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Program Overview and Strategic Framing for Location Decisions

Course Orientation and Strategic Objectives for Weighted-Factor Rating in Location Decisions

Translating Business Strategy into Decision Criteria and Constraints

Model Foundations: Criteria, Weights, and Scales

Designing Measurable Criteria Across Qualitative and Quantitative Dimensions

Weighting Schemes: Deriving and Validating Relative Importance

Scoring Scales, Normalization, and Data Readiness

Model Construction and Calculation Mechanics

From Raw Data to Weighted Scores: The End-to-End Pipeline

Qualitative Evidence Integration and Expert Judgment

Risk, Uncertainty, and Validation

Sensitivity Analysis, Scenario Testing, and Robustness Checks

Bias Mitigation, Validation, and Compliance

Deployment, Communication, and Scaling

Operationalizing the Decision: Workflows, Governance, and Reporting

Customization and Scaling Across Industries and Geographies

Capstone and Practice Assessments

Capstone Workshop: Build and Present a Weighted-Factor Rating Model

Knowledge Check 1: Foundations and Criteria Design

Knowledge Check 2: Weighting Methods and Bias Control

Knowledge Check 3: Scales and Normalization

Knowledge Check 4: Calculation Mechanics and Aggregation

Knowledge Check 5: Qualitative Evidence and Expert Judgment

Knowledge Check 6: Sensitivity Analysis and Scenarios

Knowledge Check 7: Validation and Compliance

Knowledge Check 8: Deployment and Reporting

Knowledge Check 9: Customization and Scaling

Knowledge Check 10: Integrated Capstone Assessment

Make confident, explainable site selection choices with Weighted-Factor Rating Models: Designing Robust, Transparent Location Decisions. This practical course guides supply chain and operations leaders through an end-to-end methodology for evaluating greenfield sites, consolidations, nearshoring, and network redesigns. You will translate strategy into measurable criteria, balance qualitative and quantitative evidence, and build a defensible model that stands up to executive review, audit, and post-decision scrutiny. Learn how to craft non-overlapping criteria, derive weights using proven methods (direct allocation, swing weighting, pairwise), normalize heterogeneous data, and convert expert judgment into calibrated, traceable scores. Then pressure-test outcomes with sensitivity, scenarios, and robustness checks to understand when and why rankings change. Finally, operationalize your decision with governance, reporting, and scalable templates adaptable across industries and geographies. By the capstone, you will construct and present a complete weighted-factor model, run sensitivity analyses, and deliver an executive-ready recommendation with risks and mitigations—equipping you to make faster, clearer, and more resilient location decisions.

Weighted-Factor Rating Models: Designing Robust, Transparent Location Decisions

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            <p>Location choices shape cost structures, service levels, resilience, and brand reputation for years—sometimes decades. This course equips supply chain and operations managers to design and defend robust, transparent location decisions using weighted‑factor rating models. You will translate strategy into auditable criteria and constraints, integrate qualitative judgment with quantitative evidence, and construct a repeatable analytics pipeline that withstands executive scrutiny, regulatory review, and scenario volatility. A running case thread anchors the learning experience, guiding you from framing a real siting problem through end‑to‑end model build, testing, and communication of a recommendation.</p>

<p>The program begins by aligning strategic objectives with the decision context, mapping weighted‑factor methods to common scenarios such as greenfield expansion, consolidation, nearshoring, and full network redesign. You will formalize decision scope, alternatives, and must‑have versus nice‑to‑have requirements; elicit stakeholder objectives, risk appetite, and ESG commitments; and define a criteria taxonomy spanning cost, service, risk, workforce, infrastructure, regulatory, sustainability, and community impact. With model foundations in place, you will design measurable, non‑overlapping criteria; choose scoring scales and normalization methods; and derive validated weights using techniques from direct allocation and swing weighting to AHP‑style pairwise comparisons—while actively mitigating anchoring and dominance biases and documenting rationales for auditability.</p>

<p>Building on these foundations, you will implement calculation mechanics that convert raw data into normalized, weighted composite scores, structure the model with templates and version control, and integrate qualitative evidence through calibrated rubrics, confidence ratings, panel methods, and Delphi rounds—capturing dissent and issues for governance. A dedicated risk and validation module develops skill in one‑way and multi‑way sensitivity, scenario design for macroeconomic and disruption factors, stress testing, and switch‑point analysis to reveal where rankings change and why. You will also address compliance expectations by instituting documentation standards, cross‑validation against benchmarks, and alignment with procurement and ESG requirements.</p>

<p>The course concludes with deployment practices: decision gates and RACI, update cadence, dashboards for executives, technical appendices for analysts, and change management with KPI back‑testing. You will learn to tailor criteria, weights, and aggregation rules to industry and geography, and to scale models via modular templates for rapid reuse. Knowledge checks reinforce each stage—from criteria design and weighting methods to normalization, aggregation, qualitative integration, sensitivity, validation, and reporting—culminating in a capstone where you build, test, and present a complete weighted‑factor rating model, delivering an evidence‑based site recommendation with risk mitigations and an audit‑ready record.</p>
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