## PART XIII - RISK, PORTFOLIO CONTEXT, AND DECISION MAKING | MODULE 064 # Decision Journaling and Pre-Mortems > Mission. Record the decision, evidence, disconfirming facts, expected path, and what would change the view. ## Decision output Objective: Record the decision, evidence, disconfirming facts, expected path, and what would change the view. The completed work product must be reproducible from evidence, show the downstream financial or decision effect when material, state the strongest contrary case, and define a dated update rule. ## Explicit operating procedure 1. Before the decision outcome is known, record thesis, valuation range, key assumptions, confidence, expected path, catalysts, risks, strongest contrary evidence, and what would change the view. 1. Run a pre-mortem: assume the thesis failed badly and list plausible reasons across demand, competition, execution, accounting, regulation, balance sheet, valuation, and process. 1. Convert the most plausible pre-mortem failures into leading indicators and thesis-break conditions with dates/sources. 1. Record alternatives considered and why they were rejected so later reviewers can distinguish a good process from hindsight reconstruction. 1. Freeze the journal version at each major decision or material thesis update. Do not rewrite prior reasoning after the outcome. 1. Use the journal in post-mortems to compare what was expected with what actually occurred and where uncertainty was misjudged. ## Required evidence and model bridge - Primary-source set: risk register, stress model, correlation/liquidity inputs, decision journal, forecast-error history. Preserve exact document/version, date, period, and source location for every material factual input used in decision journaling and pre-mortems. - For each key concept - dated decision, market expectations, assumptions, probability ranges, expected evidence, pre-mortem - state whether it is a reported fact, analyst calculation, management claim, external estimate, or judgment. Quantitative concepts must retain raw components and units; qualitative concepts must retain the specific evidence and counterevidence. - Map only economically relevant findings into the model or decision record. Process-control modules such as decision journaling and pre-mortems may have no direct valuation line; in that case document the downstream error or governance risk the control prevents. ## Metrics and calculation controls | Metric / concept | Construction | Required validation | | --- | --- | --- | | precommitment coverage | % of identified material decisions with a dated pre-mortem, base-rate expectation, thesis-break rule, and action trigger documented before the outcome. | precommitment coverage: Recalculate from same-scope numerator and denominator; confirm period, units, cohort/geography, and issuer definition; reconcile material differences to filings or operating data. | | calibration | For forecasts assigned probability p, realized frequency of the event in that probability bucket; compare realized frequency with stated probability. | calibration: Recalculate from same-scope numerator and denominator; confirm period, units, cohort/geography, and issuer definition; reconcile material differences to filings or operating data. | | thesis drift count | Number of material thesis assumptions changed after adverse evidence without a contemporaneous documented rationale or explicit thesis reset. | thesis drift count: Reperform the count from the defined population, inspect every material exception, and confirm the denominator/universe did not change between periods. | ## Worked application > Case: the stock rises even though a precommitted retention threshold breaks. - Reconstruct the relevant reported fact from primary evidence before interpreting the case. For decision journaling and pre-mortems, show the raw components rather than only the resulting ratio or narrative. - Build the causal chain through dated decision, market expectations, assumptions, probability ranges, then identify which link is directly observed and which link remains an assumption. - Calculate precommitment coverage, calibration, thesis drift count from sourced components under the reported/base interpretation and at least one skeptical alternative interpretation. - Translate the difference between cases into the variable that matters for decision journaling and pre-mortems: evidence quality, revenue, operating profit/NOPAT, free cash flow, invested capital, financing/dilution, risk, or valuation. Mark non-applicable links instead of inventing them. - Expert consistency test: judge the new evidence against the old standard before price action changes the narrative. - Precommit the specific future filing, KPI, customer/supplier observation, regulator action, or market input that would materially invalidate the decision journaling and pre-mortems conclusion. ## Failure tests - FAIL if dated decision cannot be defined and reproduced from the source pack. - FAIL if the prior decision state cannot be reconstructed or if a pre-mortem does not identify distinct failure mechanisms and early warning evidence. - FAIL if the decision journaling and pre-mortems conclusion depends on an unstated assumption, unreconciled definition, or evidence that cannot be traced to its source/version. - FAIL if evidence materially inconsistent with the decision journaling and pre-mortems conclusion is omitted, reclassified, or dismissed without a documented definition, materiality, causal, timing, and source-quality analysis. ## Completion test A senior reviewer must be able to reproduce the decision journaling and pre-mortems conclusion, vary the most sensitive assumption independently, trace the change through the model, understand the strongest opposing case, and identify the next evidence that would force an update. If any link is missing, the module remains open.