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aria-labelledby=\"nx-scene-title\"><div class=\"nx-scene-intro nx-es-intro\"><p class=\"nx-eyebrow\"><abbr title=\"The Global Risks Forum\">GRF<\/abbr> \u00b7 Foresight Nexus<\/p><span class=\"nx-scene-rule\" aria-hidden=\"true\"><\/span><h1 id=\"nx-scene-title\" class=\"nx-scene-title\">Decision analysis in foresight<\/h1><p class=\"nx-scene-lede\">Decision analysis under uncertainty links foresight to choice. It makes objectives, options, uncertainties and value judgements explicit, and under <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 deep-uncertainty\" data-tk=\"Nexus risk vocabulary\" data-td=\"A situation in which the parties cannot agree on the models describing a system, the probability of key inputs, or how to value outcomes. Under deep uncertainty Nexus favours scenarios and robust decisions over single\u2026\" data-ts=\"NRS-C1\" data-tr=\"draft\">deep uncertainty<\/a> it replaces the search for an optimal answer with tests of robustness and adaptability across many futures.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/globalriskforum.com\/foresight\/write-to-us\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/globalriskforum.com\/foresight\/stem\/\">Back to STEM foundation of Foresight Nexus<\/a><\/div><\/div><\/section><section id=\"nx-s-1-sec\" class=\"nx-section\" data-hue=\"systemic\" data-tone=\"alt\" aria-labelledby=\"nx-s-1\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Register<\/span><\/div><h2 id=\"nx-s-1\" class=\"nx-section-title\">Decision analysis in foresight on the record.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-es-fig\" data-es-layout=\"console\"><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Method record<\/strong><\/span><span class=\"nx-eyebrow\">STEM method<\/span><\/div><ol class=\"nx-register-rows\"><li><div><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">Decision analysis under uncertainty<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Steward<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/risk-management\/\">Systemic Risk Management<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Applied in<\/span><span class=\"nx-register-v\">Foresight Nexus<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Data<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-data\">4 inputs<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Checks<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-checks\">4 validation steps<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Canonical page<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/decision-analysis\/\">STEM Commons<\/a><\/span><\/div><\/li><\/ol><\/div><\/div><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-1\" data-hue=\"risk\" aria-label=\"Application, Policy scenarios, Data, Implementation\"><div class=\"nx-container\"><div class=\"nx-hm-band nx-band\" data-nx-tabs=\"true\" data-active=\"p1\"><div class=\"nx-tablist nx-hm-tabs\" role=\"tablist\" aria-label=\"Application, Policy scenarios, Data, Implementation\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-1\" aria-controls=\"nx-sec-application\" aria-selected=\"true\" data-key=\"p1\">Application<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-2\" aria-controls=\"nx-sec-instrument\" aria-selected=\"false\" data-key=\"p2\">Policy scenarios<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-3\" aria-controls=\"nx-sec-data\" aria-selected=\"false\" data-key=\"p3\">Data<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-4\" aria-controls=\"nx-sec-instrument-2\" aria-selected=\"false\" data-key=\"p4\">Implementation<\/button><\/div><section id=\"nx-sec-application\" class=\"nx-section nx-band-panel\" data-hue=\"risk\" data-variant=\"split\" aria-labelledby=\"nx-s-2\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-1\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Application<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">What decision analysis under uncertainty does here.<\/h2><p class=\"nx-lede\">Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict. It makes trade-offs and value judgements explicit. In foresight and risk management and <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 systemic-risk\" data-tk=\"Nexus risk vocabulary\" data-td=\"Risk that the failure or disruption of parts of an interconnected system propagates through its dependencies to impair the functioning of the whole, often beyond the sector or place where it began. It arises from\u2026\" data-ts=\"NRS-C1\" data-tr=\"draft\">systemic risk<\/a>, decision analysis helps choose actions that perform acceptably across interconnected risks and uncertain futures. It clarifies when to act now and when to keep options open. The canonical description is on <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/decision-analysis\/\">the STEM Commons<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cols\"><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><circle cx=\"12\" cy=\"12\" r=\"6\"\/><circle cx=\"12\" cy=\"12\" r=\"2\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Robust decision making<\/h3><p class=\"nx-p nx-mt-1\">Candidate policies are run across a large ensemble of futures; the conditions under which each fails are identified and used to design options that are less vulnerable.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"6\" cy=\"19\" r=\"3\"\/><path d=\"M9 19h8.5a3.5 3.5 0 0 0 0-7h-11a3.5 3.5 0 0 1 0-7H15\"\/><circle cx=\"18\" cy=\"5\" r=\"3\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Dynamic adaptive policy pathways<\/h3><p class=\"nx-p nx-mt-1\">Sequences of actions are mapped with their adaptation tipping points and lead times, so decision-holders can see which choices keep later options open and when a switch falls due.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M16 21v-2a4 4 0 0 0-4-4H6a4 4 0 0 0-4 4v2\"\/><circle cx=\"9\" cy=\"7\" r=\"4\"\/><path d=\"M22 21v-2a4 4 0 0 0-3-3.87\"\/><path d=\"M16 3.13a4 4 0 0 1 0 7.75\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Structured expert elicitation<\/h3><p class=\"nx-p nx-mt-1\">Experts are selected, briefed and asked for quantiles on uncertain quantities through Delphi rounds or calibrated protocols; judgements are aggregated and their spread is reported rather than hidden.<\/p><\/article><\/div><\/div><\/div><\/section><section id=\"nx-sec-instrument\" class=\"nx-section nx-band-panel\" data-hue=\"systemic\" data-ns-layout=\"es-wide\" aria-labelledby=\"nx-s-3\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Policy scenarios<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Compare instruments: rules, incentives and information.<\/h2><p class=\"nx-lede\">Three families of instruments side by side against the baseline, each with its own lag and adoption speed, under the coverage and compliance you set; effect sizes are teaching values to replace with evidence. Scenario: named assumptions about the future, not a forecast.<\/p><\/div><div class=\"nx-section-body\"><figure class=\"nx-in nx-fk\" id=\"nx-in-foresight-stem-decision-analysis-0\" data-nxi=\"policy\" data-nxi-id=\"policy\" data-nxi-z=\"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\" aria-label=\"Compare instruments: rules, incentives and information\"><div class=\"nx-in-body\"><div class=\"nx-in-main\"><div class=\"nx-in-tabs\" data-nxi-tabs=\"true\" aria-label=\"Views of the model\" hidden><button type=\"button\" class=\"nx-in-tab\" data-nxi-view=\"result\">Result<\/button><button type=\"button\" class=\"nx-in-tab\" data-nxi-view=\"fan\">Uncertainty<\/button><button type=\"button\" class=\"nx-in-tab\" data-nxi-view=\"tornado\">Sensitivity<\/button><button type=\"button\" class=\"nx-in-tab\" data-nxi-view=\"loops\">Loops<\/button><\/div><div class=\"nx-in-stage\" id=\"nx-in-foresight-stem-decision-analysis-0-stage\" data-nxi-stage=\"true\" data-view=\"result\"><svg class=\"nx-in-svg\" viewBox=\"0 0 720 340\" role=\"img\" aria-label=\"Outcome by option\" data-nx-z=\"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\"><\/svg><\/div><p class=\"nx-in-tip\" data-nxi-tip=\"true\" aria-live=\"polite\"><\/p><div class=\"nx-in-bar\" data-nxi-bar=\"true\" role=\"group\" aria-label=\"Play over time\" hidden><button type=\"button\" class=\"nx-in-btn\" data-nxi-prev=\"true\" aria-label=\"Step back\">&#8249;<\/button><button type=\"button\" class=\"nx-in-btn\" data-nxi-play=\"true\" aria-pressed=\"false\">Play<\/button><button type=\"button\" class=\"nx-in-btn\" data-nxi-next=\"true\" aria-label=\"Step forward\">&#8250;<\/button><span class=\"nx-in-step\" data-nxi-step=\"true\" aria-live=\"polite\"><\/span><\/div><\/div><div class=\"nx-in-side\"><p class=\"nx-eyebrow\">Controls<\/p><div class=\"nx-in-ctl\" data-nxi-ctl=\"true\"><dl class=\"nx-in-pv\"><div><dt>Baseline trend of the outcome<\/dt><dd>2.0% a year<\/dd><\/div><div><dt>Coverage of the instrument<\/dt><dd>70%<\/dd><\/div><div><dt>Compliance<\/dt><dd>75%<\/dd><\/div><div><dt>Effect size, against the teaching value<\/dt><dd>100%<\/dd><\/div><div><dt>Years ahead<\/dt><dd>20 years<\/dd><\/div><\/dl><\/div><p class=\"nx-eyebrow\">Readouts<\/p><dl class=\"nx-in-out\" data-nxi-out=\"true\" aria-live=\"polite\"><div><dt>Largest reduction at the horizon<\/dt><dd>Regulation<\/dd><\/div><div><dt>Its reduction against the baseline<\/dt><dd>21%<\/dd><\/div><\/dl><\/div><\/div><details class=\"nx-in-more\"><summary>Numbers, methods and sources<\/summary><div class=\"nx-in-more-in\"><div class=\"nx-in-tblw\" data-nxi-table=\"true\"><table class=\"nx-in-tbl\"><thead><tr><th scope=\"col\">Year<\/th><th scope=\"col\">Baseline<\/th><th scope=\"col\">Regulation<\/th><th scope=\"col\">Economic incentive<\/th><th scope=\"col\">Information and capacity<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">0<\/th><td>100.0<\/td><td>99.5<\/td><td>98.8<\/td><td>99.1<\/td><\/tr><tr><th scope=\"row\">1<\/th><td>102.0<\/td><td>101.2<\/td><td>100.1<\/td><td>99.8<\/td><\/tr><tr><th scope=\"row\">2<\/th><td>104.0<\/td><td>102.5<\/td><td>101.1<\/td><td>99.9<\/td><\/tr><tr><th scope=\"row\">3<\/th><td>106.1<\/td><td>103.5<\/td><td>101.6<\/td><td>100.0<\/td><\/tr><tr><th scope=\"row\">4<\/th><td>108.2<\/td><td>103.7<\/td><td>101.8<\/td><td>100.7<\/td><\/tr><tr><th scope=\"row\">5<\/th><td>110.4<\/td><td>103.2<\/td><td>101.7<\/td><td>102.1<\/td><\/tr><tr><th scope=\"row\">6<\/th><td>112.6<\/td><td>102.0<\/td><td>101.6<\/td><td>103.9<\/td><\/tr><tr><th scope=\"row\">7<\/th><td>114.9<\/td><td>100.4<\/td><td>101.6<\/td><td>105.9<\/td><\/tr><tr><th scope=\"row\">8<\/th><td>117.2<\/td><td>99.2<\/td><td>102.1<\/td><td>108.0<\/td><\/tr><tr><th scope=\"row\">9<\/th><td>119.5<\/td><td>98.6<\/td><td>102.9<\/td><td>110.1<\/td><\/tr><tr><th scope=\"row\">10<\/th><td>121.9<\/td><td>98.9<\/td><td>104.2<\/td><td>112.3<\/td><\/tr><tr><th scope=\"row\">11<\/th><td>124.3<\/td><td>99.7<\/td><td>105.7<\/td><td>114.5<\/td><\/tr><tr><th scope=\"row\">12<\/th><td>126.8<\/td><td>101.1<\/td><td>107.4<\/td><td>116.8<\/td><\/tr><tr><th scope=\"row\">13<\/th><td>129.4<\/td><td>102.7<\/td><td>109.4<\/td><td>119.2<\/td><\/tr><tr><th scope=\"row\">14<\/th><td>131.9<\/td><td>104.5<\/td><td>111.4<\/td><td>121.6<\/td><\/tr><tr><th scope=\"row\">15<\/th><td>134.6<\/td><td>106.5<\/td><td>113.5<\/td><td>124.0<\/td><\/tr><tr><th scope=\"row\">16<\/th><td>137.3<\/td><td>108.5<\/td><td>115.7<\/td><td>126.5<\/td><\/tr><tr><th scope=\"row\">17<\/th><td>140.0<\/td><td>110.7<\/td><td>118.0<\/td><td>129.0<\/td><\/tr><tr><th scope=\"row\">18<\/th><td>142.8<\/td><td>112.9<\/td><td>120.4<\/td><td>131.6<\/td><\/tr><tr><th scope=\"row\">19<\/th><td>145.7<\/td><td>115.1<\/td><td>122.8<\/td><td>134.2<\/td><\/tr><tr><th scope=\"row\">20<\/th><td>148.6<\/td><td>117.4<\/td><td>125.2<\/td><td>136.9<\/td><\/tr><\/tbody><\/table><\/div><button type=\"button\" class=\"nx-in-btn\" data-nxi-csv=\"true\" hidden>Download the numbers (CSV)<\/button><h4 class=\"nx-h4\">Methods<\/h4><ol class=\"nx-in-meth\"><li>Tools of government <span class=\"nx-in-cite\">Hood (1983), The Tools of Government, Macmillan<\/span><\/li><li>Carrots, sticks and sermons <span class=\"nx-in-cite\">Bemelmans-Videc, Rist and Vedung (1998), Transaction<\/span><\/li><li>Diffusion of innovations <span class=\"nx-in-cite\">Rogers (2003), Diffusion of Innovations, Free Press<\/span><\/li><li>Uncertainty fan (parameter Monte Carlo) <span class=\"nx-in-cite\">Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333<\/span><\/li><li>One-at-a-time sensitivity (tornado) <span class=\"nx-in-cite\">Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley<\/span><\/li><\/ol><h4 class=\"nx-h4\">Data<\/h4><p class=\"nx-p\">The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page&#8217;s map can draw:<\/p><ul class=\"nx-in-src\"><li>Borders <span class=\"nx-in-cite\">Natural Earth<\/span><\/li><li>Cities <span class=\"nx-in-cite\">Natural Earth<\/span><\/li><\/ul><\/div><\/details><figcaption class=\"nx-caption\">Compare instruments: rules, incentives and information. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Tools of government (Hood (1983), The Tools of Government, Macmillan); Carrots, sticks and sermons (Bemelmans-Videc, Rist and Vedung (1998), Transaction); Diffusion of innovations (Rogers (2003), Diffusion of Innovations, Free Press).<\/figcaption><div class=\"nx-in-pls\"><p class=\"nx-eyebrow\">Across the six pillars, led by Nexus Consortium<\/p><ul class=\"nx-in-pl\" aria-label=\"Where this instrument connects across the pillars\"><li data-pillar=\"labs\" data-hue=\"social\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Experiments<\/span> <a class=\"nx-link\" href=\"https:\/\/therisk.global\/nexus-labs\/\">Labs<\/a><\/li><li data-pillar=\"foundry\" data-hue=\"infrastructure\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Built in<\/span> <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/foundry\/\">Foresight Nexus in Foundry<\/a><\/li><li data-pillar=\"universe\" data-hue=\"water\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Tested at<\/span> <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/universe\/\">Foresight Nexus in Universe<\/a><\/li><li data-pillar=\"standards\" data-hue=\"biodiversity\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Codified in<\/span> <a class=\"nx-link\" href=\"https:\/\/nexustandards.com\/systemic-risk\/\">Systemic Risks in Standards<\/a><\/li><li data-pillar=\"reports\" data-hue=\"energy\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Published in<\/span> <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/reports\/\">Foresight Nexus in Reports<\/a><\/li><li data-pillar=\"academy\" data-hue=\"risk\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Taught in<\/span> <a class=\"nx-link\" href=\"https:\/\/risksacademy.com\/risk-science\/\">Faculty of Risk Science and Methods in Academy<\/a><\/li><\/ul><\/div><span class=\"nx-in-keep\" hidden><i data-c=\"c1\"><\/i><i data-c=\"c2\"><\/i><i data-c=\"c3\"><\/i><i data-c=\"c4\"><\/i><i data-c=\"c5\"><\/i><i data-c=\"c6\"><\/i><i data-c=\"l0\"><\/i><i data-c=\"l1\"><\/i><i data-c=\"l2\"><\/i><i data-c=\"l3\"><\/i><i data-c=\"l5\"><\/i><i data-c=\"h3\"><\/i><i data-c=\"neg\"><\/i><i data-c=\"on0\"><\/i><i data-c=\"on1\"><\/i><i data-l=\"0\"><\/i><i data-l=\"1\"><\/i><i data-l=\"2\"><\/i><i data-l=\"3\"><\/i><i data-l=\"4\"><\/i><i data-l=\"5\"><\/i><i data-on=\"0\"><\/i><i data-on=\"1\"><\/i><i data-pol=\"p\"><\/i><i data-pol=\"n\"><\/i><i data-k=\"R\"><\/i><i data-k=\"B\"><\/i><i data-k=\"dash\"><\/i><i data-dash=\"true\"><\/i><i data-view=\"result\"><\/i><i data-nxi-live=\"on\"><\/i><i data-nxi-live=\"off\"><\/i><i class=\"nx-in-svg nx-in-grid nx-in-ax nx-in-tk nx-in-at nx-in-ln nx-in-band nx-in-lbl nx-in-lk nx-in-ref nx-in-reft nx-in-mk nx-in-x nx-in-rect nx-in-val nx-in-rowl nx-in-cl nx-in-arrow nx-in-pol nx-in-cln nx-in-loop nx-in-edge nx-in-node nx-in-nl nx-in-reach nx-in-trib nx-in-agent nx-in-flow nx-in-legend nx-in-sw nx-in-note nx-in-loops nx-in-3d nx-in-cv nx-in-field nx-in-fl nx-in-fv nx-in-range nx-in-btn nx-in-err nx-in-tbl nx-in-cite\"><\/i><\/span><\/figure><\/div><\/div><\/section><section id=\"nx-sec-data\" class=\"nx-section nx-band-panel\" data-hue=\"risk\" data-variant=\"split\" aria-labelledby=\"nx-s-4\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Data<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">What the method consumes.<\/h2><p class=\"nx-lede\">Datasets and records used by decision analysis under uncertainty on this platform, with the role each plays and the label its values carry. Sources are listed in <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/research\/sources\/\">the source register<\/a>.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Data<\/th><th scope=\"col\">Role<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Data\">Scenario ensembles<\/td><td data-label=\"Role\">Futures across which options are tested<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Structured expert judgements<\/td><td data-label=\"Role\">Quantities for which data are absent<\/td><td data-label=\"Label\"><span class=\"nx-chip\">ESTIMATED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Stakeholder objective and preference records<\/td><td data-label=\"Role\">Criteria and weights<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Public appraisal guidance<\/td><td data-label=\"Role\">Discounting and valuation rules<\/td><td data-label=\"Label\"><span class=\"nx-chip\">Published statistics<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"data\" data-nxf-kind=\"data\" data-nxf-resource=\"nexus:\/\/grf\/R04\/stem\/decision-analysis\/#data\" data-nxf-title=\"Method record\" data-nxf-height=\"520\" hidden><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/grf\/R04\/stem\/decision-analysis\/#evidence\" data-nxf-title=\"Evidence\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-instrument-2\" class=\"nx-section nx-band-panel\" data-hue=\"systemic\" data-ns-layout=\"es-wide\" aria-labelledby=\"nx-s-5\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Implementation<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">From mandate to evaluation, by pillar.<\/h2><p class=\"nx-lede\">The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction.<\/p><\/div><div class=\"nx-section-body\"><figure class=\"nx-in nx-fk\" id=\"nx-in-foresight-stem-decision-analysis-1\" aria-label=\"From mandate to evaluation, by pillar\"><ol class=\"nx-in-steps\"><li><strong>Mandate and problem framing<\/strong> <span class=\"nx-in-cite\">Competent authority (outside the programme)<\/span><br>A competent authority frames the problem and the mandate under its own rules. <span class=\"nx-in-cite\">Howlett, Ramesh and Perl (2009)<\/span><\/li><li><strong>Evidence and system model<\/strong> <span class=\"nx-in-cite\">Foundry<\/span><br>The system is modelled with its feedbacks, data and stated limits. <span class=\"nx-in-cite\">OECD (2014), principle 2<\/span><\/li><li><strong>Options appraised with scenarios<\/strong> <span class=\"nx-in-cite\">Foundry<\/span><br>Instruments are compared under scenarios, with uncertainty shown. <span class=\"nx-in-cite\">Hood (1983)<\/span><\/li><li><strong>Exercise with stakeholders<\/strong> <span class=\"nx-in-cite\">Universe<\/span><br>The options are tested in an exercise with those who would implement and bear them. <span class=\"nx-in-cite\">OECD (2014), principle 3<\/span><\/li><li><strong>Standard or guidance drafted<\/strong> <span class=\"nx-in-cite\">Nexus Standards<\/span><br>What works is codified as a standard or guidance, open to comment. <span class=\"nx-in-cite\">Nexus Standards process<\/span><\/li><li><strong>Decision by the authority<\/strong> <span class=\"nx-in-cite\">Competent authority (outside the programme)<\/span><br>The authority decides, outside the programme, with the evidence on record. <span class=\"nx-in-cite\">Howlett, Ramesh and Perl (2009)<\/span><\/li><li><strong>Capacity and training<\/strong> <span class=\"nx-in-cite\">Risk Academy<\/span><br>Those who implement are trained on the decided instrument and its data. <span class=\"nx-in-cite\">Sendai Framework (2015), priority 2<\/span><\/li><li><strong>Monitoring and public report<\/strong> <span class=\"nx-in-cite\">Reports<\/span><br>Indicators are published with sources, limits and corrections. <span class=\"nx-in-cite\">OECD (2014), principle 5<\/span><\/li><li><strong>Evaluation and revision<\/strong> <span class=\"nx-in-cite\">Nexus Standards<\/span><br>Results return to the standard and the model: the cycle closes. <span class=\"nx-in-cite\">Howlett, Ramesh and Perl (2009)<\/span><\/li><\/ol><h4 class=\"nx-h4\">Methods<\/h4><ol class=\"nx-in-meth\"><li>Policy cycle <span class=\"nx-in-cite\">Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press<\/span><\/li><li>Governance of critical risks <span class=\"nx-in-cite\">OECD (2014), Recommendation of the Council on the Governance of Critical Risks<\/span><\/li><li>Layered drawing of directed graphs <span class=\"nx-in-cite\">Sugiyama, Tagawa and Toda (1981), IEEE SMC 11<\/span><\/li><\/ol><figcaption class=\"nx-caption\">From mandate to evaluation, by pillar: the steps as recorded, each with its pillar; sources as cited on each step.<\/figcaption><div class=\"nx-in-pls\"><p class=\"nx-eyebrow\">Across the six pillars, led by Nexus Consortium<\/p><ul class=\"nx-in-pl\" aria-label=\"Where this instrument connects across the pillars\"><li data-pillar=\"labs\" data-hue=\"social\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Experiments<\/span> <a class=\"nx-link\" href=\"https:\/\/therisk.global\/nexus-labs\/\">Labs<\/a><\/li><li data-pillar=\"foundry\" data-hue=\"infrastructure\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Built in<\/span> <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/foundry\/\">Foresight Nexus in Foundry<\/a><\/li><li data-pillar=\"universe\" data-hue=\"water\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Tested at<\/span> <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/universe\/\">Foresight Nexus in Universe<\/a><\/li><li data-pillar=\"standards\" data-hue=\"biodiversity\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Codified in<\/span> <a class=\"nx-link\" href=\"https:\/\/nexustandards.com\/systemic-risk\/\">Systemic Risks in Standards<\/a><\/li><li data-pillar=\"reports\" data-hue=\"energy\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Published in<\/span> <a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/reports\/\">Foresight Nexus in Reports<\/a><\/li><li data-pillar=\"academy\" data-hue=\"risk\"><span class=\"nx-pl-dot\" aria-hidden=\"true\"><\/span><span class=\"nx-in-plv\">Taught in<\/span> <a class=\"nx-link\" href=\"https:\/\/risksacademy.com\/risk-science\/\">Faculty of Risk Science and Methods in Academy<\/a><\/li><\/ul><\/div><span class=\"nx-in-keep\" hidden><i data-c=\"c1\"><\/i><i data-c=\"c2\"><\/i><i data-c=\"c3\"><\/i><i data-c=\"c4\"><\/i><i data-c=\"c5\"><\/i><i data-c=\"c6\"><\/i><i data-c=\"l0\"><\/i><i data-c=\"l1\"><\/i><i data-c=\"l2\"><\/i><i data-c=\"l3\"><\/i><i data-c=\"l5\"><\/i><i data-c=\"h3\"><\/i><i data-c=\"neg\"><\/i><i data-c=\"on0\"><\/i><i data-c=\"on1\"><\/i><i data-l=\"0\"><\/i><i data-l=\"1\"><\/i><i data-l=\"2\"><\/i><i data-l=\"3\"><\/i><i data-l=\"4\"><\/i><i data-l=\"5\"><\/i><i data-on=\"0\"><\/i><i data-on=\"1\"><\/i><i data-pol=\"p\"><\/i><i data-pol=\"n\"><\/i><i data-k=\"R\"><\/i><i data-k=\"B\"><\/i><i data-k=\"dash\"><\/i><i data-dash=\"true\"><\/i><i data-view=\"result\"><\/i><i data-nxi-live=\"on\"><\/i><i data-nxi-live=\"off\"><\/i><i class=\"nx-in-svg nx-in-grid nx-in-ax nx-in-tk nx-in-at nx-in-ln nx-in-band nx-in-lbl nx-in-lk nx-in-ref nx-in-reft nx-in-mk nx-in-x nx-in-rect nx-in-val nx-in-rowl nx-in-cl nx-in-arrow nx-in-pol nx-in-cln nx-in-loop nx-in-edge nx-in-node nx-in-nl nx-in-reach nx-in-trib nx-in-agent nx-in-flow nx-in-legend nx-in-sw nx-in-note nx-in-loops nx-in-3d nx-in-cv nx-in-field nx-in-fl nx-in-fv nx-in-range nx-in-btn nx-in-err nx-in-tbl nx-in-cite\"><\/i><\/span><\/figure><\/div><\/div><\/section><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-2\" data-tone=\"alt\" data-hue=\"risk\" aria-label=\"Validation, Instruments and commitments, Connections, Stewardship\"><div class=\"nx-container\"><div class=\"nx-hm-band nx-band\" data-nx-tabs=\"true\" data-active=\"p1\"><div class=\"nx-tablist nx-hm-tabs\" role=\"tablist\" aria-label=\"Validation, Instruments and commitments, Connections, Stewardship\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-1\" aria-controls=\"nx-sec-checks\" aria-selected=\"true\" data-key=\"p1\">Validation<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-2\" aria-controls=\"nx-sec-audience\" aria-selected=\"false\" data-key=\"p2\">Instruments and commitments<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-3\" aria-controls=\"nx-sec-connections\" aria-selected=\"false\" data-key=\"p3\">Connections<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-4\" aria-controls=\"nx-sec-stewardship\" aria-selected=\"false\" data-key=\"p4\">Stewardship<\/button><\/div><section id=\"nx-sec-checks\" class=\"nx-section nx-band-panel\" data-hue=\"risk\" data-variant=\"stack\" aria-labelledby=\"nx-s-6\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-1\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Validation<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">How results are checked.<\/h2><p class=\"nx-lede\">Analyses are checked through <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 sensitivity-analysis\" data-tk=\"Nexus risk vocabulary\" data-td=\"Testing how much a model's outputs change when inputs or assumptions change, to identify which drive results.\" data-ts=\"NRS-C1\" data-tr=\"draft\">sensitivity analysis<\/a>, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"ledger\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Check<\/th><th scope=\"col\">How it is done<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Check\">Sensitivity to values<\/td><td data-label=\"How it is done\">Results are re-run with alternative weights and discount rates and the effect is reported<\/td><\/tr><tr><td data-label=\"Check\">Expert calibration<\/td><td data-label=\"How it is done\">Where possible, experts answer seed questions with known answers to weight or check their judgements<\/td><\/tr><tr><td data-label=\"Check\">Scenario sampling adequacy<\/td><td data-label=\"How it is done\">The ensemble is checked for coverage so robustness is not claimed over a narrow set of futures<\/td><\/tr><tr><td data-label=\"Check\">Traceability<\/td><td data-label=\"How it is done\">Each result traces to stated objectives, options and assumptions that reviewers can examine<\/td><\/tr><\/tbody><\/table><\/div><p class=\"nx-note nx-mt-3\">Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.<\/p><\/div><\/div><\/section><section id=\"nx-sec-audience\" class=\"nx-section nx-band-panel\" data-hue=\"systemic\" aria-labelledby=\"nx-s-7\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Instruments and commitments<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">How decision analysis in foresight is governed: instruments, mandates and commitments.<\/h2><p class=\"nx-lede\">The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-au\" data-au-voice=\"governance\" data-au-n=\"1\"><figure class=\"nx-au-c\" data-au-fig=\"instrument-matrix\"><h3 class=\"nx-h4\">Policy instrument matrix<\/h3><p class=\"nx-p nx-au-what\">The kinds of instrument available on decision analysis in foresight, by level of government and cooperation.<\/p><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Instrument type<\/th><th scope=\"col\">Local<\/th><th scope=\"col\">National<\/th><th scope=\"col\">Regional<\/th><th scope=\"col\">Global<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Instrument type\"><strong>Regulatory<\/strong><\/td><td data-label=\"Local\">Zoning, building codes<\/td><td data-label=\"National\">Laws, standards, licensing<\/td><td data-label=\"Regional\">Harmonised rules<\/td><td data-label=\"Global\">Conventions and treaties<\/td><\/tr><tr><td data-label=\"Instrument type\"><strong>Economic<\/strong><\/td><td data-label=\"Local\">Local levies, grants<\/td><td data-label=\"National\">Budget lines, taxes, insurance schemes<\/td><td data-label=\"Regional\">Risk pools, regional funds<\/td><td data-label=\"Global\">Financing mechanisms<\/td><\/tr><tr><td data-label=\"Instrument type\"><strong>Information<\/strong><\/td><td data-label=\"Local\">Local warnings<\/td><td data-label=\"National\">Disclosure, early warning, statistics<\/td><td data-label=\"Regional\">Data sharing arrangements<\/td><td data-label=\"Global\">Global monitoring and reporting<\/td><\/tr><tr><td data-label=\"Instrument type\"><strong>Institutional<\/strong><\/td><td data-label=\"Local\">Local committees<\/td><td data-label=\"National\">Lead agencies, coordination councils<\/td><td data-label=\"Regional\">Regional bodies and secretariats<\/td><td data-label=\"Global\">Multilateral mandates<\/td><\/tr><tr><td data-label=\"Instrument type\"><strong>Cooperative<\/strong><\/td><td data-label=\"Local\">Community agreements<\/td><td data-label=\"National\">Partnership compacts<\/td><td data-label=\"Regional\">Memoranda and joint programmes<\/td><td data-label=\"Global\">Agreements and joint commitments<\/td><\/tr><\/tbody><\/table><\/div><figcaption class=\"nx-caption\"><span>A typology after the OECD Recommendation on the Governance of Critical Risks; examples of instrument types, not an inventory of any country&#8217;s measures.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-chips nx-au-fw\" aria-label=\"Frameworks cited\"><span class=\"nx-chip\">Sendai Framework for Disaster Risk Reduction \u00b7 UNDRR<\/span><span class=\"nx-chip\">Paris Agreement \u00b7 UNFCCC<\/span><span class=\"nx-chip\">2030 Agenda and the Sustainable Development Goals \u00b7 United Nations<\/span><span class=\"nx-chip\">International Health Regulations \u00b7 WHO<\/span><\/div><\/div><\/div><\/section><section id=\"nx-sec-connections\" class=\"nx-section nx-band-panel\" data-hue=\"risk\" data-variant=\"split\" aria-labelledby=\"nx-s-8\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Connections<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Topics that rely on this method.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/horizon-scanning\/\"><span>Horizon scanning<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/strategic-scenarios\/\"><span>Strategic scenarios<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/deep-uncertainty\/\"><span>Deep uncertainty<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/technology-futures\/\"><span>Technology futures<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/geopolitical-futures\/\"><span>Geopolitical futures<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/demographic-and-social-futures\/\"><span>Demographic and social futures<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/future-generations\/\"><span>Future generations<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/globalriskforum.com\/foresight\/topics\/foresight-in-decisions\/\"><span>Foresight in decisions<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-stewardship\" class=\"nx-section nx-band-panel\" data-hue=\"systemic\" data-variant=\"split\" aria-labelledby=\"nx-s-9\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Stewardship<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Who maintains the method.<\/h2><p class=\"nx-lede\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/risk-management\/\">Systemic Risk Management<\/a> stewards decision analysis under uncertainty for the Consortium and reviews how it is applied across platforms.<\/p><\/div><div class=\"nx-section-body\"><p class=\"nx-p\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/decision-analysis\/\">Canonical page: Decision analysis under uncertainty<\/a><\/p><\/div><\/div><\/section><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-3\" data-hue=\"risk\" aria-label=\"Connected, Questions\"><div class=\"nx-container\"><div class=\"nx-hm-band nx-band\" data-nx-tabs=\"true\" data-active=\"p1\"><div class=\"nx-tablist nx-hm-tabs\" 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href=\"https:\/\/therisk.global\/risk-management\/stem\/decision-analysis\/\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Steward platform<\/span><span class=\"nx-dest-host\"><abbr title=\"The Global Centre for Risk and Innovation\">GCRI<\/abbr><\/span><\/span><span class=\"nx-dest-title\">Decision analysis for risk management<\/span><span class=\"nx-dest-why\">Systemic Risk Management stewards this method.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-s-11-sec\" class=\"nx-section nx-band-panel\" data-hue=\"systemic\" aria-labelledby=\"nx-s-11\" role=\"tabpanel\" data-band-tab=\"nx-band-3-tab-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">11<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What are the limits of decision analysis under uncertainty in this field?<\/summary><div class=\"nx-answer\">Results depend on elicited probabilities and preferences that may be biased. 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