The rise of the web 3.0 company, by Mr. Jacques Bughin

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The rise of the web 3.0 company, by Mr. Jacques Bughin

  1. 1. Web “3.0”Jacques Bughin,Director, McKinsey & CompanyVlerick Alumni ReunionDecember 13th, 2011
  2. 2. The web is everywherePercentage of online population 2011 Categories Weekly usage Inform/search 91 Socialize 82 Communicate 68 Transact 64 Entertain 55 6 4 5 5SOURCE: Comscore, Scott Adams, McKinsey McKinsey & Company | 1
  3. 3. The Internet time line – First two waves Crash! Wave 2 Internet video End of Wave 1 (consumers) reaches 50% of Internet trafficThe Thepast present1990 1995 2000 2001 2005 2008 2010 2011 Wave 1: First First commercial Recovery: Market More data than commercial dial up broadband cap of top 5 voice on mobile; (access) internet cos higher video streaming than in bubble time surpasses P2P Web 1.0 Web 2.0SOURCE: Morgan Stanley, McKinsey McKinsey & Company | 2
  4. 4. The Internet time line: wave 3 (the intelligent enterprise) The rise of the Twitter predicts New business extended enterprise: stock market index models in flux: 30% of innovations at volatility at more - cloud P&G is done via the than 80%; the web -open source Develop and Connect a key driver of BI competition platform -insights/analytics The present Future? Cloud computing Enterprise 2.0 Google is Development of Wireless data adoption reaching majority of nowcasting the wireless natural traffic will exceed momentum users economy; search interface fixed data traffic Recorded Future as per MIT’s describes futures “Sixth sense” McKinsey & Company | 3
  5. 5. Happy Christmas Good news – Internet has brought success Good news – This will continue along with web 3.0 McKinsey & Company | 4
  6. 6. New Year Hang over? Good news – Internet has brought success Good news – This will continue along with web 3.0 Bad news – They will be winners and losers Bad and good news – You have to stand up McKinsey & Company | 5
  7. 7. Messages Good news – Internet has brought success Good news – This will continue along with web 3.0 Bad news – They will be winners and losers Bad and good news – You have to stand up McKinsey & Company | 6
  8. 8. Internet has contributed to society Material High social Accreditive to contribution capital impact employment to GDP Strong Arab consumer revolutions surplus McKinsey & Company | 7
  9. 9. Internet has become a strong contributor to economic activity 1995-2004Contribution to GDP growth 2004-2009Percent UK France Norway Belgium 33 25 23 18 17 6 4 6 2004- 2007- 2009 2010 Canada 4 10 US 6 15 Italy Germany Korea 24 16 2 12 10 2 McKinsey & Company | 8
  10. 10. The internet economic contribution has built social capital Social capital, 2008 Percent 100 Sweden 90 US 80 Canada United Kingdom 70 Germany 60 Belgium 50 South Korea 40 Italy France 30 20 10 0 0 5 10 15 20 25 30 35 40 Internet contribution to GDP, 2004-2009 PercentSOURCE: Legatum institute, McKinsey Global Institute and analysis McKinsey & Company | 9
  11. 11. … and led to employment Ratio of internet jobs created/reduced, last 3 years 3,5 Sweden 3,0 2,5 Belgium 2,0 Canada South Korea Germany 1,5 France 1,0 US Italy 0,5 0 0 5 10 15 20 25 30 35 40 Internet contribution to GDP, 2004-2009 PercentSOURCE: McKinsey Global Institute and analysis McKinsey & Company | 10
  12. 12. Messages Good news – Internet has brought success Good news – This will continue along with web 3.0 Bad news – They will be winners and losers Bad and good news – You have to stand up McKinsey & Company | 11
  13. 13. The new firm Up to now Web 3.0 1 Closed system and IP rules 1 Open system and open source: the extended enterprise 2 Social media relatively hermetic to 2 Social media reaching scale companies within enterprise and becoming embedded in processes 3 Strategic planning process; 3 Real time business intelligence discretionary business intelligence through big data 4 Capabilities defined by functions 4 New hierarchy, new business and work responsibilities by models, new markets (e.g., crowd hierarchy working) 5 In-source or outsource 5 Elastic sourcing (cloud) McKinsey & Company | 12
  14. 14. Open system and open source: Examples Consumer Cos- Media Car Mobile Health Goods metics Handsets1990 1995 2000 2005 2010 Operating Web Motor- Cars Encyclo- Drug Pros- Text- systems servers cycles pedias design thetics books Open Linux Apache prosthetics projectSOURCE: Literature search, McKinsey McKinsey & Company | 13
  15. 15. Social media reaching scale within enterprisePercentage of Companies, n=3103 Social Micro- Prediction Blogs Wikis, networking blogging markets n = 1,322 n = 809Dimensions Total n = 1,728 n = 654 n = 190Scanning external 75 40 29 9 13 5environmentFinding new ideas 73 36 29 12 13 4Managing projects 55 19 12 17 5 2Developing strategic plan 43 16 11 8 5 4Allocating resources 30 10 5 4 2 2Matching employees to tasks 29 11 4 5 3 1Assessing employee 26 7 4 3 2 1performanceDetermining compensation 20 6 4 2 1 1SOURCE: McKinsey web 2.0 survey, 2011, McKinsey Quarterly McKinsey & Company | 14
  16. 16. Big data features Massive amount versus Limited, one-shot for experimentation Real-time versus Lagging Sometimes ahead versus Lagging of time Easy mash-up versus Separate sets of non inter-operable data Behavioral and versus Stated intent based Data in nodes versus Separate McKinsey & Company | 15
  17. 17. Massive amount: Big data (brother?) is watching you 1 billion 800 million - Facebook - Google searches active users worldwide, conducted of which 10% of a day worldwide conversations by 2010 involving a brand 15 billion 19% information codified by proportion of Twitter Recorded Future comments referring to a brandSOURCE: Literature search, Recorded Future blog, Jansen et alii (2009) McKinsey & Company | 16
  18. 18. Massive amount: Big data (brother?) is watching you 1.5 Billion - Google searches Leading to sales transaction monthly … Billions Nielsen monthly points of sales transactionSOURCE: Google, Nielsen analysts presentation, McKinsey McKinsey & Company | 17
  19. 19. Big data nowcasting: CPG product launch and search SalesIndex; normalized 100 at launch date Online searches Presales Intensity Percent 140 120 100 80 60 40 20 0 One week 1st week 2nd week 3th week 4th week 5th week before Launch after after after after after launch launch launch launch launch launchSOURCE: Google insights, McKinsey McKinsey & Company | 18
  20. 20. Big data nowcasting: car sales and searchMonthly sales vs. Google search trends at second week of each month, USSOURCE: Automotive News Data Center; Google McKinsey & Company | 19
  21. 21. Big data nowcasting: DTV subscription and Search ESTIMATESQuarterly sales/total vs. Google search trends 6 weeks in advance, Europe 12 9 6 Regression fit 3 Y = 2,1 + 0,21.X 0 R² = 0.78 0 20 40 60 80 100 P = 0.00 Search queriesSOURCE: Telecom sales report, Google search for insights, McKinsey analysis McKinsey & Company | 20
  22. 22. Giants are taking data seriously "[I] can imagine [data] being more valuable than a brand." Bob McDonald, CEO of P&G https://www.mckinseyquarterly.com/Inside_ PGs_digital_revolution_2893 McKinsey & Company | 21
  23. 23. Big data nowcasting: movie box office and social mediaBox office index vs. social mentions 2 weeks in advance, worldwide Box office index 1.0 0.8 0.6 0.4 0.2 Regression fit 0 Y = 0.18 + 5.5.X 0 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 R² = 0.88 Retweet rate P = 0.00 PercentSOURCE: Huberman et alii (2010), First Monday, Google, McKinsey McKinsey & Company | 22
  24. 24. Messages Good news – Internet has brought success Good news – This will continue along with web 3.0 Bad news – They will be winners and losers Bad and good news – You have to stand up McKinsey & Company | 23
  25. 25. Revenue increase linked to the use of internet High 5.3 8.5 8.8 Web Middle 4.4 4.8 6.5 intensity Revenue impact high-low: 2.3x 3.8 4.6 5.4 Low Low Middle High Extended enterpriseSOURCE: McKinsey SMB survey, MGI McKinsey & Company | 24
  26. 26. Extended enterprise – The tail of two companiesCosmetics MotorcycleSouth Korean cosmetics market share Vietnamese motorcycle market share 40 Missha 75 70 Loncin 35 and other 65 Chinese 60 co-creators 30 55 50 25 45 40 20 35 30 15 25 Honda LaNeige 20 and 10 Ettude affiliates 15 10 Other 5 5 Suzuki 0 0 2002 03 04 2005 1998 99 2000 01 2002 McKinsey & Company | 25
  27. 27. Big Data companies seem to outperform peers Big data leaders1999-2009 (10-year CAGR); Percent Other competitors Revenue EBITDA Online retailers 24 22 -1 7 Casinos 9 12 5 1 Insurance 9 14 8 5SOURCE: Bloomberg and Datastream; annual reports; McKinsey CPAT tool; McKinsey analysis McKinsey & Company | 26
  28. 28. Messages Good news – Internet has brought success Good news – This will continue along with web 3.0 Bad news – They will be winners and losers Bad and good news – You have to stand up McKinsey & Company | 27
  29. 29. Companies are slowly recognizing the new gameLikeliest organizational changes in next 3 years, worldwidePercentage of respondents; N = 4,261 Companies with majority Average of web technology usage Extended enterprise 35 68 Self-organization 32 61 Data driven decision 32 72 and intelligence Informal and agile 27 49 hierarchy Financial transparency 19 39SOURCEMcKinsey web 2.0 survey, the extended enterprise McKinsey & Company | 28
  30. 30. Implications for organization leaders 1 Build new massive capabilities in web 3.0 2 Design open-based organization Accept multi-personae: customer as buyer, participant, 3 buzzer, etc. Redefine information cloud strategy to implement 4 technology 5 Experiment fast McKinsey & Company | 29
  31. 31. Thank you

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