Isbn: 9798276496900 - supply chain analytics with python & excel: data models, kpis, and performance systems: a comprehensive guide (6 resultados)

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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 35,42
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. Neuware - Reactive PublishingSupply chains are now data systems. The companies that win are the ones who can measure, model, forecast, and optimize faster than their competitors. This book gives you the analytical toolkit to do exactly that.Supply Chain Analytics with Python & Excel is a practical, execution-driven guide for professionals who want to turn raw operational data into performance insights, forecasting engines, and decision systems. Whether you work in procurement, logistics, inventory, operations finance, or analytics, this book shows you how to quantify the movement of goods, money, and time with clarity and precision.You'll learn how to build integrated data models, automate performance dashboards, and apply Python and Excel to solve real supply-chain problems, from inventory optimization to demand forecasting, lead-time modeling, and KPI design. Every concept is tied directly to business impact.Inside, you'll learn how to: - Build supply-chain data models in Python and Excel that track demand, flow, and performance- Design KPIs that actually diagnose bottlenecks, constraints, and hidden inefficiencies- Automate reporting, dashboards, and scenario analysis- Apply forecasting models for demand variability, seasonality, and trend detection- Optimize reorder points, safety stock, and service levels using analytics- Analyze transportation, warehousing, and fulfillment costs with data-driven logic- Construct end-to-end performance systems that link suppliers, operations, and customers- Integrate Python-driven insights into Excel workflows used across the businessUnlike traditional supply chain books that focus on theory, this guide is built for execution. Every page connects analytics to measurable operational outcomes: reduced cost, improved service level, faster cycle time, higher forecast accuracy, and system-wide stability.If you want to move beyond static reporting and become the person who builds the models, dashboards, and decision systems that supply-chain leaders rely on, this book gives you the blueprint.…

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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 36,83
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Paperback. Condición: new. Paperback. Reactive PublishingSupply chains are now data systems. The companies that win are the ones who can measure, model, forecast, and optimize faster than their competitors. This book gives you the analytical toolkit to do exactly that.Supply Chain Analytics with Python & Excel is a practical, execution-driven guide for professionals who want to turn raw operational data into performance insights, forecasting engines, and decision systems. Whether you work in procurement, logistics, inventory, operations finance, or analytics, this book shows you how to quantify the movement of goods, money, and time with clarity and precision.You'll learn how to build integrated data models, automate performance dashboards, and apply Python and Excel to solve real supply-chain problems, from inventory optimization to demand forecasting, lead-time modeling, and KPI design. Every concept is tied directly to business impact.Inside, you'll learn how to: - Build supply-chain data models in Python and Excel that track demand, flow, and performance- Design KPIs that actually diagnose bottlenecks, constraints, and hidden inefficiencies- Automate reporting, dashboards, and scenario analysis- Apply forecasting models for demand variability, seasonality, and trend detection- Optimize reorder points, safety stock, and service levels using analytics- Analyze transportation, warehousing, and fulfillment costs with data-driven logic- Construct end-to-end performance systems that link suppliers, operations, and customers- Integrate Python-driven insights into Excel workflows used across the businessUnlike traditional supply chain books that focus on theory, this guide is built for execution. Every page connects analytics to measurable operational outcomes: reduced cost, improved service level, faster cycle time, higher forecast accuracy, and system-wide stability.If you want to move beyond static reporting and become the person who builds the models, dashboards, and decision systems that supply-chain leaders rely on, this book gives you the blueprint. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Condición: New. Print on Demand.

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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 40,22
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Paperback. Condición: new. Paperback. Reactive PublishingSupply chains are now data systems. The companies that win are the ones who can measure, model, forecast, and optimize faster than their competitors. This book gives you the analytical toolkit to do exactly that.Supply Chain Analytics with Python & Excel is a practical, execution-driven guide for professionals who want to turn raw operational data into performance insights, forecasting engines, and decision systems. Whether you work in procurement, logistics, inventory, operations finance, or analytics, this book shows you how to quantify the movement of goods, money, and time with clarity and precision.You'll learn how to build integrated data models, automate performance dashboards, and apply Python and Excel to solve real supply-chain problems, from inventory optimization to demand forecasting, lead-time modeling, and KPI design. Every concept is tied directly to business impact.Inside, you'll learn how to: - Build supply-chain data models in Python and Excel that track demand, flow, and performance- Design KPIs that actually diagnose bottlenecks, constraints, and hidden inefficiencies- Automate reporting, dashboards, and scenario analysis- Apply forecasting models for demand variability, seasonality, and trend detection- Optimize reorder points, safety stock, and service levels using analytics- Analyze transportation, warehousing, and fulfillment costs with data-driven logic- Construct end-to-end performance systems that link suppliers, operations, and customers- Integrate Python-driven insights into Excel workflows used across the businessUnlike traditional supply chain books that focus on theory, this guide is built for execution. Every page connects analytics to measurable operational outcomes: reduced cost, improved service level, faster cycle time, higher forecast accuracy, and system-wide stability.If you want to move beyond static reporting and become the person who builds the models, dashboards, and decision systems that supply-chain leaders rely on, this book gives you the blueprint. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…