Patrick Couch - Intelligenta Maskiner & Smartare Tjänster

© 2014 IBM Corporation

BusinessConnectA New Era of Smart

Intelligenta Maskiner & Smarter TjänsterPatrick Couch, IBM

© 2014 IBM Corporation2

A New Era of Smart

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The Elevator Pitch

1. Ni vet hur maskiner & apparater av alla slag blir allt mer instrumenterade?

2. Och ni vet hur dessa maskiner och apparater blir allt mer ihopkopplade med

varandra?

3. Och ni känner säkert alla till att dessa maskiner & apparter blir alltmer

intelligenta?

4. Ni förstår givetvis att detta öppnar upp för en mängd helt nya affärsmöjligheter.

5. Och även att både era konkurrenter och era kunder förstår detta.

6. Den stora frågan är: Vad gör ni av detta? Hur gör ni dessa aspekter till

framgångsfaktorer för just er verksamhet, för just ert företag?


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The Internet of Things

“In 2020, Over 30 Billion Connected Devices Will Be In Use.” – Gartner (link)

“There will be 212 B devices or things connected to networks by 2020” - IDC (link)

“Driven by reducing price per connection and the consequent rapid growth in the number of machine-to-machine (M2M) connections, we expect the number of connected objects to reach 50bn by 2020 (2.7% of things in the world).” – Cisco (link)

“There are more than 10 billion wirelessly connected devices in the market today; with over 30 billion devices expected by 2020..” – ABI Research (link)

“From vehicles and smart phones to containers and machines – by 2015 more than six billion things will be connected to the internet.” – Bosch (link)

Business Insider Intelligence: Global Internet Device Installed Base Forecast

Source: Installed base forecast: http://www.businessinsider.com/growth-in-the-internet-of-things-2013-10


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Big Data – ones and zeros...

Sources: OECD Broadband Statistics, June 2013; IDC, “ Internet of Things (IoT): Realizing Value Through Intelligent Business Transformation,” March 2014; IBM GTO 2014; Forrester, “Mapping The Connected World,” October 2013; IBM HorizonWatch, “Internet of Things,” January 2013, Wikipedia

Ex

ab

yte

s

2005 2010 2015 2020

% of machine generated data

Size of machine generated data

The exabyte is a multiple of the unit byte for digital information. The prefix exa indicates multiplication by the sixth power of. Therefore one exabyte is one quintillion bytes (short scale).

1 EB = 1.000.000.000.000.000.000 B = 1.000 Peta Bytes = 1 million TeraBytes = 1 billion Giga Bytes.


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Big Data – How big is Big?

Ford Fusion: 145 actuators*, 4.700 relays and 70 sensors, including radar, sonar, accelerometer, camera, rain sensors. Collectively, these devices generate more than 25 gigabytes of data per hour, which is processed by more than 70 on-board computers.

* According to the Wikipedia; An actuator is a type of motor that is responsible for moving or controlling a mechanism or system.


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The opportunity: Services

“Service Revenues for the IoT will reach $500 Billion by 2018, dwarfing the $33 Billion in revenue expected from devices in 2018” - Harbor Research (link)

“Sized applications of the Internet of Things could have direct economic impact of $2.7 trillion to $6.2 trillion per year in 2025.” – McKinsey (link)

Bloomberg Article: Cisco CEO Pegs Internet of Things as $19 Trillion Market

“Economic value-add (which represents the aggregate benefits that businesses derive through the sale and usage of IoT technology) is forecast to be $1.9 trillion across sectors in 2020. The verticals that are leading its adoption are manufacturing (15 percent), healthcare (15 percent) and insurance (11 percent)..” – Gartner (link)

“IoT product and service suppliers will generate incremental revenue exceeding $300 billion, mostly in services, in 2020.” – Gartner (link)

ZDNet Article: Internet of things: $8.9 trillion market in 2020, 212 billion connected things

“IoT technology and services spending to generate global revenues of $4.8 trillion in 2012 and $8.9 trillion by 2020, growing at a compound annual rate (CAGR) of 7.9%.” – IDC (link)


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The Challenge: Customers & Competitors

Individuals are more connected and empowered

Increased consumer expectations

Different ways to engage digitally

Expanded information transparency

Operations and business models are being transformed

Redefined consumer value

Integration across digital with physical

Concerns around risk, security, compliance and privacy

Competition is coming from new and different areas

New competitors from different industries

Changes in value migration; new winners and losers

New types of collaboration

Business Challenges

Business Challenges

Business Challenges

Mobile revolution

Social media explosion

Cloud Enablement

Power of analytics

ForcesForces

Source: 2011 IBM Digital Transformation Study, IBV Analysis


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The Solution: Transformation

Organizations transition from intense focus on operating costs toward growth and transformation1

New business models are impacting organizations and industries

64% of executives believe new business models will impact their industries more profoundly than

ever before2

37% of executives say new disruptive business models will

be the biggest organizational impact on their companies3

Anticipated change (%) between previous 3 years and next 3 years

Sources [1] 2013 CEO Study Q5: “What are the top priorities in your business strategy”; (n=4183); [2] 2013 Global Digital Reinvention Executive Study Q12: “Please rate the extent to which the following trends will have an impact on your business” (n = 1089); [3] 2013 Global Digital Reinvention Executive Study Q24: “What is your biggest organizational change likely to be caused by digitization?” (n = 1090);


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Transformation: It’s all around D

egre

e o

f ec

on

om

ic im

pac

t (f

unct

ions

, in

dus

trie

s, g

eogr

aph

ies)

Digital products and infrastructure

• Digital products (e.g. Music, Entertainment)

• Infrastructure (e.g. Telco, Software, IT Infrastructure)

Digital products and infrastructure

• Digital products (e.g. Music, Entertainment)

• Infrastructure (e.g. Telco, Software, IT Infrastructure)

Digital distribution and web strategy

• e-commerce (e.g. Retail, Electronics)

• Efficiency through web strategy (e.g. Government)

Digital distribution and web strategy

• e-commerce (e.g. Retail, Electronics)

• Efficiency through web strategy (e.g. Government)

Late 1990sLate 1990s 2000s2000s 2010s2010sLimitedLimited

Time

PervasivePervasive

Digital transformation of business models

• Mobile revolution• Social media• “Hyper digitization” • Power of analytics

Source: Source: BM Institute for Business Value: Digital Transformation Creating new business models where digital meets physical


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Transformation: That means business model innovation

Redefine existing industries

Business Model Innovation

IndustryModel Innovation

EnterpriseModel Innovation

RevenueModel Innovation

Do as much as possible within your organization

Pricing innovation

Create entirely new industries

Move into new industries Payer innovation Specialize by focusing on differentiating activities

Intensively collaborate with external partners

Changing the way your industry works or changing your value chain

Changing your value proposition or the way you price for products/services

Changing what you do and where you collaborate

Package innovation


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The Enabler: AnalyticsUnderstanding how to create value from data (…has been the focus of IBM’s analytics studies for 5 years)

Analytics: The new path to value

Operationalizing analytics in

sophisticated organizations

Analytics: The widening

divide

Mastering analytic competencies

Analytics: The real world use

of big data

Fundamentals of big data

Analytics: A blueprint for value

Extracting value from data and

analytics

2010 2011 2012 2013

The intelligent enterprise and

Breaking away with BAO

2009

Defining analytics as a strategic

asset


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Analytics: What is it?

How can everyonebe more right…….more often?

How can everyonebe more right…….more often?

Descriptive

Prescriptive

Predictive

Cognitive

What has happened?

What could happen?

How can we achieve the best outcome?

Tell me the best course of action?

Big Data & Analytics

Big Data & Analytics

How is data managed and stored?

Business Value

Business Value

Information Layer


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Analytics Success Factors: Characteristics of a Leader

80% of Leaders measure the impact of analytic investments.

66% of Leaders see analytics investment ROI of under 12 months measurement.

60% of Leaders have predictive analytic capabilities.

Leaders are 166% more likely to make most decisions based on data.

Almost two-thirds of Leaders are confident enough with the data and analytics available to them to use it in their day-to-day decision-making processes.

57% of business executives within Leader organizations oversee the use of data and analytics within their own departments, guided by an enterprise-level strategy, common policies and metrics, and standardized methodologies.

Leaders are 221% more likely to have formal career path for analysts, and 130% more likely to think analytics talent is very import

Leaders were defined based on their self-reported performance within their industry and market and who attribute much of their success to analytics.

Identifying Leaders

Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value


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Wrapping up and returning to Ford Fusion

Mike Tinskey, director of vehicle electrification and infrastructure, describes the data collected from the vehicles as “small but growing” (Ref: 25GB/Hour). He says “We gather data every time the customer plugs in. We know where they’re plugging in, how many gas miles they drove, how many electric miles, how often they plug in and how often they take trips. It’s helping to shape where we go next with products.” One proposed use of this data is to work out ‘peak times’ of energy usage, and charge customers a lower rate if they refrain from plugging in when power demand is high.

Source: http://dataconomy.com/how-big-data-brought-ford-back-from-the-brink/