"Transformando el Conocimiento Empresarial en Resultados" - Ibm smarter analytics

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  • Slide #2: Smarter Planet and the Role of AnalyticsFour years ago, IBM started a new conversation about building a smarter planet – an initiative that reflects our efforts to instrument and interconnect the flow of data, information and devices between our physical and virtual worlds.  When we first launched smarter planet, we knew advanced analytics would have a fundamental role to play, however, it has quickly become the silver thread woven throughout our portfolio. MENSAJES:Nuevaconvesación – construir un planeta mas inteligente – el mundo esta instrumentado y interconectado a traves de miles de millones de dispositivos que permiten integrar el mundo físico y el virtual.Sabiamos que SmartAnalyticstendria un rol fundamental en la iniciativa Smartplanet pero tal vez lo que nos sorprendio fue la velocidad con que esto ocurrio
  • Slide #3: Evolution of AnalyticsHemos aprendido de nuestros cliente: se aplican en nuevas modalidades para identificar nuevos patrones para alcanzar nuevo conocimiento nunca antes imaginado Mas alla del caos creado por la sociedad hiper conectado, vemos nuevos patrones de automatización. Estos patrones estan instrumentando el mundo fisicoalreadedor nuestro conforme las empresas cada vez mas se interconectan y crean grandes data warehouses para lograr el mejor conocimiento posible. Estos patrones se repiten en cada una de las industrias Si se usa adecuadamente, este cononcimientopermitira a las organizaciones reinventarse x completo ya sea en la creación de nuevos productos, nuevos servicios y optimizar las fuerzas de trabajo y procesos. Requisitosquerequierenfundamentalmente de innovacionparacompetirexitosamente en el mercado global de HOYWhat we’ve learned from these engagements is that analytics continues to evolve, continues to be applied in new ways to identify new patterns and unlock new insights in ways previously unimaginable.  Amidst the chaos created by a hyper-connected society of empowered consumers, we are seeing a pattern of automation emerging. This pattern is driving the instrumentation of the physical world around us as organizations interconnect and aggregate information in massive data warehouses in order to apply analytics to gain greater insight. This pattern repeats across every industry, extending throughout both the virtual and physical worlds.  If done correctly, the insight gained can enable an organization to completely re-invent their products, deliver new service capabilities and optimize their workforce and processes . . . all part of the relentless pursuit of innovation required to compete successfully in today’s global marketplace.  But to do so requires us to move from enterprise data to big data . . . business initiatives to business imperatives . . . and from advancing a single organization to transforming entire industries.
  • Slide #4: IBV-MIT DATAYou see the data on this chart… from study conducted by our Institute of Business Value and MIT Sloan Management ReviewNumber of enterprises using analytics to create a competitive advantage jumped almost 60 percent in just one year… Nearly 6 out of 10 organizations now differentiating through analytics. We found that the overall increase in advantage went almost exclusively to organizations who were already experienced users of analytics… so the early adopters are extending their leadership. Those organizations are more than twice as likely to substantially outperform their peers  So we’re seeing early bifurcation of the market – leaders and followers. Reinforced by a separate MIT Study that found analytics led to 5-6 percent productivity increases… which is big enough in most industries to separate the winners from the losers. That’s all change that’s happening within enterprises….
  • Slide #5: Analytics Moving from Enterprise Data to Big DataThe implications of this pattern are clear – a major transformation is underway.  This transformation is fundamentally changing how organizations are structured, how daily operations are managed and where new investments are made to create value. It is being powered by the onset of big data, which in turn is being instrumented and analyzed by new computing systems with deep analytic capabilities.  Analytics has grown beyond enterprise data to big, largely unstructured data from billions and billions of diverse sources: . . . there are 200 million tweets sent each day, or roughly 12 TB data. . . every second of high-definition video creates 2,000 times as many bytes as a single page of printed text. . . . . . all told, there are 1.8 trillion gigabytes of information available in today’s digital world . . . a truly remarkable figure that continues to grow at an alarming rate.  Yet, it is through the complexities caused by big data that we can start to recognize new patterns that we simply couldn’t before: . . . insurance companies are identifying fraud patterns by combing different data sources in real time to analyze massive transactional databases . . . financial institutions that are trading based on trending social content . . . energy companies that are analyzing 350 billion meter readings each year to predict power consumption . . .  With every new challenge created by big data comes an equal opportunity . . . for those who are truly prepared to leverage it . . . to significantly improve organizational decision making.
  • So what do clients tell us in our studies? From a study conducted early this year: More than one-third of business leaders frequently make major decisions with information they don’t trust. And one-half of business leaders say they don’t have access to sufficient information to do their jobs. Another more recent study highlights strong differences between the top-performing organizations and those who aren’t keeping up with their peers. Top performers were 15 times more likely to excel at predicting the future… evaluating the consequences and trade-offs of their actions
  • Key point can be talked about on this chart:Oil which is the fuel for modern economy for centuries. However, Oil in its raw form has little value. It needs to be refined and separated into a large number of consumer products, from petrol and kerosene to asphalt and chemical reagents used to make plastics and pharmaceuticals. It is also used in manufacturing a wide variety of materials.Big Data is just like oil, in it’s raw form it provide no value to enterprise, until it is processed and valuable and actionable business insights are “distilled”. Just like the technology that made available 100 years ago to discover oil and process it to consumable products. Big Data technology is going to transform and revolutionize the way enterprise get and use
  • Answers to these questions are delivered through the power of Business Analytics.All organization are striving to achieve better outcomes. Businesses are looking to drive revenue growth and ensure expenses stay in line to ensure strong margins. Public sector organizations are also trying control expenses while offering important services that benefit their constituencies.Informed, smarter decisions is a key foundation to better outcomes. Organizations need to ensure consistency across the broad spectrum of decision making from operational through to strategic decisions. Everyone in the organizations needs to be able to answer: how are we doing, why and what should we be doing?The key to decision making is driving new actionable insights. These insights are sweet spots of information that enable smarter decision making at all levels of the organization.The foundation to uncovering insights which improve decision making and deliver better outcomes is trust in the data. The organization must have confidence that the information is accurate and it must be organized in a way that is easy to uncover these insights.Let‘s have a look at some IBM clients who are using Business Analytics drive better outcomes for their organizations..
  • WHY do Analytics-driven outperform? WHAT do they do different?BA processes and solutions enable everyone, top-to-bottom and all functions, to make better decisions. WHY?Easy-to-use technologyReal-time info / analysisImpact of decisions across organization (NO silos)Improved colloborationCan measure outcomesCite EXAMPLES from slide...Let‘s examine organizations who‘ve embraced Analytics...
  • Slide #8 : FOUR INITIATIVES What we’ve found working with our clients is that enterprises that are going to drive change around business analytics tend to start in one of the four areas. Customer Analytics In a moderate-growth market, with profit pools stagnating… the mandate for customer relationship management is about taking that share from competitors. Best way to do that... insight on behaviors, as well as understanding the return or impact of promotional spending, loyalty programs, And of course, make existing customers loyal customers.  Operational Efficiency And across industries, the opportunities in: Predictive maintenance… preparing, not repairing Optimizing supply chains… and the claims process. Financial Operations and Processes To do more with less, all enterprises must understand their sources of profit, and sources of cost. Roll that insight into the planning processes Accelerate the time and integrity in the closing process. Regulatory, Risk and Fraud In the post-2008 era of increasing regulation and oversight… reporting analytics is the response to governmental controls in every industry, not just financial services. Including insight into traditional and emerging categories of risk… predicting and getting ahead of future regulation. As well as fraud detection.
  • Slide #20 : ConclusionTo close off this section, one additional point... and it's not trivial. We've talked about the mandate we see in our clients. They do not consider the embrace of analytics optional. It's foundational to competitive position. All industries. All size of enterprise. We've looked at examples of how that's playing out in industries, and the solutions we're delivering for industry impact... which means outcomes and time to value. Very real. And I hope we've conveyed that its takes a fairly sophisticated set of capabilities to address this market in a meaningful way... which is the intentional engineering of our business model, development model, and go to market model across IBM Software and Services... along with the massive -- and exclusive -- capability of IBM Research.  We think this constitutes a credible approach to this market, and it’s also why understand that the barriers to entry here are extreme. The point I'll end on is this: Last year as we marked our Centennial anniversary... one of the things that came clear... is that over that time there really have been just a few constants… and one of them is that at our core... is this enduring passion for discovery. We value thinking. We believe the core of our brand promise to our clients is access to experts and expertise. We enjoy grand challenges, and we have the will to stay with them.  So from our inception… right through to today… the opportunity to unlock new value... to think in terms of complex systems… to apply this great technology portfolio and tens of thousands of people who cherish the search for the possibility... that's the DNA of our company and the deep intellectual capital of IBM.It's the kind of work we seek. And it’s the essence of what we mean when we talk about a Smarter Planet. With that… I’ld wish you all a very wonderful day ahead and thanks for all the confidence you have extended towards us over the years.


  • 1. 11 de Octubre de 2012IBM Smarter AnalyticsAproveche el poder de la analítica paratomar decisiones inteligentesAlan SchcolnikTechnical Sales Manager – Business Analyticsalan.schcolnik@ar.ibm.com © 2012 IBM Corporation
  • 2. Hace cuatro años atrás, comenzamos a trabajar con las organizaciones para construir un planeta más inteligente Interactuando con miles de clientes, aprendimos que las analíticas son fundamentales para el éxito2 © 2012 IBM Corporation
  • 3. Desde ese momento, las analíticas han continuado evolucionando:  Desde iniciativas del negocio a imperativos del negocio  De datos corporativos a “big data”  Desde iniciativas individuales a transformaciones completas de diversas industrias3 © 2012 IBM Corporation
  • 4. Las analíticas han evolucionado desdeiniciativas del negocio a imperativos del negocio COMPAÑÍAS SOFISTICADAS ANALÍTICAMENTE HAN SUPERADO A SUS COMPETIDORES Quienes respondieron que las analíticas le han permitido crear una Organizaciones que alcanzan ventaja competitiva una ventaja competitiva con analíticas tienen2010 37% 57% increase 2.2x mas probabilidad de superar sustancialmente a2011 58% sus pares Ratio of respondents who indicated analytics creates a competitive advantage to those who indicated it did not and the likelihood they also indicated their organizations was “substantially outperforming their competitive peers.” The ratio was 2.0 to 1 in 2010. Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research4 partnership. Copyright © Massachusetts Institute of Technology 2011 © 2012 IBM Corporation
  • 5. Las analíticas están evolucionandodesde lo posible a lo probado $300 Million 80% increase $200 Million in savings in productivity increase in & fraud reduction savings cash flow $24 Million 600% increase in reduced waste in cross-sell 40% decline and fraud campaign in homicide rates5 © 2012 IBM Corporation
  • 6. Los desafíos de sus usuarios no son únicos y van en aumento… Usuarios no consiguen la información a tiempo Usuarios no consiguen la información correcta Proceso de recolección y verificación de información altamente complejo Usuarios trabajan con números diferentes Existen diferentes herramientas para acceder a distintas fuentes de información (Silos de información) Volúmenes de dato crecen incontrolablemente Inconsistencia en los datos Información distribuida en cientos de planillas desconectadas Procesos de cierre muy complejos y largos Incapacidad para modelar escenarios y crear análisis 7 what-if © 2012 IBM Corporation
  • 7. Las Organizaciones están funcionando convarios puntos ciegos 1 de 3 Líderes toman frecuentemente Top Performers Demuestran su Experiencia decisiones basados en información que ellos no 15X confían o no tienen 1 de 2 Predecir y prepararse para el futuro evaluando “trade-offs” proactivamente Líderes dicen no tener acceso a la información que necesitan Industry Top performers para realizar su trabajo Industry Under performers8 Source: IBM: Break Away with Business Analytics and Optimization Study © 2012 IBM Corporation
  • 8. Mejores Resultados Decisiones Inteligentes Conocimiento Accionable Información Relevante10 © 2012 IBM Corporation
  • 9. Pero…¿por qué hablamos de BA y no de BI? Nueva Estrategia Predecir y actuar Sentido y respuesta Falta de Velocidad Agudeza Tiempo Real, Acceso Instinto e intuición Basado en Hechos ineficiente Volumen Expertos de análisis Todos Variedad Back office Punto de impacto Incapacidad para predecir Automatizado Optimizado Desafíos de la Información Método Tradicional Analíticas del Automatización Planificación Business del Negocio de Recursos Intelligence Negocio & Optimización11 © 2012 IBM Corporation
  • 10. Aplicada en toda la Alinear planes de recursos para crecimientos sostenibles yOrganización rentables Cumplir con confianza Reducir churn Optimizar mix de Incrementar personas satisfacción y lealtad Beneficios comparables Mejorar posicionamiento Business competitivo Reducción gaps de Priorizar entrega de Analytics portafolios Mitigar riesgos de productos rentables IBM Business Analytics Administrar una desarrollo mayor demanda Maximizar la efectividad Mejorar la capacidad de del pipeline y la producción rentabilidad de cliente Reducir inventarios12 © 2012 IBM Corporation
  • 11. y en todas las Industrias Finanzas Seguros Retail Industrial• Risk Adjusted Profitability • Product Profitability • Store Development • Sales & Operation• Branch Performance • Claims Submission • Strategic Promotions Planning• Retail Banking Customer Optimization • Financial Merchandising • Allocations Optimization Segment Performance • Insurance Self Service • Financial Workbench & • Risk Analysis• Corporate Banking • Insurance Scorecard… Scorecard… • Trade Promotion Customer Segment Perf Management • Asset Management… Telco Energía Gobierno Salud • Customer Service • Intelligent Utility Network • Crime Information • Enterprise Health Analytics • Customer Billing • Asset Plant Lifecycle Mgmt. Warehouse • Health Plan Industry Models • Compliance • Central Engineering • Case Management • Customer Care & Insight for • Simple Order… • Rate Case • Municipal Performance Health Plans • Aging Workforce Management • Risk, Fraud, & Compliance • Violations… • Court Management for Health Plans… • Fraud Investigation … 13 © 2012 IBM Corporation
  • 12. Las Organizaciones se transforman comenzando por una de estas cuatro iniciativas Ejemplos: 1 Crecer, retener y satisfacer clientes • Administración del Churn • Análisis de sentimiento • Propensión de compra / Mejor próxima acción 2 Aumento de la eficiencia operacional • Mantenimiento predictivo • Optimización de la cadena de abastecimiento • Optimización de reclamos 3 Transformación de procesos financieros • Rolling plan, pronóstico y presupuesto • Automatización de los procesos de cierre • Tableros de tiempo real Administrar14 4 riesgo, fraude y cumplimiento de regulaciones • Visibilidad de riesgo operativo y financiero • Identificación del fraude en tiempo real © 2012 IBM Corporation
  • 13. 1 - Crecer, retener y satisfacer clientes XO Communications mejoró tanto sus ratios de retención como sus ingresos  Considera más de 500 variables para predecir la intención de recisión del cliente en los próximos 90 días • Cada cliente recibe un “churn score” • Ejecuta campaña proactiva en el grupo de los Top 10  Reducción de churn efectivo del 35% en el primer año  Mejora de la facturación en los clientes retenidos del 60%  Reducción de los agentes de servicio necesario para un mismo nivel de contacto con clientes15 www.youtube.com/watch?v=-KOn0Qn0lgA © 2012 IBM Corporation
  • 14. 2 of ColumbiaDistrict - Aumento de la eficiencia operacionalAgua y Alcantarillado - Reducción de llamadas de clientesa través de un adecuado mantenimiento preventivo La Necesidad: Durante muchos años DC Water encontró grandes desafios “Our work with IBM has en balancear la necesidad de actualizar su infraestructura con allowed our assets to los recursos financieros escasos. communicate with us— and we’re doing more DC Water trabajo con IBM para implementar una solución de than just listening, we’re Business Analytics para modernizar su infraestructura y así ganar mayor visibilidad en la operaciones críticas. taking action.”  Reducción de llamadas de clientes en un 36% a través de un —Mujib U. Lodhi, chief adecuado mantenimiento preventivo y la implementación de information officer, DC medidores automáticos Water  Posibilidad de incrementar investigaciones urgentes en los primeros 10 minutos desde un 49% a 93% de los casos  Mayor habilidad para generar reportes de cumplimiento regulatorio y de revisión gerencial en segundos en lugar de días16 © 2012 IBM Corporation
  • 15. 3 - Transformación de procesos financieros Nike Latinoamerica mejoró su proceso de planificación alcanzando una precisión del pronóstico del ventas del 97% “Con Cognos Express  Nike México contaba con la gente para crear el logramos tener un solo proceso pero le faltaba la herramienta para proceso de planeación convertirse en reales consultores del negocio y ser así alcanzando una precisión del pronóstico de ventas del 97%.” reales business partners para el negocio  Solución de planificación con varios objetivos — Carlos Gemmel, Business and Financial Planning, Nike alcanzados:  Precisión del pronóstico de ventas del 97%  Reducción de 5 a 2 días en el proceso de presupuesto  Capacidad para contar con 15 escenarios17 www.youtube.com/watch?v=hKUHI-HPfXQ © 2012 IBM Corporation
  • 16. 4 - Administrar riesgo, fraude y cumplimiento de regulaciones Bancolombia Usa predictive analytics para identificar transacciones fraudulentas “With the data mining  Solución para detectar más rápido y fácil aquellas system, we generated productivity savings of transacciones que provienen potencialmente de nearly 80 percent.” operaciones de lavado de dinero — Francisco Ruiz, Head of  1.3 millones de transacciones analizadas diariamente Compliance, Bancolombia  Revela un 40% más de transacciones sospechosas con actividades sospechosas  Capacidad para descubrir nuevas técnicas de lavado de dinero  Integra múltiples transacciones para detectar relaciones18 © 2012 IBM Corporation
  • 17. Pero como acercar las analíticas alos datos Analytic ApplicationsNuevas analíticas requieren de BI / Exploration / Functional Industry Predictive Content Reporting Visualization App App BI / Analytics Analytics Reportingplataformas de BIG DATA • Integrar y administrar toda la IBM Big Data Platform variedad, velocidad y volumen de los Visualization Application Systems datos & Discovery Development Management • Aplicar analíticas avanzadas en los set de información fuentes Accelerators • Visualizar toda la información para análisis ad-hoc Hadoop Stream Data System Computing Warehouse • Desarrollar ambientes para la construcción de nuevas analíticas • Seguridad y Gobernabilidad de los datos Information Integration & Governance19 © 2012 IBM Corporation
  • 18. En conclusión …uso de analíticas es clave en esta nueva era Los Líderes serán distinguidos por su habilidad en aprovechar Toda la Información Toda la  Transacciones Gente  Todas las áreas  Warehouses  Expertos y no expertos  Documentos  Ejecutivos y empleados  Redes sociales  Socios y Clientes  Sensores  Videos  Geoespacial  ….etc Todas las Todas las Decisiones Perspectivas  Críticas o menores  Pasado – Histórica, agregada  Estratégicas o tácticas  Presente – Tiempo-Real  Rutinarias o  Futuro – Predicción excepcionales20 ……en el punto de impacto © 2012 IBM Corporation
  • 19. Y la toma de decisiones debe ser optimizadaEquipe a los tomadores de decisiones con la previsión necesaria para intervenir Ejecutivo Gerente de Unidad Gerente de Línea Usuario casual Analista de Negocios Analista Financiero . Monitoreo de la actividad en tiempo real Dashboards Scorecards Reportes Consultas Análisis Analíticas de Modelos Planes contenido Predictivos Permite a toda la organización obtener una idea clara sobre la salud del negocio y entender que está ocurriendo en su área de responsabilidad ¿Por qué (no) estamos en la ¿Qué es probable que suceda? ¿Qué debemos hacer a senda correcta? continuación?Analizando Simulación con modelos predictivos y Asignar recursos en el lugar correcto ytendencias, estadísticas, correlaciones y análisis “what-if” que permite predecir definir objetivos para esas asignacionescontexto, es posible entender que resultadosgenera mejores resultados Tecnología agnóstica – datos de distintos orígenes para una visión única del negocio Mensajería Fuentes Aplicaciones Fuentes Otras21 relacionales OLAP Fuentes Corporation © 2012 IBM
  • 20. Agenda del CIO según Gartner – 2012 Source: Gartner “Executive Summary - Amplifying the Enterprise: The 2012 CIO Agenda”, Mark P.22 © 2012 IBM Corporation McDonald | Dave Aron - January 2012
  • 21. A smarter planet is built on Smarter Analytics www.Ibm.com/SmarterAnalytics Alan Schcolnik Technical Sales Manager – Business Analytics alan.schcolnik@ar.ibm.com23 © 2012 IBM Corporation