Del Big Data a las Big Decisions:

Transcripción

1 Del Big Data a las Big Decisions: Una forma de añadir valor en la era digital Josep Valor Liderando el cambio digital de tu compañía IESE Barcelona, 4 de marzo de blog: jvalor@iese.edu

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3 La primera disrupción: la fábrica de hielo Prof. Josep Valor, blog: 3

4 La segunda disrupción: la fábrica doméstica de hielo Prof. Josep Valor, blog: 4

5 Qué tienen estas compañías en común? Prof. Josep Valor, blog: 5

6 Que en la última década han sido sustituidas en el S&P 500 por estas otras! Prof. Josep Valor, blog: 6

7 Drivers de la Era Digital: Tercera Plataforma Movilidad La Nube...Tenemos una estrategia en móvil, quizá para la nube, pero redes sociales, big data?!!.. Big Data Redes Sociales Prof. Josep Valor, blog: 7

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9 Fuentes del Big Data Estructurados Transacciones ERP/CRM/SCM Transacciones de acciones Clickstream/Page views/web transactions Web links/blog references No estructurados s Twitter feeds Documentos de texto Facebook posts Sensores Mobile phone/gps/location data RFID, Bar Code Scanner Data Real-time machinery diagnostics/engines/equipment Etc... Prof. Josep Valor, blog: 9

10 Una fuente enorme de datos es el móvil... Red de Proximidad Red de Llamadas Red de Localización Red de Amigos Prof. Josep Valor, blog: 10

11 Wal-Mart Stores, Inc. 1 millón de transacciones de clientes cada hora Alimentando bases de datos con más de 2.5 Petabytes/dia 167 veces los libros de la Library of Congress Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 11

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13 Las 3 V s del Big Data Volumen Necesidades de Almacenamiento Análisis masivo Variedad Transaccional Social Media Móvil Velocidad Generación Proceso Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 13

14 Cómo obtenemos la cuarta V? Prof. Josep Valor, blog: 14

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16 transformando Gigabytes en decisiones...

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18 rea the thin scoring buffer around area. We the divided 3-point the arc; scoring we call area this into area a the grid sco 1 ft 2 consisting (Figure 1). of To 1,284 quantify unique shooting range, cells, we applied each 1 ft spatial 2 (Figur he grid analyses and Tiros within to evaluate en each la shooting NBA : cell. performance across the grid and w Fuente: Kirk Goldsberry, CourtVision: New Visual and Spatial Analytics for the NBA - MIT Sloan Sports Analytics Conference 2012 Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 18

19 6. Antawn Jamison % 7. Andre Igudola % 8. Ray Allen % 8. Kevin Durant % Tiros en la NBA : Posiciones preferidas de 4 jugadores 10. Danny Granger % Table 1: Top 10 players in Spread metric 6. Joe Johnson % 7. Vince Carter % 8. Paul Pierce % 8. Rudy Gay % 10. Danny Granger % Table 2: Top 10 players in Range metric Steve Nash Ray Allen Dirk Nowitski Kobe Bryant Figure 3: The shooting ranges of Steve Nash, Ray Allen, Dirk Nowitzki, and Kobe Bryant. These four players had the highest Range values, but these graphics reveal that they achieve them in much different ways. For example, when compared to the three others, Dirk Nowitzki shoots Prof. relatively Josep few Valor, 3-point valor@iese.edu shots and performs blog: much better in the mid-range areas on the :@josepvalor left side of the court, while Ray Allen excels in the corners of the court where Steve Nash rarely shoots. Fuente: Kirk Goldsberry, CourtVision: New Visual and Spatial Analytics for the NBA - MIT Sloan Sports Analytics Conference

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21 Anton van Leeuwenhoek ( ) Prof. Josep Valor, blog: 21

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23 Ernst August Friedrich Ruska ( ) Prof. Josep Valor, blog: 23

24 Virus H1N1 (fiebre porcina/swine flu)

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28 Josep Valor,

29 Film-related searches and box office revenue Prof. Josep Valor, blog: 29

30 1. DESCRIPTIVE 2. PREDICTIVE 3. PRESCRIPTIVE

31 The sexy job in the next ten years will be statisticians The ability to take data to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it that s going to be a hugely important skill. How the Web Challenges Managers McKinsey Quarterly Hal Varian Text Chief Economist at Google

32 Ciudado con la correlación versus la causalidad Las moscas se vuelven sordas al arrancarles las alas

33 Intuición vs. Análisis de Datos

34 Experimentos Controlados Tests A/B Fuente: Ronny Kohavi Prof. Josep Valor, blog: Dividir el tráfico aleatoramiente entre dos (o más) versiones A (Control) B (Test) Recoger métricas relevantes Analizar Mejor método científico para probar causalidad :@josepvalor 34

35 Experimento MSN Home Page Search Box Criterio Global de Evaluación: Clicks en los enlaces de compra B es peor en el 64% de los casos A B Fuente: Ronny Kohavi Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 35

36 to have a great idea have a lot of them Thomas A. Edison

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38 Big Data vs. HiPPOs Highest Paid Person s Opinion

39 Escépticos informados Fuente: S. Shah, A. Horne and J. Capellá, HBR, abril 2012 Prof. Josep Valor, blog: 39

40 Las personas somos una fuente primordial de datos

41 Comportamiento de las tribus urbanas Body Level One Body Level Two Body Level Three Body Level Four Body Level Five Fuente: Sense Networks & Prof. Alex Petland Prof. Josep Valor, blog: 41

42 Fuente: Sense Networks & Prof. Alex Petland

43 SmartSteps Prof. Josep Valor, blog: 43

44 El Big Data llega a la vida real de los átomos Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 44

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49 Rolls Royce tiene más de sensores en sus nuevos motores: puede vender servicios por tiempo operativo Prof. Josep Valor, blog: 49

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51 Qué tardaremos en que nos atienda un robot? Prof. Josep Valor, blog: 51

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53 Personal Data Store Prof. Josep Valor, blog: 53

54 The Internet of You Prof. Josep Valor, blog: 54

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58 Personal data is the new oil of the internet and the new currency of the digital world. Meglena Kuneva European Consumer Commissioner Data is now the world s new natural resource. Virginia Rometty IBM President & CEO

59 Fraude y Robo Invasión de Privacidad Ciber-Terrorismo & Vandalismo Discriminación de precio Denegación de seguro médico Robo de clientes o ideas Obama s Privacy Bill of Rights Tenets UE con legislación más restrictiva (multas de hasta 1M o 2% del beneficio)

60 Hemos estado monitorizando sus correos, y hemos llegado a la conclusión de que no está haciendo nada ilegal. No obstante, también hemos visto que usted es un incompetente.

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62 Hay problemas de privacidad de todo tipo Mi padre dice nos espías online No es tu padre Prof. Josep Valor, blog: 62

63 Creación de un Mercado de Datos Fuente: World Economic Forum, febrero 2013 Prof. Josep Valor, blog: 63

64 The end of the average Prof. Josep Valor, blog: 64

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67 To err is human, but to really foul things up you need a computer. Paul Ehrlich

68 CIO Technology Priorities, Gartner 2013 Source: Gartner Research, 2013 Prof. Josep Valor, blog: 68

69 Top 10 IDC Predictions For CIOs, January 2014 (3rd platform: mobile, cloud, big data, social - 1st: mainframes, 2nd: PC) In two years, over 70% of CIOs will change their primary role from directly managing IT to become an innovation partner; Before 2017, only 40% of CIOs will rise to the challenge from CxOs to partner in strategic planning; 70% of CIOs will increase enterprise exposure to risk; Enterprise business mobility will require 60% of CIOs by 2017 to support an agile architecture; The demographic shift to young and mobile customers will require 80% of CIOs in consumer-facing businesses to integrate IT with public social networks by 2015; By 2015, 3rd Platform requirements will drive 60% of CIOs to use enterprise architecture (EA) as a required IT tool, but only 40% will deploy EA effectively; By 2015, 60% of CIO security budgets for increasingly vulnerable legacy systems will be 30-40% too small to fund enterprise threat assessments; By 2017, the transfer of 3rd Platform investments from IT to line-of-business budgets will require 60% of CIOs to reduce the cost of infrastructure and operations; By 2016, 80% of the IT budget will be based on providing service integration; By 2018, adoption of 3rd Platform IT technologies will redefine 90% of IT role Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 69

70 The Chief Digital Officer Digital will become a boardroom topic Digital terms will converge under one leader: mobile, tablets, kiosks, digital stores, branches, e-commerce, digital marketing, etc. Digital budgets will rise and innovation will top the agenda Digital skill will become even harder to source Digital will change (disrupt?) the physical (i.e. the role of wearable devices?) Source: Forrester Research, 2014 Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 70

71 The Chief Digital Officer If you have a CDO, what is he/she responsible for? Source: Forrester Research, 2014 Prof. Josep Valor, valor@iese.edu blog: :@josepvalor 71

72 Man is the lowest cost, 150 pound, nonlinear, all-purpose computer system which can be mass produced by unskilled labor. A 1965 NASA, man-in-space report

73 Gracias! blog: