\n\nThe document discusses the evolution of the internet and the rise of "web 3.0". It provides statistics on internet usage and outlines three waves of the internet - web 1.0, web 2.0, and the emerging web 3.0. Web 3.0 is characterized by an intelligent enterprise, real-time business intelligence using big data, and new open business models utilizing tools like cloud computing and crowdsourcing.\nThe document also examines the economic and social impacts of the internet. It has significantly contributed to GDP growth, increased social capital, and led to more jobs being created than reduced in several countries. However, it notes there will be both winners and losers with the continuing evolution of web 3.0.\n

1. Web “3.0”
Jacques Bughin,
Director, McKinsey & Company
Vlerick Alumni Reunion
December 13th, 2011

2. The web is everywhere
Percentage of online population 2011
Categories Weekly usage
Inform/search 91
Socialize 82
Communicate 68
Transact 64
Entertain 55
6
4
5
5
SOURCE: Comscore, Scott Adams, McKinsey McKinsey & Company | 1

3. The Internet time line – First two waves
Crash! Wave 2 Internet video
End of Wave 1 (consumers) reaches 50% of
Internet traffic
The The
past present
1990 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 2.0
SOURCE: Morgan Stanley, McKinsey McKinsey & Company | 2

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. Happy Christmas
Good news – Internet has brought success
Good news – This will continue along with web 3.0
McKinsey & Company | 4

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. 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. 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. Internet has become a strong contributor to economic activity 1995-2004
Contribution to GDP growth 2004-2009
Percent
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. 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
Percent
SOURCE: Legatum institute, McKinsey Global Institute and analysis McKinsey & Company | 9

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
Percent
SOURCE: McKinsey Global Institute and analysis McKinsey & Company | 10

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. 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. Open system and open source: Examples
Consumer Cos- Media Car Mobile Health
Goods metics Handsets
1990 1995 2000 2005 2010
Operating Web Motor- Cars Encyclo- Drug Pros- Text-
systems servers cycles pedias design thetics books
Open
Linux Apache prosthetics
project
SOURCE: Literature search, McKinsey McKinsey & Company | 13

15. Social media reaching scale within enterprise
Percentage of Companies, n=3103
Social Micro- Prediction
Blogs Wikis,
networking blogging markets
n = 1,322 n = 809
Dimensions Total n = 1,728 n = 654 n = 190
Scanning external 75 40 29 9 13 5
environment
Finding new ideas 73 36 29 12 13 4
Managing projects 55 19 12 17 5 2
Developing strategic plan 43 16 11 8 5 4
Allocating resources 30 10 5 4 2 2
Matching employees to tasks 29 11 4 5 3 1
Assessing employee 26 7 4 3 2 1
performance
Determining compensation 20 6 4 2 1 1
SOURCE: McKinsey web 2.0 survey, 2011, McKinsey Quarterly McKinsey & Company | 14

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. 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 brand
SOURCE: Literature search, Recorded Future blog, Jansen et alii (2009) McKinsey & Company | 16

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 transaction
SOURCE: Google, Nielsen analysts presentation, McKinsey McKinsey & Company | 17

19. Big data nowcasting: CPG product launch and search Sales
Index; 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 launch
SOURCE: Google insights, McKinsey McKinsey & Company | 18

20. Big data nowcasting: car sales and search
Monthly sales vs. Google search trends at second week of each month, US
SOURCE: Automotive News Data Center; Google McKinsey & Company | 19

21. Big data nowcasting: DTV subscription and Search ESTIMATES
Quarterly 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 queries
SOURCE: Telecom sales report, Google search for insights, McKinsey analysis McKinsey & Company | 20

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. Big data nowcasting: movie box office and social media
Box 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
Percent
SOURCE: Huberman et alii (2010), First Monday, Google, McKinsey McKinsey & Company | 22

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. 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 enterprise
SOURCE: McKinsey SMB survey, MGI McKinsey & Company | 24

26. Extended enterprise – The tail of two companies
Cosmetics Motorcycle
South 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. Big Data companies seem to outperform peers Big data leaders
1999-2009 (10-year CAGR); Percent Other competitors
Revenue EBITDA
Online retailers 24 22
-1 7
Casinos 9 12
5 1
Insurance 9 14
8 5
SOURCE: Bloomberg and Datastream; annual reports; McKinsey CPAT tool; McKinsey analysis McKinsey & Company | 26

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. Companies are slowly recognizing the new game
Likeliest organizational changes in next 3 years, worldwide
Percentage 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 39
SOURCEMcKinsey web 2.0 survey, the extended enterprise McKinsey & Company | 28

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. Thank you