DATA REVOLUTION: How changes in data collection and analysis are changing the world around us José María Álvarez-Pallete Cambridge, MA, April, 14th 2016
The biggest technology revolution period in human history United Kingdom United States INDUSTRIAL INTERNET Telegraph 2.5 WATT s Steam Machine Steam Locomotive Electric Generator Running Water Radio Broadcasting PC Mobile Data Web 2.0 1.5 1.0 0.5 0 (GDP per cápita, % increase year over year 1300 50 1650 1700 50 1800 50 1900 50 2010 2020 Source: Gordon 2012 & GE 2012 1
Drastic adoption cycles reduction Diffusion Rate: Years to reach 50 million Number of devices multiplies with each new technology 1880 1960 Telephone 75 years MAINFRAME + 1 M Radio 38 years MINI COMPUTER + 10 M TV 17 years PC + 100 M Internet 4 years DESKTOP INTERNET + 1 Bn Facebook 3.5 years MOBILE INTERNET + 5 Bn Angry Birds 35 days!!! INTERNET OF THINGS + 20 Bn 2015 2030 Source: Web research & Morgan Stanley, 2015. 2
The pace of technological disruption is faster than ever Storage and computation costs Capacity $569 Price per Gigabyte 10 TB 1979 $222 Laptop battery cost CAGR -15% 2005 2015 Price per 1 Mm transistors 2015 $0.06 $0.03 Source: Deloitte University Press 1991 1995 1999 2003 2007 2011 2015 3
Exponential growth of data Data/Month 800 EXABYTES 200 TERABYTES 800 TERABYTES 2.400 PETABYTES 20 EXABYTES 80 EXABYTES 1995 2000 2005 2010 2015 2020 Source: Alcatel Lucent 4
Digital disruption Hotel Industry Food Industry 25.5 $Bn 4.9 $Bn 9.2 $Bn 0.9 $Bn Estimated Value 2015 Market Cap 2015 Transport Industry Market Cap 2015 Market Cap 2014* Telecom Industry 62.5 $Bn 19 $Bn 3.6 + 6.3 $Bn 9,8 $Bn Estimated Value 2015 Market Cap 2015 Note: Campofrio s market Cap. as of 31 Dec 2014. The company was acquired by Alfa in June 2015. Source: Bloomberg, TWSJ & Company information 5 Adquisition Value (by Facebook 2014) Adquisition Value (by Telefónica 2010)
Increasing demand for sophisticated data analysis skills Cumulative Number of Data Scientists Over Time (Thousands) Data Scientists Per Company. Top 25 2014 14 12 10 8 6 4 2 0 x2 over the last 4 years 1995 2000 2005 2010 2015 Microsoft Facebook IBM GlaxoSmithKline Booz Allen Hamilton Nielson GE Apple Linkedin Teradata HP Intel Twitter Capital One Google Accenture Oracle SAS AT&T Amazon Groupon King Allstate American Express Capgemini 0 50 100 150 200 250 65% of the students entering primary school today will end up working in new jobs that do not exist yet Source: Forbes, WEF 6
Digital Globalization: The new era of global flows Data flows are soaring Cross Border Data Flows 2014 45x growth in data flows 2005-2014 Trade Finance Data Bandwidth (Gbps) <50 50-100 100-500 500-1,000 1,000-5,000 5,000-20,000 >20,000 1980 2014 Global flows increase economic growth 100% = 211.3 Tbps (Terabits per second) 10% increase in world GDP, worth ~7.8 Tn USD en 2014 2.8 Tn USD GDP increase from data flows, large impact than goods trade ~50% potential GDP boost for some countries by increasing participation in global flows Source: McKinsey Global Institute 7
Evidence that digital and social networks are isomorphic Social Network based on mobility Network based on phone calls Source: Coscia & Hausmann 8
Building geographical interaction graphs Mobility graph 25 Bn records analyzed Mobile-calls graph Fixed-calls graph 1.9 Bn records analyzed Source: Internal Data 9 230 Mn records analyzed
Mobile-calls High correlation between mobility and mobile-calls networks Infomap communities Normalized Mutual Information 0.81 Source: Internal Data Mobility 10
Community clusters built from mobility reflect real-life interaction Mobility Source: Internal Data 11
Big data, an engine for economic forecast Data Universe Time: 49 months >1.4 million series; >67 million data, 2012-2015 period Data Records: >13,000 millions >70,000 Corporations and SMEs with international traffic Data volume: 1.2 Terabytes >21,000 export and import data records Source: Internal data & DataComex 12
ene./2012 abr./2012 jul./2012 oct./2012 ene./2013 abr./2013 jul./2013 oct./2013 ene./2014 abr./2014 jul./2014 oct./2014 ene./2015 abr./2015 jul./2015 oct./2015 Similarities in the evolution of Telco and external trade data, suggest relations among series Behavioral pattern of international mobile traffic*, imports and exports (2012-2015) (mn sg) 200 180 160 140 120 100 80 60 40 20 0 Mn Euros 30.000 27.500 25.000 22.500 20.000 17.500 15.000 International Mobile Traffic (mn sg) Export (Mn euros) Import (Mn euros) *Top 1000 by total volume of international traffic (02/2016). Source: Based on Operator s aggregated and anonymized data & DataComex (2016). 13
A cross-correlation analysis corroborates the strong relation Strong Cross-correlations between time series of import/export and traffic lag 0 2012-2015 Exports 91% IMT vs Exp Imports 87% IMT vs Imp Source: Based on Operator data & DataComex (2016). 14
International traffic pattern shows signs of sectorial economic activity International mobile traffic breakdown by region 2012-2015 Construction Textile Automotive Turism Energy Europe 47% 74% 90% 76% 47% Latin America & the Caribbean North America Middle East 26% 7% 3% 11% 22% 10% 5% 3% 8% 11% 6% 1% 0,2% 1% 6% Asia 2% 8% 3% 1% 4% Africa 9% 4% 2% 3% 9% Oceania 0,5% 0,2% 0,0% 0,0% 1% Source: Based on operator s data in Spain. 15
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