of the TP sequence: once the conditional future is clear, the practitioner can move to Clouds, conditional FRTs, conditional PRTs, and Transition Trees.

Liabilities. The tree is easy to overclaim. A weak Conditional Reality Tree can smuggle prediction into logic, especially when the starting condition is political, environmental, or market-driven and evidence is thin. It can also become a scare tactic if the practitioner writes future UDEs in vague language or refuses to state the assumptions under each arrow. The tool is recent, so the field has less shared practice around it than around the CRT, FRT, Cloud, or PRT.

The other liability is sequencing. The Conditional Reality Tree can motivate action, but it doesn’t choose the action. A team that stops after drawing the bad future may create urgency without a route out. The tree should be followed by ordinary solution work: surface the conflict, test injections, map obstacles, and sequence the transition.

Contrasts with: Future Reality Tree (FRT) — The FRT maps desirable effects expected from implemented injections; the Conditional Reality Tree maps expected UDEs when named conditions hold and action is absent, inadequate, or externally forced.

Extends: Current Reality Tree (CRT) — The Conditional Reality Tree borrows the CRT's reality-tree structure, but moves the analyzed UDEs into a future conditional reality rather than today's existing system.

Informed by: The Change Matrix — Youssef and Mabin use Zultner's expanded Change Matrix to explain why decision makers may remain near the current state even when the future UDEs are visible.

Related: Evaporating Cloud (Conflict Resolution Diagram) — A Conditional Reality Tree can be linked to a core conflict at its base, as in Youssef and Mabin's business-owner example where refusal to change is held by a cloud.

Tested by: Categories of Legitimate Reservations (CLR) — Youssef and Mabin require the finished tree to be scrutinized with the CLR, including checks for future UDEs the first pass failed to foresee.

Uses: Necessary Cause (Necessity Logic) — The starting condition has a necessity role: in order for this conditional tree to be valid, the named condition or conditions must hold.

Uses: Sufficient Cause (Sufficiency Logic) — Once the starting condition is accepted, the Conditional Reality Tree reads upward through if-then sufficiency links like other reality trees.

Sources

• Youssef and Mabin, Conditional Reality Tree (Cond. RT) (TOCICO, 2024), in the local library. The primary source for the tool: definition, rationale, Standing-on-the-Shoulders-of-Giants derivation, the mixed boundary between necessity and sufficiency logic, the four process steps, and the population, water-dispute, and retailer examples.

• Cox and Schleier, Theory of Constraints Handbook (2010), Ch. 23 (Mabin and Davies, “The TOC Thinking Processes: Their Nature and Use”). The canonical source for the classical TP sequence the Conditional Reality Tree extends: CRT for what to change, EC and FRT for what to change to, PRT and Transition Tree for how to cause the change, plus the sufficiency and necessity building blocks.

• Cox, TOCICO Dictionary of Theory of Constraints Terms (2nd ed., 2012), entries “current reality tree,” “future reality tree,” “sufficiency-based logic,” “necessity-based logic,” “undesirable effect,” “injection,” and “categories of legitimate reservation.” The certification-grade vocabulary used to keep the new tool’s claims compatible with the older TP canon. Distributed through TOCICO membership; no Open Library record.

• Zultner, The Change Matrix: Corrected & Enhanced from 4 to 6 Boxes (CM2) (TOCICO Body of Knowledge paper, 2023), in the local library. Youssef and Mabin use the expanded Change Matrix to explain why actors may remain near the current state even when the future UDEs should be motivating action.