{"schema_version":1,"research_id":"eoa_inverse_innovation_exp04_external_evaluation_20260802","source_assessment_id":"layer_decay_and_expiration_management__logistics_supply_chain:RETRIEVAL_FIRST:v0","cell_id":"layer_decay_and_expiration_management__logistics_supply_chain","search_queries":["manual forecast adjustments supply chain harmful overrides research 60000 forecasts","site:docs.aws.amazon.com supply chain demand planning forecast override start end date reason code","site:docs.oracle.com service parts planning retain manual forecast overrides planning time fence","site:help.sap.com IBP manage manual forecast adjustments planning notes overrides","judgmental forecast adjustments supply chain companies primary research 60000 Good and Bad Judgment in Forecasting PDF","forecast overrides persistence supply chain planning governance stale override research","demand planning forecast value added manual override process best practice official","supply chain planning manual overrides audit trail reason code official product documentation","EP4528530A1 planning scenario override validity period snapshot chain","planning override dependency committed orders allocation forecast override supply chain patent","forecast override audit history reason user start end date planning system","demand planning override workflow approval expiry renewal","site:ptc.com/en/support/article/CS265557 \"Need to audit SKU Overrides\"","site:ptc.com \"SKU Overrides\" \"Audit Trail\"","site:bls.gov employer costs employee compensation professional occupations December 2025 per hour","site:bls.gov May 2025 software developers median annual wage management analysts","AWS Supply Chain pricing demand planning user pricing 2026 official"],"sources":[{"source_id":"S1","title":"Demand plan - AWS Supply Chain","publisher":"Amazon Web Services","url":"https://docs.aws.amazon.com/connect-decisions/legacy/userguide/changing_category.html","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"n.d.","accessed_at":"2026-08-02","claims_supported":["AWS manually entered forecast overrides are automatically saved and reapplied in the next planning cycle.","Overrides require a reason code; imported overrides also require start and end dates.","The interface exposes hierarchy-wide effects and prior changes, and published demand plans can feed downstream processes."]},{"source_id":"S2","title":"AWS Supply Chain adds new override retention capability","publisher":"Amazon Web Services","url":"https://aws.amazon.com/about-aws/whats-new/2023/09/aws-supply-chain-override-retention-capability/","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"2023-09-14","accessed_at":"2026-08-02","claims_supported":["AWS introduced automatic cross-cycle saving and reapplication of manual forecast overrides.","Demand planners are the identified users and can manage retained overrides in a unified view.","The feature responds to recurring manual effort around adjustments for promotions, seasonality, and other demand variations."]},{"source_id":"S3","title":"Oracle Service Parts Planning Implementation and User's Guide","publisher":"Oracle","url":"https://docs.oracle.com/cd/E26401_01/doc.122/e48778/T515331T515343.htm","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"n.d.","accessed_at":"2026-08-02","claims_supported":["Oracle permits manual overrides to be discarded, retained, or retained only within a planning time fence on subsequent plan runs.","Retained overrides are reapplied over a newly processed forecast.","Forecast overrides can feed another service-parts plan that recommends replenishments, establishing downstream operational consequences."]},{"source_id":"S4","title":"Guide: Modify a demand forecast manually","publisher":"Microsoft","url":"https://learn.microsoft.com/en-us/dynamics365/supply-chain/master-planning/tasks/modify-demand-forecast-manually","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"2025-06-17","accessed_at":"2026-08-02","claims_supported":["Production planners can create, edit, delete, and publish demand-forecast lines in Dynamics 365.","Manual forecast modification is an established supply-chain-planning workflow, including bulk editing through Excel."]},{"source_id":"S5","title":"What If Scenario Planning - Setup (EP 4528530 A1)","publisher":"European Patent Office","url":"https://data.epo.org/publication-server/rest/v1.2/publication-dates/2025-03-26/patents/EP4528530NWA1/document.pdf","source_class":"GOVERNMENT_OR_REGULATOR","publication_date":"2025-03-26","accessed_at":"2026-08-02","claims_supported":["Planning overrides can be represented with base and scenario snapshot chains and explicit validity periods.","The described system propagates changes to dependent computed locations and falls back to base-version values where no override applies.","The system preserves versions and uses null snapshots as deletion markers, overlapping with validity, dependency, fallback, and reversible-history components."]},{"source_id":"S6","title":"Supply Chain Forecasting: Theory, Practice, their Gap and the Future","publisher":"Lancaster University / European Journal of Operational Research","url":"https://eprints.lancs.ac.uk/id/eprint/78811/1/EJOR_review_paper_R2_manuscript.pdf","source_class":"AUTHORITATIVE_SECONDARY","publication_date":"2016","accessed_at":"2026-08-02","claims_supported":["Judgmental adjustment is common, but results across firms and adjustment types are mixed.","Evidence from more than 60,000 forecasts found that small adjustments often damaged accuracy, positive adjustments were less likely to help, and weekly adjustments reduced accuracy in one retailer.","The review recommends reasons, tracking, monitoring, evaluation, and authorization mechanisms, and reports weak evidence about adjustment rationales and successive interventions.","Forecasts influence replenishment, transport, and production decisions, so evaluation should include operational utility rather than forecast accuracy alone."]},{"source_id":"S7","title":"Profit Implications of Judgmental Adjustments to Forecast Inputs: Evidence from a Large-Scale Field Experiment","publisher":"INFORMS / Management Science","url":"https://pubsonline.informs.org/doi/10.1287/mnsc.2024.06321","source_class":"PRIMARY_RESEARCH","publication_date":"2025-07-25","accessed_at":"2026-08-02","claims_supported":["A large-scale field experiment at an automotive spare-parts retailer found forecast-input overrides increased profitability by 4.92 percent on average.","Benefits varied with SKU margin, lifecycle, and supplier size.","Forecast accuracy alone did not capture profit effects, countering blanket expiration and supporting stratified operational evaluation."]},{"source_id":"S8","title":"Oracle Demantra Sales and Operations Planning User Guide: Sales and Operations Planning Workflows","publisher":"Oracle","url":"https://docs.oracle.com/cd/E18727-01/doc.121/e10533/T506362T506367.htm","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"2010","accessed_at":"2026-08-02","claims_supported":["Oracle provides workflows to archive approved demand plans, approve or revoke scenarios, detect exceptions, and export consensus forecasts to downstream planning applications.","Only S&OP managers can execute specified approval workflows, identifying an organizational authorizer.","Administrators are expected to configure workflows around the analysts and managers performing approval tasks."]},{"source_id":"S9","title":"When to Override Demand Priority","publisher":"Oracle","url":"https://docs.oracle.com/en/cloud/saas/supply-chain-and-manufacturing/26b/faubm/when-to-override-demand-priority.html","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"2026","accessed_at":"2026-08-02","claims_supported":["Order-priority overrides can redistribute supply.","Oracle warns that lower-priority orders' planning results can worsen after such an override, demonstrating customer-allocation safety consequences."]},{"source_id":"S10","title":"Plan Improvement Actions - Amazon Connect Decisions","publisher":"Amazon Web Services","url":"https://docs.aws.amazon.com/connect-decisions/latest/userguide/demand-planning-plan-improvement-actions.html","source_class":"OFFICIAL_PRODUCT_DOCUMENTATION","publication_date":"2026","accessed_at":"2026-08-02","claims_supported":["AWS refreshes plan-improvement actions every plan run as new data arrives.","The workflow requests business context, applies validated corrections, and can update forecast-override rules for a bounded period such as three months.","This is adjacent prior art for periodic revalidation and context-backed planning-rule changes."]},{"source_id":"S11","title":"Employer Costs for Employee Compensation - December 2025","publisher":"U.S. Bureau of Labor Statistics","url":"https://www.bls.gov/news.release/archives/ecec_03202026.htm","source_class":"GOVERNMENT_OR_REGULATOR","publication_date":"2026-03-20","accessed_at":"2026-08-02","claims_supported":["December 2025 total employer compensation averaged $77.39 per hour for management, professional, and related civilian occupations and $87.21 for management, business, and financial occupations.","The figures provide a public resource-equivalent labor basis for broad 2026 cost bands."]},{"source_id":"S12","title":"Amazon Connect Decisions Pricing","publisher":"Amazon Web Services","url":"https://aws.amazon.com/products/connect/decisions/pricing/","source_class":"COMMERCIAL_FIRST_PARTY","publication_date":"2026","accessed_at":"2026-08-02","claims_supported":["Pricing is based on teammate type rather than user count and requires contacting AWS for a needs-specific quote.","The product is represented as working with existing systems and workflows without large upfront commitment.","Public documentation does not expose enough pricing detail to estimate licensing precisely."]}],"problem_evidence":{"support":"MODERATE","rationale":"Manual forecast and priority overrides clearly exist, can persist across planning cycles, and can affect replenishment and allocation. Large empirical literatures show that adjustment value is heterogeneous and that some adjustments damage performance. However, no opened source measures the narrower prevalence of old, rationale-less overrides remaining active after their justifying disruption ends, so the exact candidate problem is plausible and consequential but not yet directly quantified.","source_ids":["S1","S2","S3","S6","S7","S9"]},"stakeholder_evidence":{"support":"MODERATE","rationale":"Demand planners, production planners, planning administrators, and S&OP managers are identifiable operators and authorizers. Official systems assign scenario approval to S&OP managers, while the research review explicitly calls for justification, monitoring, and authorization controls. The evidence establishes role-level pull, but no named enterprise has publicly requested the complete lease-plus-dependency-gate-plus-quarantine workflow or committed funding.","source_ids":["S1","S2","S4","S6","S8","S10"]},"prior_art":{"proximity":"SUBSTANTIAL_COLLISION","closest_analogues":[{"name":"AWS cross-cycle forecast-override lifecycle","similarity":"Combines retained overrides, mandatory reason codes, start and end dates for imported overrides, hierarchy impact visibility, prior-change history, and downstream publication.","remaining_difference":"The documentation does not show mandatory affirmative renewal by the named owner using fresh evidence, an automated gate against live committed-order or allocation dependencies, or a recoverable post-expiry quarantine.","source_ids":["S1","S2"]},{"name":"Oracle Service Parts Planning override-retention controls","similarity":"Controls whether overrides survive later plan runs, limits retention with a planning time fence, falls back to regenerated forecasts, and applies retained overrides to replenishment planning.","remaining_difference":"The control is plan-level and overwrite-oriented rather than a per-override renewable lease with owner evidence, live-commitment gating, and reversible post-expiry quarantine.","source_ids":["S3"]},{"name":"Validity-bounded scenario snapshot chains in EP 4528530 A1","similarity":"Uses planning override indicators, validity periods, base-value fallback, dependent-value propagation, versioned snapshots, and deletion markers.","remaining_difference":"It is primarily a data representation and scenario-computation design; it does not establish accountable renewal, commitment-specific expiry blocking, or a planner-authorized quarantine workflow.","source_ids":["S5"]},{"name":"Amazon Connect Decisions plan-improvement actions","similarity":"Refreshes review actions each planning run, requests business context, applies validated corrections, and can impose bounded forecast-override rules.","remaining_difference":"It does not document per-override default expiry, named-owner renewal, committed-order dependency blocking, or recoverable quarantine.","source_ids":["S10"]},{"name":"Oracle Demantra approval and archival workflows","similarity":"Provides manager-authorized scenario approval, revocation, exception review, archiving, and downstream export.","remaining_difference":"The workflow governs whole plans or scenarios rather than expiring individual overrides through the proposed linked controls.","source_ids":["S8"]}],"distinctive_claim_remaining":"For override classes with reliable identity and dependency data, a default-expiring per-override lease that requires fresh evidence from a named owner, blocks expiry on live or unresolved committed-order/allocation dependencies, and quarantines the prior value for authorized restoration will reduce the proportion of active overrides lacking a current rationale by at least 25% relative to existing periodic review, without degrading fill rate by more than 0.5 percentage points or increasing expiry-attributable service failures. These numerical thresholds are proposed test criteria, not established effects.","confidence":"MODERATE"},"implementation_evidence":{"support":"MODERATE","rationale":"Core primitives already exist separately: per-period override identity, start/end dates, reason codes, history, plan-cycle refresh, time-fence retention, base-value fallback, approval workflows, scenario archives, dependent-value propagation, and downstream publishing. A read-only retrospective can therefore be implemented through exports and joins. The critical unresolved engineering issue is whether production data can reliably link each override to live committed orders, allocations, releases, and restorations. Authority is organizational rather than inherently regulatory: S&OP/planning governance must approve policy and access. No special legal prohibition was found, but retention, access control, audit preservation, and any hard-deletion rules remain enterprise- and jurisdiction-specific. Automated expiry is unsafe until dependency-recall and service noninferiority are demonstrated.","source_ids":["S1","S3","S5","S8","S9","S10"]},"scores":{"meaningful_impact":{"score":4,"rationale":"Overrides can alter forecasts, replenishment, supply allocation, inventory, and customer service; both harmful and beneficial effects can be operationally material.","source_ids":["S3","S6","S7","S9"]},"stakeholder_pull":{"score":3,"rationale":"Demand planners and S&OP managers visibly manage, approve, and review overrides, and research calls for stronger justification and authorization. Pull for the exact integrated treatment is not directly documented.","source_ids":["S1","S6","S8","S10"]},"incremental_advantage":{"score":3,"rationale":"The combination could add accountable renewal and safer expiry to established retention controls, but most constituent capabilities are already known and incremental benefit remains untested.","source_ids":["S1","S3","S5","S10"]},"distinctiveness_plausibility":{"score":3,"rationale":"No opened source showed all three residual controls in one planning-override workflow, but bounded web search cannot exclude proprietary deployments, additional patents, or undocumented product features.","source_ids":["S1","S3","S5","S8","S10"]},"technical_implementability":{"score":4,"rationale":"Existing products demonstrate the needed metadata, histories, approval workflows, validity periods, fallbacks, and dependency propagation. Live order/allocation linkage is the principal uncertainty.","source_ids":["S1","S3","S5","S8"]},"adoption_authority_feasibility":{"score":3,"rationale":"Planning governance and S&OP managers are credible authorizers, but the workflow crosses demand, supply, allocation, IT, audit, and possibly legal-retention ownership.","source_ids":["S8","S9"]},"evidence_readiness":{"score":3,"rationale":"A shadow study is bounded and production-safe, but owner, rationale, renewal evidence, and commitment-dependency completeness are proprietary and may not be captured consistently.","source_ids":["S1","S3","S6"]},"safety_net_benefit":{"score":4,"rationale":"Dependency blocking, fallback, audit history, and quarantine directly reduce the irreversibility of mistaken expiry, although the integrated safety performance has not been tested.","source_ids":["S3","S5","S8","S9"]},"scalability":{"score":3,"rationale":"Per-override automation can scale across many SKU-location-periods, but dependency queries, review queues, rubber-stamp renewal, and heterogeneous lease rules may create operational load.","source_ids":["S1","S3","S6","S10"]}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"50K_TO_250K","scope":"Six-week read-only inventory and shadow replay of approximately 300 stratified overrides from one business unit, including planner adjudication and an analysis report.","confidence":"MODERATE","assumptions":["Existing exports or read-only APIs expose override, forecast, order, allocation, and outcome history.","Approximately 600-1,600 hours of planner, analyst, data-engineering, and governance effort.","BLS management/professional compensation is used as a resource-equivalent labor anchor; no production integration or software purchase is included."],"source_ids":["S11"]},"initial_deployment_startup":{"band_2026_usd":"250K_TO_1M","scope":"Build a nonproduction override inventory, lifecycle-state model, reminder/review workflow, dependency-query prototype, and shadow dashboard for one planning platform.","confidence":"LOW","assumptions":["Approximately 3,000-8,000 blended professional hours plus security, data-quality, and vendor-support contingencies.","The organization already licenses a planning system and can reuse its identity, history, and approval functions.","Quoted vendor licensing is excluded because public pricing is not sufficiently specific."],"source_ids":["S1","S3","S8","S11","S12"]},"operational_launch":{"band_2026_usd":"1M_TO_5M","scope":"One-business-unit production pilot with role-based access, order/allocation integrations, audit storage, quarantine/restore controls, monitoring, validation, training, and rollback procedures.","confidence":"LOW","assumptions":["Approximately 8,000-20,000 internal and external professional hours.","Includes integration and assurance contingency for multiple downstream order and allocation systems.","Excludes enterprise-wide replacement of the planning platform and excludes inventory losses caused by pilot errors."],"source_ids":["S3","S8","S9","S11","S12"]},"annual_recurring":{"band_2026_usd":"250K_TO_1M","scope":"Ongoing policy ownership, planner review time, data-quality monitoring, dependency-control maintenance, audits, support, and incremental vendor charges for one business unit.","confidence":"LOW","assumptions":["Roughly two to five full-time-equivalent resources distributed across planning, engineering, governance, and support.","Renewal volume is controlled through stratified lease rules and automation.","Vendor pricing remains quote-based and may move the result outside this band."],"source_ids":["S10","S11","S12"]}},"verified_pipeline_gates":{"externally_supported_problem":{"status":"YES","reason":"External research and official product documentation establish common manual overrides, cross-cycle persistence, mixed or harmful adjustment performance, and downstream replenishment/allocation consequences. Specific stale-override prevalence remains unmeasured but does not erase the supported problem class.","source_ids":["S1","S2","S3","S6","S7","S9"]},"externally_credible_adopter_or_authorizer":{"status":"YES","reason":"Demand planners are identifiable users, while S&OP managers and planning-governance owners have documented approval and workflow authority.","source_ids":["S1","S4","S8","S10"]},"distinct_testable_incremental_claim":{"status":"YES","reason":"The residual linked workflow is contrastive against AWS, Oracle, and snapshot-chain prior art and has specified rationale-reduction and service-noninferiority outcomes.","source_ids":["S1","S3","S5","S10"]},"bounded_next_evidence_step":{"status":"YES","reason":"A six-week, 300-override, read-only shadow replay has a fixed population, comparators, outcomes, halt rules, and falsifiers without modifying production plans.","source_ids":["S1","S3","S6","S7"]},"no_unresolved_safety_or_authority_stop":{"status":"YES","reason":"The next step is read-only, treats missing dependencies as unresolved rather than safe, and requires planning-governance authorization before any live expiry. Safety uncertainty blocks production automation but not the bounded shadow study.","source_ids":["S8","S9"]},"credible_cost_scope_and_range":{"status":"YES","reason":"The four scopes are explicitly bounded and use current public employer-compensation data, with wide bands and low confidence where vendor pricing and integration complexity are opaque.","source_ids":["S11","S12"]}},"next_evidence_step":"With approval from the demand-planning process owner, run a six-week read-only retrospective and shadow replay on 300 overrides stratified by override type, age, SKU lifecycle, margin/service class, location, and planner. Compare (A) current review/persistence, (B) simple end-date expiry without dependency gating, and (C) the proposed renewable lease plus dependency gate and quarantine. For each override, reconstruct owner, rationale currency, evidence, age, renewal eligibility, downstream orders/allocations, regenerated fallback, simulated disposition, planner-review time, and realized service/profit proxies. Have demand, supply, and allocation planners independently adjudicate a blinded sample to estimate dependency-gate recall. Advance only if rationale-less active overrides fall at least 25% versus A, C catches materially more live dependencies than B, estimated fill-rate degradation is no more than 0.5 percentage points, and no service-critical dependency is missed. Falsify or redesign if baseline rationale-less prevalence is below 5%, dependency data are unresolved for more than 10% of the sample, any service-critical dependency is missed, the reduction target is not met, or median incremental review burden exceeds 15 minutes per override. Do not deactivate, publish, release, delete, or restore any production object.","blocking_evidence":["No direct measurement of the prevalence, age distribution, or downstream distortion of active overrides whose original rationale has expired.","No demonstrated recall rate for linking overrides to live committed orders, customer allocations, replenishment releases, or indirect dependencies.","No comparative evidence that the proposed workflow outperforms simpler end dates, time fences, or periodic review.","No field evidence that renewal requirements avoid rubber-stamping and remain tolerable for planners.","No live noninferiority evidence for fill rate, stockouts, expedites, allocation stability, profitability, or restoration effectiveness.","No enterprise-specific legal, audit-retention, access-control, or permanent-disposition review.","Vendor licensing and integration costs are quote-based and organization-specific."],"research_disposition":"PROBLEM_PREVALENCE_STUDY","world_novelty_boundary":"This evaluation measured only a bounded open-web boundary. It establishes manual overrides, cross-cycle retention, start/end dates, reason codes, histories, time-fence clearing, approval and archival workflows, periodic context refresh, base-value fallback, validity-bounded snapshots, dependency propagation, and deletion markers as prior practice. It did not locate one direct source documenting the complete combination of mandatory fresh-evidence renewal by a named owner, automated gating against live committed-order or allocation dependencies, and recoverable post-expiry quarantine. World novelty, patentability, freedom to operate, market size, and realized impact remain unmeasured.","arm":"RETRIEVAL_FIRST","candidate_version":0,"controller_recommendation":{"action":"STOP_EMPIRICAL_RESEARCH_NEEDED","repairable":true,"material_progress_observed":true,"progress_targets":["Obtain a complete, deduplicated inventory for at least 300 historical overrides with owner, age, rationale, scope, and renewal evidence fields.","Quantify baseline prevalence of active overrides lacking a current rationale and determine whether it exceeds the 5% problem-falsifier threshold.","Demonstrate at least 99% dependency-gate recall on planner-adjudicated committed-order and allocation dependencies, with zero missed service-critical dependencies.","Show at least a 25% reduction in rationale-less active overrides versus current practice in shadow replay.","Show service noninferiority within a 0.5-percentage-point fill-rate margin and no increase in expiry-attributable critical failures.","Measure review burden and show median incremental effort at or below 15 minutes per override.","Secure written planning-governance ownership for lease classes, renewal authority, quarantine access, restoration, and final disposition."],"reason":"Web evidence establishes a real practice, consequential downside, credible authorizers, substantial adjacent prior art, and a narrow testable residual claim. The decisive questions—local stale-override prevalence, dependency-data completeness, planner behavior, and service safety—require proprietary historical data and shadow or live operational testing, so further bounded web search cannot resolve them."}}