Run Operations And Supply Chains On Evidence
Firm profitability — from 72 books.
Mike West, Editor · Leading With Data · leadingwithdata.guide/guides/operations-analytics
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Run Operations And Supply Chains On Evidence
Firm profitability — from 72 books.
Mike West, Editor · Leading With Data · leadingwithdata.guide/guides/operations-analytics
The problem
Firm profitability and financial erodes when it is left to instinct instead of method.
You were taught the moves piecemeal, never the whole model.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
The model
- 01Quantitative Modeling & Analytics Application
- 02Problem Formulation & Model Fidelity
- 03Resource & Problem Constraints
- 04Strategic Alignment of Operations
- 05Data Quality & Governance
- 06Data Warehouse / Analytics Infrastructure
- 07Analytical Capability & Insight
- 08Demand Forecasting Process & Accuracy
How it grows
- New to the role0–1 yr
- Running the function1–3 yr
- Shaping the whole3+ yr
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
Step 1 of 5 · Quantitative Modeling & Analytics Application
The analytics tier (descriptive/predictive/prescriptive) must be chosen from the decision, not the data you happen to have.
Misconception
Practitioners believe a more sophisticated technique (deep learning over linear programming) automatically yields better operational decisions.
Reality
Method power is worthless without a decision it changes; a simple prescriptive model that a planner will trust and execute beats a black-box predictor that sits unused.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
Step 2 of 5 · Problem Formulation & Model Fidelity
The objective function is a policy statement—get stakeholders to sign off on it in words.
Misconception
Practitioners treat formulation as a quick preamble to the 'real work' of solving the model.
Reality
Formulation is where most modeling failures are born and fixed; the objective function and constraint set silently encode assumptions that dominate every downstream number.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
Step 3 of 5 · Resource & Problem Constraints
A constraint's shadow price tells you what relaxing it is worth—compute it before accepting the limit.
Misconception
Practitioners assume constraints are fixed facts of the environment rather than choices some of which can be relaxed.
Reality
Many binding constraints are policy or contract artifacts; the highest-leverage analysis often targets loosening the one constraint that limits the whole system.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
Step 4 of 5 · Strategic Alignment of Operations
Every operational metric should trace to how the firm competes; orphan metrics signal misalignment.
Misconception
Practitioners believe operational excellence—lower cost, higher efficiency—is universally good regardless of strategy.
Reality
A cost-minimizing supply chain actively harms a firm competing on responsiveness or product freshness; the right operational objective is derived from how the business wins, not from generic efficiency.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
Step 5 of 5 · Data Quality & Governance
Data quality is a governed, continuous process with named owners, not a one-time scrub.
Misconception
Practitioners think data quality is a cleanup task to run before a project, not an ongoing governed process.
Reality
Data decays continuously as processes, SKUs, and systems change; without ownership and stewardship, quality regresses and models silently drift.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
A framework to use
Analytic Hierarchy Process (AHP) for Supplier Selection
This framework is part of the full guide. See the guide →
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
The cheat sheet
- Quantitative Modeling & Analytics ApplicationThe analytics tier (descriptive/predictive/prescriptive) must be chosen from the decision, not the data you happen to have.
- Problem Formulation & Model FidelityThe objective function is a policy statement—get stakeholders to sign off on it in words.
- Strategic Alignment of OperationsEvery operational metric should trace to how the firm competes; orphan metrics signal misalignment.
- Data Quality & GovernanceData quality is a governed, continuous process with named owners, not a one-time scrub.
- Demand Forecasting Process & AccuracyMeasure Forecast Value Added, not just accuracy—beating the naive baseline is the bar.
- Demand & Process Variability / UncertaintySafety stock is driven by variance and tails, not by average demand.
- Inventory Policy & Safety StockSafety stock is a function of variability and service target, not a fixed days-of-supply.
- Service Level & Stockout RiskFill rate and cycle service level are different metrics; publish which one your targets refer to.
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data
Sources
- Business Applications of Operations Research — Bodhibrata Nag
- Data Analysis Python Excel for Supply Chain The ultimate analytics guide for Supply Chain 2024 (Supply Chain Analytica) — Bisette, Vincent Publishing etc.
- Data Science for Supply Chain Forecasting — Nicolas Vandeput
- Data Warehouse and Data Mining — Jugnesh Kumar
- Inventory and Production Management in Supply Chains, Fourth Edition — Edward A. Silver, David F. Pyke etc.
- Inventory Optimization Models and Simulations — Nicolas Vandeput
- Lean but agile rethink workforce planning and gain a true competitive edge — Rothwell, William J.Graber etc.
- Lean Analytics: Use Data to Build a Better Startup Faster — Alistair Croll, Benjamin Yoskovitz
- Lean Construction
- The Six Sigma Handbook, Third Edition — Paul Keller Thomas Pyzdek [Thomas Pyzdek etc.
+ 62 more sources in the full guide
Run Operations And Supply Chains On Evidence · Mike West, Editor · Leading With Data