## Page 1 CRM y SCM Gestión de la Información Grado en Ingeniería Informática Universidad de Burgos <img>Universidad de Burgos logo</img> UNIVERSIDAD DE BURGOS José Ignacio Santos, José Manuel Galán jisantos@ ubu.es, jmgalan@ ubu.es --- ## Page 2 # Contenidos * → Relación entre ERP, CRM y SCM * → CRM * • Estrategia de negocio * • Aplicación de gestión * → SCM * • Cadena logística * • Aplicaciones de gestión * • Efecto látigo --- ## Page 3 # ERP, CRM y SCM graph TD subgraph ERP A[Administración] B[Finanzas] C[RRHH] D[Proyectos] end subgraph CRM E[Marketing] F[Ventas] G[Servicio Clientes] end subgraph SCM H[Compras] I[Logística] J[Producción] end subgraph Supply Chain Management K[Supply Chain Management] end A --- B B --- C C --- D D --- A E --- F F --- G G --- E H --- I I --- J J --- H K --- H K --- I K --- J K --- A K --- B K --- C K --- D K --- E K --- F K --- G Desde el punto de vista de SI y TI, los sistemas CRM y SCM son extensiones especializadas (y enriquecidas) en la gestión de los procesos con clientes (CRM) y los procesos con proveedores (SCM) Pueden ser módulos integrados dentro del ERP de algunos vendedores, o pueden ser aplicaciones de gestión independientes (que deberán ser interoperables con el ERP de la empresa) La arquitectura de estos sistemas es similar a la de los sistemas ERP y su despliegue también (hosted, cloud, híbrido) --- ## Page 4 # Confusión con las nombres SCM, CRM graph TD A[SCM, CRM] --> B[Estrategia de negocio
La organización busca rediseñar sus procesos para mejorar la eficiencia operativa (SCM) y la gestión personalizada de los clientes (CRM)] A --> C[Sistema de información
Sistema de información integrado (similar a un ERP) que funciona como OLTP] B --> D[SCM, CRM] C --> D --- ## Page 5 # ¿Por qué sistemas separados? ERP, CRM, SCM comparten una arquitectura (base de datos, DBMS, lógica de aplicación), pero se separan en sistemas diferentes por diversas razones: **Especialización funcional:** La complejidad funcional de áreas como CRM y SCM supera la funcionalidad estándar que ofrece un ERP Por ejemplo, un CRM necesita manejar campañas de marketing, análisis de comportamiento, segmentación avanzada. Un SCM incorpora funcionalidades de optimización de rutas, gestión de proveedores globales, simulaciones de demanda, coordinación. **Escalabilidad tecnológica** Requerimientos operativos diferentes: los procesos CRM y SCM suelen requerir más flexibilidad, manejo de datos externos y tiempos de respuesta distintos Bases de datos separadas (aunque conectadas) por necesidades de rendimiento, y también por independencia tecnológica (de un mismo proveedor) --- ## Page 6 # CRM: lógica de negocio “CRM es una estrategia empresarial que optimiza los ingresos y la rentabilidad promoviendo la satisfacción y la fidelidad de los clientes” (Gartner). “Poner al cliente en el centro de tu negocio” El objetivo es **gestionar las relaciones con los clientes** para retener e incorporar nuevos clientes. Requiere la gestión integrada (personas, procesos, datos y tecnología) de las principales áreas relacionadas: **marketing, ventas, servicio al cliente y gestión** ¿Cómo? mediante aplicaciones CRM <img>SAP CRM logo</img> <img>Oracle CRM logo</img> --- ## Page 7 # CRM: software de gestión La aplicación CRM ofrece funcionalidades para: * **Marketing:** gestión de campañas, segmentación de clientes, Social Media (presencia en redes sociales), etc. * **Ventas:** gestión de las interacciones con clientes a través de todos los canales (tienda física, tienda web, teléfono, correo, redes, etc.): compras, devoluciones, sistemas de recomendación, etc. * **Atención al cliente:** gestión del soporte, incidencias, fidelización etc. * **Análisis** del comportamiento del cliente (data mining, ML, AI) para la personalización de servicios, investigación de mercados, predicción de ventas, etc. --- ## Page 8 # SCM: lógica de negocio SCM es una estrategia empresarial que busca mejorar los procesos logísticos entre todos los socios comerciales que participan en la satisfacción de la demanda un bien o servicio. Frente a una gestión logística tradicionalmente centrada en la gestión de los procesos logísticos internos de una empresa (flujos de bienes y de información entre la empresa, proveedores y clientes) ... Aparece el concepto de **cadena de suministro**, que pone el acento en la **colaboración** y **coordinación** necesaria entre todos los agentes que hacen posible la producción y distribución de un bien (proveedores, plantas de fabricación, centros de distribución, mayoristas, minoristas, empresas de transporte, etc.) --- ## Page 9 La gestión logística de productos Diferencias y similitudes entre estos productos <img>A white and red Nike running shoe filled with blackberries.</img> <img>A pile of red and green apples.</img> <img>A red and black ATI Radeon graphics card.</img> --- ## Page 10
Ejemplo
**How Many Countries Does It Take to Make a Coat?** To make this jacket for the U.S. market, Hong Kong garment producer Li & Fung ordered materials from factories in five countries and had them delivered to Thailand, where the jacket was stitched together. Using a network of Web sites, Li & Fung stays in touch with its worldwide suppliers and can compress the time it takes to get items into stores. <img>A diagram of a winter jacket illustrating the sourcing of components from different countries. The jacket is shown in orange, with arrows pointing to each part that lists the country responsible for that component: • Liner (top left): China, the world’s largest producer of cotton • Shell and fleece (top right): Taiwan, which specializes in making material for outdoor clothing • Hood (bottom left): Thailand, a leading exporter of imitation fur • Zipper teeth (bottom center): Japan, the globe’s biggest producer of stainless steel for zippers • Snaps (bottom right): Germany, which gave the world the snap fastener in the 1880s</img> fuente: Laudon (2012) --- ## Page 11 # Versión simplificada de la cadena logística Cadena logística tradicional (teórica) graph LR A[Ciclo de aprovisionamiento] --> B[Proveedor materia prima] B --> C[Ciclo de producción] C --> D[Productor] D --> E[Ciclo de reposición] E --> F[Mayorista (wholesaler)] F --> G[Ciclo de pedido de cliente] G --> H[Minorista (retailer)] H --> I[Cliente] <img>Cows grazing in a field under a blue sky.</img> <img>Milk bottles on a conveyor belt in a factory.</img> <img>A grocery store aisle with shelves stocked with various products.</img> <img>Two people sitting at an outdoor table drinking from bottles.</img> --- ## Page 12 Cadena logística real --- ## Page 13 # SCM: software de gestión La aplicación SCM es una extensión de las funcionalidades originales de un ERP. Las aplicaciones de SCM ofrecen las siguientes funcionalidaes (Bozarth 2008): * **Sistemas de planificación:** * E.g. planificación colaborativa de la demanda: compartir información en tiempo real sobre previsiones de ventas, inventarios y producción, con el objetivo de mejorar la toma de decisiones y reducir tanto los costos como el riesgo de desabastecimiento o sobreproducción * **Sistemas de ejecución logística:** gestionan la información de las actividades logísticas (órdenes, embarques, movimientos de productos, pago, facturación, ...) * E.g. “online tracking system” de FedEx: cada paquete está identificado con un código de barras que es leído en cada operación, y puede seguirse por los usuarios autorizados * **Sistemas de análisis y decisión inteligente para el diseño y optimización del sist. logístico:** * E.g. localización de los almacenes, tamaño de contenedores, simulación de tráfico logístico, optimización de tiempos de transporte, ... --- ## Page 14 # Ejemplo SAP SAP Integrated Business Planning system Software As A Service (SAAS) con funcionalidades de apoyo a la decisión y de planificación * ☑ **Integrated planning** - Plan at strategic and tactical levels, and then drill into operational details. * ☑ **Sales and operations planning (S&OP)** - Deliver a cross-departmental sales and operations plan that balances inventory, service levels, and profitability. * ☑ **Supply planning** - Develop rough cut capacity plans in a bucketed time series supply plan. * ☑ **Forecasting and demand management** - Get full demand transparency with short-term, mid-term, and long-term forecasting. Take advantage of best-in-class capabilities for demand sensing and statistical forecasting. * ☑ **Inventory optimization** - Prescribe inventory targets to maximize profit, while buffering for uncertainty. * ☑ **Response planning** - Create order confirmation and an adopted supply plan based on prioritized demands, allocations and supply chain constraints. * ☑ **Supply and allocations planning** - Create allocations and a supply plan based on prioritized forecast demands and supply chain constraints. * ☑ **Real-time supply chain management (SCM)** - Enable supply chain professionals to navigate, analyze, and profitably manage your entire supply chain in real time. Functional capabilities --- ## Page 15
Process: Global IBP 05/09/2013
StepStatusDate Range
Product ReviewCompleted5/9/13 – 5/11/13
Demand ReviewCompleted5/12/13 – 5/14/13
Supply ReviewCompleted5/15/13 – 5/16/13
Pre S&OP Review67%5/18/13 – 5/17/13
Executive Review5/18/13 – 5/20/13
Dashboards
**Scenario Comparison (50M)** <img>A grouped bar chart comparing three scenarios—Baseline, Upside, and Downside—across four metrics: Constrained Demand Plan Rev (blue), Projected Inventory Cost (orange), Gross Profit (green), and Operating Profit (yellow). • Baseline: Constrained Demand Plan Rev ≈ 40 M, Projected Inventory Cost ≈ 1 M, Gross Profit ≈ 22 M, Operating Profit ≈ 18 M. • Upside: Constrained Demand Plan Rev ≈ 45 M, Projected Inventory Cost ≈ 1 M, Gross Profit ≈ 23 M, Operating Profit ≈ 19 M. • Downside: Constrained Demand Plan Rev ≈ 43 M, Projected Inventory Cost ≈ 1 M, Gross Profit ≈ 21 M, Operating Profit ≈ 17 M.</img> **Top New Products** <img>A horizontal bar chart listing six new product models (z105 Phone, z102 Phone, y102 Smart Phone, x104 Smart Phone, t102 Phone, t100 Phone) with three metrics per product: Marketing Forecast Rev (blue), Marketing Forecast Profit (orange), and Operating Profit (yellow). • z105 Phone: Marketing Forecast Rev ≈ 38 M, Marketing Forecast Profit ≈ 19 M, Operating Profit ≈ 18 M. • z102 Phone: Marketing Forecast Rev ≈ 30 M, Marketing Forecast Profit ≈ 12 M, Operating Profit ≈ 14 M. • y102 Smart Phone: Marketing Forecast Rev ≈ 32 M, Marketing Forecast Profit ≈ 14 M, Operating Profit ≈ 15 M. • x104 Smart Phone: Marketing Forecast Rev ≈ 35 M, Marketing Forecast Profit ≈ 14 M, Operating Profit ≈ 15 M. • t102 Phone: Marketing Forecast Rev ≈ 25 M, Marketing Forecast Profit ≈ 11 M, Operating Profit ≈ 13 M. • t100 Phone: Marketing Forecast Rev ≈ 15 M, Marketing Forecast Profit ≈ 5 M, Operating Profit ≈ 7 M.</img> **Market Share by Family** <img>A horizontal stacked-bar chart showing market share percentage (Pct) for various product families across three time points: Q3 2013, Q4 2013, and Q1 2014. Each family has a blue bar representing Market Share Pct. • z Tablet: Q3 2013 ≈ 0.35, Q4 2013 ≈ 0.30, Q1 2014 ≈ 0.25. • z Phone: Q3 2013 ≈ 0.30, Q4 2013 ≈ 0.25, Q1 2014 ≈ 0.20. • z e-Reader: Q3 2013 ≈ 0.25, Q4 2013 ≈ 0.20, Q1 2014 ≈ 0.15. • y Smart Phone: Q3 2013 ≈ 0.30, Q4 2013 ≈ 0.25, Q1 2014 ≈ 0.20. • y Media Player: Q3 2013 ≈ 0.25, Q4 2013 ≈ 0.20, Q1 2014 ≈ 0.15. • x Tablet: Q3 2013 ≈ 0.30, Q4 2013 ≈ 0.25, Q1 2014 ≈ 0.20. • x Phone: Q3 2013 ≈ 0.25, Q4 2013 ≈ 0.20, Q1 2014 ≈ 0.15. • x e-Reader: Q3 2013 ≈ 0.20, Q4 2013 ≈ 0.15, Q1 2014 ≈ 0.10. • t Smart Phone: Q3 2013 ≈ 0.25, Q4 2013 ≈ 0.20, Q1 2014 ≈ 0.15. • t Media Player: Q3 2013 ≈ 0.20, Q4 2013 ≈ 0.15, Q1 2014 ≈ 0.10. • s Tablet: Q3 2013 ≈ 0.20, Q4 2013 ≈ 0.15, Q1 2014 ≈ 0.10. • s Phone: Q3 2013 ≈ 0.20, Q4 2013 ≈ 0.15, Q1 2014 ≈ 0.10. • s e-Reader: Q3 2013 ≈ 0.15, Q4 2013 ≈ 0.10, Q1 2014 ≈ 0.05.</img> **Consensus Revenue vs AOP** <img>A clustered bar chart comparing consensus revenue (green) to actual operating profit (yellow) across four quarters (Q3 2013, Q4 2013, Q1 2014, Q2 2014, Q3 2014). • Q3 2013: Consensus Demand Plan Rev ≈ 28 M, AOP Rev ≈ 25 M. • Q4 2013: Consensus Demand Plan Rev ≈ 28 M, AOP Rev ≈ 25 M. • Q1 2014: Consensus Demand Plan Rev ≈ 28 M, AOP Rev ≈ 45 M. • Q2 2014: Consensus Demand Plan Rev ≈ 28 M, AOP Rev ≈ 35 M. • Q3 2014: Consensus Demand Plan Rev ≈ 28 M, AOP Rev ≈ 30 M.</img> --- ## Page 16 # Ejemplo de sistema de ejecución logística: Wal-Mart <img>A circular flow diagram illustrating Wal-Mart’s inventory management system linked to Procter & Gamble’s supply-chain software. The flow starts with a Wal-Mart store where a customer buys Pampers Baby-Dry, triggering alerts that reach the distribution center and then the Procter & Gamble regional supply manager who reroutes a delivery truck labeled “RE-ROUTE # 237” to replenish the store.</img> 1. A special promotion causes Wal-Mart shoppers to snap up boxes of Pampers Baby-Dry. 2. Each box of Pampers has an RFID tag. Shelf-mounted scanners alert the stockroom of urgent need for restock. 3. Wal-Mart’s inventory management system tracks and links its in-store stock and its warehouse stock, prompting quicker replenishment and providing accurate real-time data. 4. Wal-Mart’s systems are linked to the P&G supply-chain management system. Demand spikes reported by RFID tags are immediately visible throughout the supply chain. 5. P&G’s logistics software tracks its trucks with GPS locators, and tracks their contents with RFID tag readers. Regional managers can reroute trucks to fill urgent needs. 6. P&G suppliers also use RFID tags and readers on their raw materials, giving P&G visibility several tiers down the supply chain, and giving suppliers the ability to accurately forecast demand and production. Fuente: Heizer and Render, Operations Management (2011) --- ## Page 17
Ejemplo de gestión caótica de almacenes de Amazon
<img>A cluttered shelf filled with assorted grocery items (cookies, canned goods, snacks) and a magazine, illustrating disorganized warehouse storage.</img> How Amazon arranges its warehouses (Tech Insider, 2016) --- ## Page 18 # Ejemplo de gestión caótica de almacenes de Amazon * Dificultades para gestionar los almacenes de Amazon: número elevado de referencias, número elevado de pedidos de clientes, predicción de la demanda (e.g. campañas “Black Friday”), ... * Amazon persigue minimizar los tiempos de preparación de los pedidos * Gestión caótica * El almacén está dividido por ubicaciones (bin/slot) con un código único asociado. * Cuando entra un producto (SKU) el sistema de información busca la primera ubicación libre de forma aleatoria y se le asigna. El producto se lleva allí y se registra el movimiento de entrada (escaneo de la ubicación, del producto, hora, ...) * Las salidas suelen producirse en lotes u órdenes de picking (que no tienen que corresponder con una orden de un cliente). Son listas de productos que un encargado (picker) ha de ir a recoger y llevar en un carrito. * Para cada orden de picking, el SI calcula una ruta óptima (menor tiempo de picking) que el encargado ha de seguir para ir recogiendo cada producto (registrando el correspondiente movimiento de salida). --- ## Page 19 # Ejemplo de gestión caótica de almacenes de Amazon **Ventajas:** * **Flexibilidad** en la organización del almacén, no es necesario planificar los sitios o prever espacio, y resulta muy sencillo aumentar el almacén cuando se necesita. * **Eficiencia**, en el uso del espacio al no dejar huecos libres * El **trabajo** de los operarios es **más sencillo**, no requieren aprender nada del almacén, únicamente las operaciones básicas de mover un producto, escanearlo, depositarlo o recogerlo. * La **gestión** es más sencilla aunque requiere de herramientas informáticas (e.g. gestión de ubicaciones mediante códigos de barras, creación de cestas de picking, minimización de las rutas de picking: problema del viajante) <img>A diagram showing a grid of points with red lines connecting them, illustrating a path or route.</img> --- ## Page 20 ¿Por qué es tan crítico la gestión de la información en toda la cadena logística? Efecto látigo (bullwhip effect) Simulación mediante el juego de rol “beer game” --- ## Page 21 # Beer game Antes de seguir con el resto de las diapositivas se recomienda probar el juego de simulación: * https://beergame.masystem.se/ * https://beergameapp.firebaseapp.com/ 1. Crear un juego 2. Escoger un rol, i.e. manufacturer, distributor, wholesaler, retailer 3. El juego se desarrolla por rondas (weeks), en cada ronda: a. Se recibe producto del proveedor (pedido anteriormente) b. Se recibe un pedido de cliente. Si hay stock se envía directamente. Si no hay stock aumenta la cantidad pendiente (backlog) c. Debe decidir la cantidad de cerveza que quiere pedir a su proveedor d. El objetivo es mantener un nivel de stock adecuado que permita responder a los pedidos de los clientes e. Cuidado porque tanto el stock como las unidades pendientes tienen un coste (mayor el coste de ruptura de stock). f. Existen retardos entre las órdenes de pedido y la recepción del producto --- ## Page 22 # Efecto látigo (bullwhip effect) graph TD A[Clientes] -->|piden 100
(demanda real)| B[Minorista] B -->|100 + 20| C[Mayorista] C -->|120 + 20| D[Distribuidor] D -->|140 + 20| E[Productor] F[Otros minoristas] --> B G[Otros mayoristas] --> C H[Otros distribuidores] --> D style A fill:#fff,stroke:#333,stroke-width:2px,color:#333 style B fill:#fff,stroke:#333,stroke-width:2px,color:#333 style C fill:#fff,stroke:#333,stroke-width:2px,color:#333 style D fill:#fff,stroke:#333,stroke-width:2px,color:#333 style E fill:#fff,stroke:#333,stroke-width:2px,color:#333 linkStyle 0 stroke:red,stroke-width:2px linkStyle 1 stroke:red,stroke-width:2px linkStyle 2 stroke:red,stroke-width:2px linkStyle 3 stroke:red,stroke-width:2px linkStyle 4 stroke:red,stroke-width:2px linkStyle 5 stroke:red,stroke-width:2px linkStyle 6 stroke:red,stroke-width:2px linkStyle 7 stroke:red,stroke-width:2px linkStyle 8 stroke:red,stroke-width:2px linkStyle 9 stroke:red,stroke-width:2px linkStyle 10 stroke:red,stroke-width:2px linkStyle 11 stroke:red,stroke-width:2px linkStyle 12 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linkStyle 602 stroke:red,stroke-width:2px linkStyle 603 stroke:red,stroke-width:2px linkStyle 604 stroke:red,stroke-width:2px linkStyle 605 stroke:red,stroke-width:2px linkStyle 606 stroke:red,stroke-width:2px linkStyle 607 stroke:red,stroke-width:2px linkStyle 608 stroke:red,stroke-width:2px linkStyle 609 stroke:red,stroke-width:2px linkStyle 610 stroke:red,stroke-width:2px linkStyle 611 stroke:red,stroke-width:2px linkStyle 612 stroke:red,stroke-width:2px linkStyle 613 stroke:red,stroke-width:2px linkStyle 614 stroke:red,stroke-width:2px linkStyle 615 stroke:red,stroke-width:2px linkStyle 616 stroke:red,stroke-width:2px linkStyle 617 stroke:red,stroke-width:2px linkStyle 618 stroke:red,stroke-width:2px linkStyle 619 stroke:red,stroke-width:2px linkStyle 620 stroke:red,stroke-width:2px linkStyle 621 stroke:red,stroke-width:2px linkStyle 622 stroke:red,stroke-width:2px linkStyle 623 stroke:red,stroke-width:2px linkStyle 624 stroke:red,stroke-width:2px linkStyle 625 stroke:red,stroke-width:2px linkStyle 626 stroke:red,stroke-width:2px linkStyle 627 stroke:red,stroke-width:2px linkStyle 628 stroke:red,stroke-width:2px linkStyle 629 stroke:red,stroke-width:2px linkStyle 630 stroke:red,stroke-width:2px linkStyle 631 stroke:red,stroke-width:2px linkStyle 632 stroke:red,stroke-width:2px linkStyle 633 stroke:red,stroke-width:2px linkStyle 634 stroke:red,stroke-width:2px linkStyle 635 stroke:red,stroke-width:2px linkStyle 636 stroke:red,stroke-width:2px linkStyle 637 stroke:red,stroke-width:2px linkStyle --- ## Page 23 # Propagación de la variabilidad TM12-2 Caption to Come <img> A composite diagram illustrating the bullwhip effect across four stages of a supply chain: • Top-left chart titled "Consumer sales" shows a relatively smooth, low-order quantity over time. • Top-right chart titled "Retailer orders to wholesalers" depicts larger, more frequent fluctuations in order quantity, with a red arrow indicating the propagation of variability from consumer sales to retailer orders. • Bottom-left chart titled "Wholesaler orders to manufacturer" shows even greater oscillations, with a red arrow pointing from retailer orders to wholesaler orders. • Bottom-right chart titled "Manufacturer orders to supplier" shows the most pronounced swings, with a red arrow pointing from wholesaler orders to manufacturer orders. The y-axis on all charts is labeled "Order quantity," ranging from 0 to 20 units, while the x-axis represents "Time." The overall visual emphasizes how small variations at the consumer end grow into large fluctuations by the time they reach suppliers. </img> Bullwhip Effect (efecto látigo): pequeñas distorsiones (variabilidad) en un extremo de la cadena se propagan convirtiéndose en grandes oscilaciones en el otro. La información entre los distintos agentes que conforman la cadena es fundamental en su funcionamiento. --- ## Page 24 # Fuentes de variabilidad ## Fuentes de variabilidad * Reglas de inventarios min-max: pedir cuando el inventario baja del mínimo, hasta llegar al máximo * Tiempos de espera: al aumentar los tiempos de respuesta aumentan los stocks de seguridad, las cantidades de pedido * Tamaño de lotes de pedido: pedido de lote grande seguidos de periodos sin pedidos dificultan estimar la demanda * Cambios en los precios: respondemos tratando de acumular cuando los precios son bajos * Órdenes infladas: cuando se desconfía del cumplimiento, o se espera falta de suministro en un periodo * Promociones comerciales (incentivan el consumo de clientes) * Políticas de incentivos de ventas (incentivan las ventas de los comerciales) ¿Cómo reducir el efecto látigo? Reducir la incertidumbre (compartir información entre agentes de la cadena) y reducir las fuentes de variabilidad --- ## Page 25 # Cómo reducir el efecto látigo Ejemplos: * Minimizar los tiempos de obtención y procesamiento de la información logística * Controlar la demanda real de productos en tiempo real. E.j., Wal-Mart comparte la información de los POS (point of sale) con sus proveedores * Eliminar métodos de aprovisionamiento que ocasionan lotes de pedido grandes * Eliminar incentivos a los clientes que alimentan tendencias de acumulación de productos * Identificar y eliminar las causas por las que los clientes cancelan o reducen pedidos * Disponer de aplicaciones que permitan la planificación y gestión cooperativa de las operaciones logísticas --- ## Page 26 # Referencias * Bozarth, Cecil C., Robert B. Handfield, and P. Chandiran. Chapters 1, 8. Introduction to operations and supply chain management. Upper Saddle River, NJ: Pearson Prentice Hall (2008)