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Dreamforce to You Helsinki 3.11.2016

Energiaa, uusia innovaatioita, rohkeutta uudistua... Dreamforce to You -tapahtuma kokosi Helsinkiin yli 750 asiakasta ja yhteistyökumppania 3.11.2016. Tapahtuman jaettavat esitysmateriaalit koottuna.

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Dreamforce to You Helsinki 3.11.2016

  1. 1. koulutus
  2. 2. #Verkostot 10  Customers   50-­‐100  Events   20000  Followers   100  000   Readers/year   +300  000   Pageviews   10  Events   5000   Guests   130  000   Readers   380  000   Pageviews   Idea Strategia Johtaminen Muotoilu Digitalisaatio 1.  Miksi? Enemmän ja parempaa vähemmällä 2.  Mitä? Omistaja-arvon kasvattaminen, Kasvu, Muutosjohtaminen, Digistrategiat, Yritysmuotoilu 3.  Miten? Valmennukset, konsultointi, Koulutus, Puheenvuorot 4.  M&M Mainetutkimuksen 1. “Elää ja yrittää kuten opettaa” Digitalist   www.villetolvanen.com   Yritysmuotoilu  
  3. 3. ”Etsimme uutta internetistä, vaikka ainoa tehtävä olisi mullistaa vanha.”
  4. 4. Digitalisaation tehtävä on luoda enemmän ja parempaa vähemmällä. Digitalisoiminen on paras, tehokkain ja halvin tapa luoda uutta arvoa.
  5. 5. Digijuna yritysten ja toimialojen välillä pitenee.
  6. 6. Ollakseen ”strateginen” on oltava keskeinen osa arkea. Kulttuuri ahmii strategioita aamupalaksi.
  7. 7. Data, järjestelmät, prosessit, arvoketjut, siilot, ATK Arvo, Tieto, Ekosysteemit, Asiakaskokemus
  8. 8. Ekosysteemit, Alustatalous, Yhteisöt & Asiakaskokemus
  9. 9. Janatodellisuus   Markkinat   Arvoketjut   Ratkaisut   Materiaalit     Ympyrätodellisuus   Ekosysteemit   Arvoverkostot   Arvo   Asiakkaat     TRANSFORMAATIO  
  10. 10. Asiakaskokemus Infrastruktuuri Työ, verkostot Prosessit Toimintamallit, Transformaatio – Digitalisaatiosta totta KulOuuri  &   Johtaminen  
  11. 11. Digitalisaation edellykset 1.  Ymmärrys – kulttuuri, visio, roadmap, 2.  Osaaminen – strategia, toimintasuunnitelma 3.  Työkalut – ympäristöt, organisaatio, hankesalkku
  12. 12. KäyOöliiOymät   Vuorovaikutus   Sisällöt  Kumppanit   Asiakaspolku   Äly   AsioinU   Palvelut   AutomaaUo   Digivisio –asiakaskokemus?
  13. 13. Digiajan asiakaskokemus INFRA PROSESSIT CRM R&D   SCM   PALVELUT   MYMA   ASPA   ASIAKAS- KOKEMUS
  14. 14. 5% technology 95% culture & change management Open Close Comms Values Production R&D Business models Product Marketing Sales Customer care Experience Network NEXT
  15. 15. 170/100/100
  16. 16. Haasteita 1.  Terminologia 2.  Tuotelähtöisyys 3.  Pistemäisyys 4.  Sirpalemaisuus 5.  Reaktiivisuus
  17. 17. Toimintasuunnitelma 1.  Lähtökohdat (swot) 2.  Tavoitteet, määrälliset & laadulliset 3.  MWB toiminnoittain 4.  Kehityshakkeet 12, 24, 36 5.  ToSi = Tavoitteista totta 1.  Kuka, Mitä & Milloin Kilpailuetu   Toimituskyky   GTM  
  18. 18. Tuotekehitys   &  innovaaUot   TyökulOuuri,   verkostot  ja   ekosysteemit   Tuotanto  &   jakelunhallinta   MarkkinoinU  &   myynU   Asiakaspalvelu   Analogiset   Sähköiset   Digitaaliset   -­‐prosessit   Mittarit - Digiprosentti 1.  Yrityksen  nykyiset   Sähköiset  ja  digitaaliset   Toimintamallit   2.  Benchmark  yli   Toimialojen  =   Mitä  käytössä  vs.   Parhaat.  
  19. 19. Tee näin. 1.  Arvoketju 2.  Ymmärrys, osaaminen & työkalut 3.  Roadmap, 1000pvå 4.  Organisoituminen 5.  Nopeat, helpot voitot 6.  Tuloksellinen ja pitkäjänteinen tekeminen.
  20. 20. Arvoketju •  Missä kohtaa arvoketjua olemme parhaita? •  Mitkä toimijat uhkaavat tekemistämme? •  Mitä mahdollisuuksia digitalisaatio tuo •  Miten varmistamme kyvymme ajatella liiketoimintamme asiakkaan/ulkopuolisen silmin?
  21. 21. Digitaalinen liiketoimintaympäristö Markkinat   Yleisö   Ekosysteemit   Asiakkaat   Ratkaisu   Arvo   1. Kevytyrittäjät, henkilöbrändit = Artistit, kirjailijat, asiantuntijat, yrittäjät 2. Yritysten omat kanavat & Kauppapaikat 3. Yritysten yhteisöt esim. Novita, Pentik, Varusteleka 4. Kauppapaikat esim. Oikotie, autotalli, Amazon, jne. 5. Ekosysteemit esim. Tori.fi, Digitalist, jne.   Digitalist  
  22. 22. 300  000  sivulatausta   12  000  seuraajaa   75  00  FB  fania   5000  Osallistujaa   4000  FB  ryhmässä   10   kumppania   ”Digitalisoidaan Suomi pikseli kerrallaan” TBWA Digitalist Marketing Forum Dingle Digitalist Social Business Forum Ixonos Digitalist Customer Experience Forum Technopolis Digitalist pop-up MTV Digitalist 5M Meltwater Digitalist Communications Forum IBM Digitalist Leadership Forum Salesforce Digitalist Growth Forum Sonera Digitalist IOT Forum Solita Digitalist Thinkers Forum Digitalist Network 2016
  23. 23. Yritysmuotoilu & digitalisaatio Liikeidea Strategia Johtaminen Muotoilu Digitalisaatio YMMÄRRYS   OSAAMINEN   TYÖKALUT  
  24. 24. Ekosysteemit, Yhteisöt & tekoäly ovat jo täällä. Digiaika on tänään, tässä ja nyt.
  25. 25. 3 November 2016 Confidential and proprietary: Any use of this material without specific permission of McKinsey & Company is strictly prohibited Machine learning in the digital age
  26. 26. 68McKinsey & Company Mindfulness – “The quality or state of being conscious or aware of something” Take a big breath and relax, with your eyes open and looking at the hourglass Bring your awareness to the sensations of breathing You may softly count your breaths, one to ten and then start over Once your mind settles down during the first few minutes, get more absorbed in the breath Be aware of whatever is moving through the mind 1 2 3 4 5
  27. 27. 69McKinsey & Company The Hour Glass Your guide to mindfulness McKinsey & Company
  28. 28. 70McKinsey & Company 70McKinsey & Company 5/60 3% full 1/60 50% full
  29. 29. 71McKinsey & Company71 Section 1 “The trouble is you think you have time”
  30. 30. 72McKinsey & Company 72McKinsey & Company The Human Genome Project Timeline 1985 2000
  31. 31. 73McKinsey & Company MIT announces that driverless car cannot be implemented before 2030s Autonomous driving 2004 STOPSTOP until 2030
  32. 32. 74McKinsey & Company DARPA announces the "Grand Challenge" for autonomous vehicles 2004/ 2005 Autonomous driving
  33. 33. 75McKinsey & Company Google Car debuts and takes a blind man for tacos 2010 Autonomous driving
  34. 34. 76McKinsey & Company Tesla announces driverless car with ability to drive "across U.S." for mass production S-model in 2017 2016 Autonomous driving
  35. 35. 77McKinsey & Company DeepMind’s AlphaGo matches in Spring 2016
  36. 36. 78McKinsey & Company 1883 1949 1979 2015 1913 +300,000 -10,000 Speed of innovation
  37. 37. 79McKinsey & Company
  38. 38. 80McKinsey & Company80 Section 2 “Change is inevitable. Progress is optional.”
  39. 39. 81McKinsey & Company Question VS.
  40. 40. 82McKinsey & Company Connectivity and processing power Billions of people connected on the go, unprecedented processing power, storage, and knowledge access New stakeholders vs incumbents Value created by entrants that provide value from data Incumbents threatened New points of view New way of looking at decisions and events across physical, digital & biological worlds New business models Emergence of new disruptive business models reshaping production, consumption and delivery models Incentives redefined Intermediate players in value chain must enable data, promote transparency Why does machine learning matter
  41. 41. 83McKinsey & Company End-to-end analytics transformation driven by cultural and organisational change Motorsports CONTEXT RESULTS 40% JOURNEY 20% •  Formula 1 is the largest racing series in the world •  Continuous in-season engineering improvements are key to winning on the track •  Spend on testing is heavily limited by regulations •  Innovative use of communication data to find the most effective R&D operating model •  Analytics-empowered teams now able to focus on optimising parts with highest predicted potential Improvement in investment yield Earlier warning on project performance What is possible? CLIENT EXAMPLE
  42. 42. 84McKinsey & Company Boosting traditional P&L levers Delivering the digital model Developing new areas of growth Strategic priorities Gather and analyse real-time data to fully realise digital and seamless multi- channel experience Explore new operating and business models Generate revenue and improve margin, optimise efficiency, control and manage risks What are the opportunities for you?
  43. 43. 85McKinsey & Company Driving change across your company Improve Margin Material cost reduction by reduced complexity of components 5-10% Inventory buffer reduction through improved forecasting >50% Improved R&D productivity driving reduced time to market 20%Revenue uplifts through improved sales force effectiveness at same cost base 15% Component complexity management Supply chain forecasting and inventory management Digital procurement and R&D Sales force cost efficiency and effectiveness Yield management Yield improvement through improved planning 2-4% Generate Revenue Improve MROI by modelling marketing spend effectiveness 300% 20% Increase sales through better Next Best Action suggestions Increase conversion by tailoring commercial solutions to customers 75% Increase potential customer by identifying new high potential customers 8-10% Reduce churn rate through improved customer profiling 20-25% Marketing and new customer onboarding Product sales: cross and up- selling (NBA) Value-added services and solution tailoring Customer base acquisition Customer retention
  44. 44. 86McKinsey & Company Machine Learning Based Study Largest 500,000 companies 350 TB unstructured business data 10 Million business relationships 100 Million people behavioural data 15 Billion page views Classified companies into levels of AI Maturity…
  45. 45. 87McKinsey & Company Even where AI capability exists, maturity is low Companies employing AI at scale 967 494 87Strategic direction for business Building applications Lab projects/proof of concept
  46. 46. 88McKinsey & Company Application of AI concentrated in digital and data based business 60% in digital and data based businesses Companies investing in AI by industry Analyzed by spiderbook 8.78% Internet 4.19% Telecommunications 3.37% Research 2.66% Retail 2.55% Marketing and advertising 32% Software information technology services 2.35% Financial service 2.15% Automotive 2.04% Government administration 1.33% Internet 1.33% Telecommunications 1.33% Research 1.53% Retail 1.63% Marketing and advertising 1.63% Financial service 1.74% Banking 1.84% Management consulting 1.94% Semiconductors 1.33% Internet 0.92% Internet
  47. 47. 89McKinsey & Company Question VS.
  48. 48. 90McKinsey & Company The Fortune 1000 company churn rate 1973 1983 1993 2003 2013 35% 45% 60% 70% Companies new to the Fortune 1000 2023 over 80% Companies expected to fall
  49. 49. 91McKinsey & Company91 Section 3 “May your choices reflect your hopes, not your fears.”
  50. 50. 92McKinsey & Company What can you do for your company?
  51. 51. McKinsey & Company 93 # 1 Vision: Unreasonable aspirations
  52. 52. McKinsey & Company 94 # 1 Vision: Unreasonable aspirations Vision Processes Business demand Location Sourcing & partner mgmt. People Organization Architecture Governance
  53. 53. McKinsey & Company 95 What does this mean? What does this not mean? ▪ Board level "owner" ▪ Stretching and coherent vision ▪ Value-oriented targets ▪ Adding “analytics” to existing responsibilities ▪ Uncoordinated, one-off initiatives ▪ Slot time-to-market # 1 Vision: Unreasonable aspirations
  54. 54. Decision as the focal point End-to-end connection from data to decision (people, IT, processes) Step-by-step approach to enable organization Use cases 96McKinsey & Company # 2 Use cases: Driving change
  55. 55. 97McKinsey & Company # 2 Use cases: accelerator –what it means for an organisation The strategic question Identify similar use cases Develop hypotheses Embedding Apply analytics Develop decision support Break into use cases Design and build the data lake Test and refine Insights Factory 1 2 3 4 5 6 7 8 9 Links to Insights Factory
  56. 56. 98McKinsey & Company # 2 Use cases: Accelerator – how to get it right § There is an opportunity to rapidly capture significant value § The current business model has an existing analytics interlock § You plan to use returns on high- value use cases to finance an analytics transformation § You need to quickly develop and attract analytics talent §  Forming silos with sub-scale teams §  Failing to unlock value through synergies §  Failing to change the wider organisational culture §  Missing exploration of new business models due to focus on current problems When to choose What to watch out for
  57. 57. # 3 Foundation excellence Flexible big data IT stack (Lambda architecture) IT/Infrastructure Agile and flexible software development (e.g., scrum teams, microservices) IT/Software New capabilities (data engineers and scientists, analytical engineers, software developers, GUI designers) Capabilities and talent Full spectrum of analytics from r egression to ensembled learning Analytics
  58. 58. 100McKinsey & Company #3 – Foundation Excellence: what it means for an organisation Culture Reactive to market dynamics Proactively taking advantage of and defining market dynamics IT Traditional warehouse with siloed data Integrated architecture based on data lake Organisation Traditional organisation with CDO Clearly defined roles in agile organisational structure Processes Independently-designed processes for each business unit Aligned, data-enabled processes with organisation-wide workflows Recruit talent externally Build talent internallyEmployees Data used by few to manage efficiently Democratisation of dataData Central closed platform, capable of basic analytics Distributed open platform used for advanced analytics Analytics Decisions based on periodic reporting Decisions made in real time Performance management From To
  59. 59. 101McKinsey & Company #3 – Foundation Excellence: how to get it right 101McKinsey & Company When to choose What to watch out for When to choose What to watch out for §  There is clarity on specific needs for use cases §  It is possible to pilot in smaller business units §  There is strong political will to implement the programme §  Long term foundation-only projects §  ‘Build it and they will come’ mentality §  Uncontrolled data ingestion
  60. 60. 102McKinsey & Company What can you do for yourself?
  61. 61. Personal experience: Building your digital & analytics skills Example: Pursuing “analytics” enlightenment (e.g., through Coursera) §  Code in a day §  Data in a day §  Hacking in a day §  Tech in a day §  Innovation in a day 1. Innovation Data Skills Leadership Infrastructure
  62. 62. Personal experience: Visiting the disruptors Example: Doing a Board offsite at a Silicon Valley ‘bootcamp’ 2. Silicon Valley – still the capital of tech
  63. 63. McKinsey & Company And it is not just the Valley!
  64. 64. Personal experience: Establish Analytics Advisory Council 3. Serial analytics entrepreneur CDO of non- competing firm Technology leader “Wacky” digital evangelist/futurologist CEO of a tech start-up bootcamp Senior partner at a tech VC fund Digitalle/savvy customer of the company
  65. 65. Personal experience: Get a reserve mentor 4.
  66. 66. Personal experience: Five at five 5.
  67. 67. 109McKinsey & Company109 Section 4 “Those who cannot change their minds or ways cannot change
  68. 68. Learn, don’t protect. “Leadership and learning are indispensable from each other.” – JF Kennedy
  69. 69. Be an adaptive leader – not a technical one. Beta 13-40 Hz Alpha 7-13 Hz Theta 4-7 Hz Delta 0-4 Hz
  70. 70. “A problem cannot be solved at the same level of consciousness that created it. You must learn to see the world anew.” - Einstein Serve others rather than yourself.
  71. 71. McKinsey & Company Let go, don’t be attached. “It is not because things are difficult that we do not dare, it is because we do not dare that they are difficult.”– Seneca
  72. 72. 127
  73. 73. The only way is forward @tommituovila @nestecorp
  74. 74. © Wärtsilä In one year: We serve 12,000 customers 115,000 deliveries, constituting more than 900,000 line items, packed in 134,000 packages Around 106,000 transportations making use of roughly 150 carrier modalities Our 3,600 field service professionals perform 100,000 field service jobs 16,300,000 kg of parts, with a total volume of 46,700 m3 66,700 export declarations We maintain knowledge and skills for 350 different product types 117,000 unique materials stored We provide 100,000 technical answers We maintain 600 installations under long-term contract ...One promise to the customer: We offer expertise, proximity and responsiveness for all customers in the most environmentally sound way. WÄRTSILÄ SERVICES
  75. 75. © Wärtsilä 12,000 Customers 100,000 Field Service and workshop jobs 450 Installations with long-term contracts 900,000 Parts order lines 350 Product types 20,000 Technical answers Ei kädet ristissä rikkaiksi tulla.
  76. 76. © Wärtsilä Minkä ilotta oppii, sen surutta unohtaa.
  77. 77. © Wärtsilä Kysyen kylän löytää.
  78. 78. © Wärtsilä Kylhä työlki elää, mut kaupal rikastuu.
  79. 79. © Wärtsilä POHJA- TYÖ UTELIAS MIELI TUKIJOUKOT ASIAKAS- ARVO
  80. 80. © Wärtsilä
  81. 81. DREAMFORCE TO YOU 2016 ENABLING PERSONALISED CUSTOMER JOURNEY @arivee_ www.linkedin.com/in/arivant CMO Ari Vänttinen, Comptel Corporation
  82. 82. “ YOU CHANGE THE STORY AND YOU WILL CHANGE THE BUSINESS.
  83. 83. MARKETING FOR GOOD! NEW ERA
  84. 84. WE ARE LIVING MAGICAL TIMES IN MARKETING.
  85. 85. Why-How- What?
  86. 86. GENERATION FLUX IS IN CHARGE NOW. 1) POWERSHIFT
  87. 87. “ I WANT” “THANK YOU SUCCESS FORMULA “ I WANT” “THANK YOU”
  88. 88. 1) MOBILE YOUR CUSTOMER IS MOBILE! Mobile is the new TV!
  89. 89. VIRALITYDEMANDATTENTI ON 3) MARKETING ROI
  90. 90. Why? POWER SHIFT CUSTOMER IS MOBILE MARKETING ROI
  91. 91. Why-How- What?
  92. 92. FORGET B2B, B2C ----- YOU ARE IN BUSINESS TO MOMENTS! 1) CREATE VALUE IN-THE- MOMENTS
  93. 93. “I WANT” “I NEED” “I BUY” “I CHOOSE” “I LEARN” - MOMENTS PERCEIVED VALUE CURVE DELIVER VALUE HERE!
  94. 94. STOP BUYING ATTENTION, START PAYING ATTENTION! 2) FROM CAMPAIGNS TO JOURNEYS
  95. 95. HELLO WORLD, I AM THE INTERNET OF ME 3) IT´S NOT ABOUT THE CUSTOMERS BUT A CUSTOMER
  96. 96. MASS YOUR MARKET USED TO BE HERE! YOUR MARKET WILL BE HERE! LONG TAIL
  97. 97. How? CREATE VALUE IN-THE-MOMENTS FROM CAMPAIGNS TO JOURNEYS THINK NOT THE CUSTOMERS BUT A CUSTOMER
  98. 98. Why-How- What?
  99. 99. DATA REFINERY -­‐  INTELLIGENT  FAST  DATA  FABRIC  ™   FASTERMIND™ Customer Engagement Intelligence & Automation •  Engagement actions •  Journey Builder •  Next Best Actions •  Recommendations •  Real Time Profiling Relevant Other DataRelevant Fast Data CUSTOMER ENGAGEMENT AUTOMATION   ACTIONS IN THE MOMENTS MACHINE LEARN. OPTIMIZE .SCALE Channels
  100. 100. Thanks! Let’s amaze customers.
  101. 101. THE FIRST 50 JOIN FREE! GO TO NEXTERDAYNORTH.COM FREE CODE: Nexterday4Salesforce
  102. 102. www.salesforce.com/fi/blog  

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