Great Expectations

Cognitive Analytics for the

Service EconomyConnected

www.freedigitalphotos.netPhoto by patrisyu

2

Content

• The Industrial Economy

• Disruptions to the Industrial Economy

• Services as a Key Differentiator – A Smartphone Perspective

• Service Transformation Challenges for Electronic Companies

• Why Cognitive Analytics

• Some Use Cases of Cognitive Analytics

• Summary and Conclusion

3

What was the Industrial Economy

4

The Industrial Economy

► Part Standardization

► Assembly Modularity

► Vertical integration

Early Industrialization was built on the concept of building scale with

minimal differentiation

“You can have any color, so long as it is black”- Henry Ford, on the T-Model

Source: The Software Defined Supply Chain, IBM WP

5

Industrie 4.0 – What’s Changing?

6

The Four Transformation waves in the Industrial Economy

Source: http://www.engineersjournal.ie/wp-content/uploads/2014/05/Domhnall_Carrol-006.jpg

Importance of Scale, Standardization and the Global Supply Chain

becoming less important in Industry 4.0

7

Disruptive Technologies Enabling Industry 4.0

Intelligent Robotics 3D Manufacturing

Low Power Wide Area Networks

Cognitive Analytics

Cheap, Adaptive Robots which can work alongside humans and can be “taught” tasks without the need of programming.

Allows for smaller set-up and operating costs. Disruption in areas requiring smaller volumes with uncertain demand

Industrial internet will allow M2M communication and control

Advanced analytics and machine learning algorithms which can detect patterns from structured and unstructured sources

Open Source H/W and S/W

Maturing of Open Source S/W and H/W platforms means low licensing and development costs for products

Disruptions are lowering the entry

barrier into product manufacturing

which will erode product

differentiation in the long run

8

How is manufacturing responding to Industrie 4.0?

9

Service and Customer Innovation are key focus areas for global manufacturing

• By 2017, 70% of global manufacturers will offer connected products

• By 2016, only 20% of manufacturers will have an integrated approach to delivering service

• By 2017, 75% of leading manufacturers be doubling the investments in customer-facing technology

Note: The size of the bubble indicates complexity/cost to address

Source: IDC, 20146 of the top 10 imperatives are around

service and customer innovation which

reiterates the importance in developing

differentiated capabilities in those areas

10

How are the new companies differentiating themselves?

11

Disruption Through Service – Xiaomi Case Study

• Xiaomi is a Chinese Mobile Company founded in 2010

• Started out as a software company with a UI, MIUI based on the Android OS

• Has grown its sales volumes from 7.2 mil in 2012 to over 30* mil in 2014

• Apart from phones its product portfolio includes*:

– an online digital content store, which includes apps, games, wallpapers and themes, and ebooks and is one of the top android stores

– applications and services such as MiTalk (an IM service) and MiDrive (cloud storage)

– other hardware such as the MiBox (a smart set-top box for the TV), the MI Wi-Fi (Wi-Fi router), MI Charger (portable phone charger) and the MiTV (a 47-inch smart TV)

– accessories such as earphones, screen guards and a USB cable

*http://www.analysysmason.com/Research/Content/Comments/Xiaomi-smartphones-Feb2014-RDMD0-RDRP0/

12

Price Disruption: Comparison of Mi Phones with CompetitorsModels Mi 4 Samsung Galaxy S5 Apple iPhone 6

Display 5.0-inch full HD (1920x1080p) 5.1-inch Super AMOLED display with full HD

4.7-inch LED-backlit IPS screen with Retina HD

OS Android v4.4.3 KitKat with MIUI v6.0 Android v4.4.2 KitKat OS iOS v8.0

Chipset 2.5GHz Qualcomm Snapdragon 801 series quad-core CPU

2.5GHz Qualcomm Snapdragon 801 series quad-core CPU

1.4GHz Dual-core Cyclone CPU

GPU Adreno 330 Adreno 330 PowerVR GX6450 (quad-core graphics)

RAM 3GB LP-DDR3 993MHz 2GB DDR3 1GB

Storage Capacity 16GB [Not expandable] 16GB, expandable via micro SD card

16GB/64GB/128GB[Not expandable]

Camera Main: 13- megapixelFront: 8-megapixel

Main: 16-megapixelFront: 2.1-megapixel

Main: 8-megapixelFront: 1.2-megapixel

Battery 3080 mAh (Li-Ion Polymer) 2800 mAh battery Talk time: up to 14 hours (3G)

Network 3G LTE Cat.4 (150/50Mbps) 3G & 4G-LTE

Price* $ 330 ~$850 $891 -$1191

*All prices in India at time of launch

Pricing of Xiaomi is less then half of the competition but with similar

specs

Source: http://www.ibtimes.co.in/xiaomi-mi4-vs-samsung-galaxy-s5-vs-apple-iphone-6-specification-comparison-622035

13

Capacity and Channel Disruption: Sell small batches online and through pre-booking

Flipkart India page screen shot

Xiaomi Mi4 Flipkart Flash Sale to Go Live on 03 MarchXiaomi India Facebook page screen shothttp://www.bgr.in/news/xiaomi-mi-4-goes-out-of-stock-in-15-seconds-next-sale-on-february-17/

Sell in small batches of 30,000 and 100,000 through pre-booking process

and no formal advertisement or promotion flash sales

14

Customer Engagement Disruption – Deeper Engagement

0

5

10

15

20

25

30

MIUI Apple/Google

Average Downloads per Quarter per device (in mil)

Xiaomi users download apps at almost twice the rate of other Android users and iOS users

http://www.tech-thoughts.net/2013/09/xiaomi-international-growth-data-usage-carriers.html#.VYuQ7WMpnW5

Extremely active set of users who regularly take part in forums, blogs etc and even compete on popularity

“Fans” can vote on features and specs they want

MIUI is frequently updates ( almost weekly) and available for upgrade

15

What is different about Xiaomi?

Xiaomi Apple

Catering to lower end of the emerging markets Catering to a higher end of the markets in both developed and emerging economies

Competes through high specs at low prices Competes on product differentiation

Very small production capacity relies on small batches sold through limited online vendors

Vertically integrated across product design, OSand supply chain with large vendor capacity

Software product upgrade releases almost every week

Releases upgrades once or twice a year

Sells online and in small batches through pre-registration

Sells across multiple channels including own retail chain

Makes revenue from cross-selling and up-selling of content

Makes about 9% revenue from content. Primarily revenue through hardware

Releases a new product every 16 months on average with few very few models

Releases a new model of the product every year with multiple product-lines and SKU’s

“ People just don’t get it. The

mobile phone itself is only the

carrier” – Lei Jun, Xiaomi

Xiaomi looks at “hardware as a distribution” device rather than as a product in itself while Apple aims at product differentiation primarily

16

Takeaways from the Discussion

• Service can be source of competitive advantage

• Hardware getting more commoditized with differentiation coming from the software layer

• Brands are built not by an advertisement (telling) but through customer experience which comes as being part of the tribe

• Micro segments are what matters, not the average

17

Why Service Differentiation in Electronics?

18

Consumers are demanding considerable improvement in service quality

Source: Consumer Survey (2010) by IBM Institute for Business Value (IBV)

Service quality satisfaction levelScope for

improvement

44%

46%

52%

53%

54%

56%

56%

58%

0% 50% 100%

Interaction with device manufacturers

Interaction with service provider

Device interoperability

Account management

Usage support

Provision of user information

Stable provision of services

Number of services

A large opportunity for service improvement also points to

significant opportunity for newcomers to gain market share

19

Electronics companies are largely interested in pursuing services, to drive differentiated offerings

� Companies are driven by

defensive strategic rationales to

raise a bar for the competitors by

adding more values on H/W,

acting upon customers’ demand

� Financial benefits such as

additional revenue, high margin

and stable cash flow are not clear

yet, as most of companies are at

the early stage

Why pursuing service?

“It is getting harder to maintain the leadership position in the industry if you stick to products only. We need to reconfigure the H/W to meet customers’ needs and provide solutions and services that customers want to enhance their experience around the products.” Consumer electronics, Asia

Source: Industry Interview (N= 32) by IBM Institute for Business Value (IBV)

To achieve

competitiveness

by differentiating

offerings

To deepen

customer

relationship

To increase

perceived value in

consumer’s minds

To meet consumer

needs & demands

To create new

revenue streams

88%

38%

53%

66%

25%

20

Principles of engagement in the connection economy

“ We are moving from the industrial economy to the connection economy”- Seth Godin, Marketing Guru

1 Customers have a choice not to engage, -give them a reason to why they should

2 Mass market is no longer relevant –it’s the edges where the action is

3 The only work that matters is the work that matters – don’t ask if you will succeed, ask if you will matter to the customer

https://www.youtube.com/watch?v=sKXZgTzEyWY

21

Why is Service Differentiation difficult for product companies?

22

3 Challenges for Generating a Differentiated Service

1 Capability Issue

Fundamental difference between product and service means new capabilities required

2 Ubiquity of Data

Data explosion means that it is a question of being able to detect the signal from the noise

3 Customer Expectation

Customer expects value which is clearly defined, differentiated and personalized

23

1.The fundamental differences between manufacturing and service can create difficulties in delivering experiences

Manufacturing vs. Service

� Intimacy with channels

(e.g. on & offline retailers, N/W

operators)

� One-time transaction

� H/W manufacturing and delivery are

separable – Consumption happens

after the production

� Activities are relatively linear and

easily definable in modules

Source: IBV analysis

� Intimacy with end-users & Strong

incumbent positions

� On-going relation

� Service production and delivery are

inseparable - Consumption happens

at the very same moment as

production, making the production

and delivery of equal importance

� Activities are complex with multi-

functional traits

Need to recognize the difference and create new approaches

“Service requires creativity, flexibility and more focus on individual case, whereas manufacturing is straightforward and very R&D-focused.”

CEO,Consumer electronics, China

24

As companies will be able to interact directly with customers and have visibility into customer experiences…

Set Up Use Get HelpUpgrade/

Replace

Product

ResearchPurchase

PRE-SALE POST-SALE

� Basic user information

� Usage issues

� Product information

� Basic user information

� Purchase history

� Usage data (e.g. purchase, location, usage duration, frequency)

� Installation information

� Billing information

� Usage issues

� Product upgrade data

� Product information (Registration) - optional

Product only

Product +

Service

� More types of data on users and their usage

� More interaction points & depth

� No time lag in collecting data

Source: IBV analysis

SALE

25

2.There is an explosion in data in all forms and all sources

• Data will grow to 40 zeta bytes by 2020, a 50 fold increase from 2010

• 80% of this data will be unstructured

• 30B pieces of content are shared everyday on Facebook

• Over 181 mil public blogs in 2011 compared to 35 mil in 2006

http://dazeinfo.com/2012/03/10/number-of-blogs-up-from-35-million-in-2006-to-181-million-by-the-end-of-2011/https://blog.kissmetrics.com/facebook-statistics/

• 40B of connected devices by 2020• 99% of devices which will be connected someday are yet unconnected

http://www.forbes.com/sites/quora/2013/01/07/how-many-things-are-currently-connected-to-the-internet-of-things-iot/

26

3.Engagement Decisions are getting more complex

Mass Media

Web

Mobile

Social

Store

Purchase

► Explosion in touch points

► Information is dynamic

► Information is unstructured

► Information is “contextual”

Weather Patterns Economic Patterns Demographic Patterns

External Factors

A seller needs to understand both the internal and external context of a

customer at a transactional level

27

Key Takeaways from the Discussion

• There is an urgent need for building service capabilities

• Customer data is voluminous and fragmented across service logs, blogs, social media

• Systems have to put in place which is able to integrate data across these channels and extract meaningful insights from them

• Key to success is to be able to use these insights in providing customers with personalized services in a form which is most convenient to the customer

What is Cognitive Computing?

29

A simplified view of Cognitive Computing

Big Data – Provide Nuggets of information where humans need to “connect the dots”

Cognitive Computing–Era where machines will begin “connecting the dots”

30

Gaps in current Computing Methodologies

Supervised Learning

• Current computing can only predict/prescribe what it has been taught

• Is severely restrictive in most situations requiring simplifying rules

Structured Data

• Focused on structured data which is just 20% of the data available in organizations

• Cannot handle unstructured data without heavy simplifications

Machine ‘like’ Intelligence

• Human intelligence requires the thinking and understanding of process and problems in a certain way which machines today can’t [cognitive dissonance]

31

Cognitive Computing is responding to these challenges

http://blog.stephenwolfram.com/2011/01/jeopardy-ibm-and-wolframalpha/

Goal is the same:• How do you minimize “cognitive dissonance”?i.e how do you develop a system which is able to understand a problem in the same way as humans

Cog.nih.tiv (n). Having the property of reasoning, deduction, induction, and an awareness of immediate as well as latent cause and effect

32

High Level Watson Architecture*

1. Query or topic is posed to Watson

2. Watson parses the query

3. Multiple hypothesis are generated based on 2

4. On each of the hypothesis competing models are run

5. Results are synthesized using advanced scoring methodology

6. Final ranking to possible answers along with confidence levels are provided

11 22

33 44

55 66

Watson Relies on:• Evidence and prior results (answers) on the topic/industry which has been fed to it aforehand

• DeepQA architecture which enables massive parallelization of hypothesis testing and scoring from the content

Source: http://researcher.watson.ibm.com/researcher/view_group_subpage.php?id=2159

High Level Architecture of DeepQA

Why is Cognitive Computing critical to Service Differentiation?

34

Friends’ social posts are more influential in determining purchasing choices than direct retailer communications

Source: IBM IBV 2013 survey, n= 30,554. Q40 decision influencers

Influencers of purchase behavior

59%

57%

52%

51%

44%

41%

Friends post/pins about items purchased

Friends post/pins about retailers shopped

Retailers emailed sales announcements

Retailers sales announcements via social

Retailers recommendations on own website

Retailers recommendation on social sites

Chart shows percent of shoppers finding the communication “somewhat” or “very influential'

Data is available but fragmented. Suppliers need capability to intervene

with relevant information at the right time on the right channel

35

Half of consumers are neutral about SoLoMo* initiatives and are still waiting for a reason to engage with retailers

Retailers using current location (GPS)

negative neutral positive

28 49 23

23 51 26

22 50 28

20 50 30

17 52 31Associates able to pull up my browsing history

Retailers texting me

Retailers analyzing my posts to recommend new items

Retailers contacting me via social networks

Source: IBM IBV 2013 survey, n= 30,554. Q31 InfoShare *SoLoMo = Social Location Mobile

Interest in SoLoMo

Providers need to pinpoint customer needs on a real-time basis to be

valued to a customer

36

How is Cognitive Computing relevant to service differentiation?

Biggest barrier to enriching customer experience is fragmented data outside and within the organization. Cognitive Computing would help by data integration and providing insights when and where its required

Business users and algorithms often speak in different terms. Cognitive algorithms would be able to understand and help users design processes faster and closer to consumer requirements

Existing models for analytics would be able to use attributes from unstructured data and that would improve the model accuracies

Where is Cognitive Computing being applied today?

38

Branches of Cognitive Computing

Provide expert domain expertise to human user

Make evidence based contextual decisions autonomously

Discovers new patterns which is currently not detectable by humans

Decision

DiscoveryEngagement

22

11 33

Source: Your cognitive future, How next-gen computing changes the way we live and work, IBV WP

Final Goal is to provide computers with the ability to make own decisions

and discover new patterns

39

FutureFutureFutureFuturePresentPresentPresentPresentPastPastPastPast

True Q&A

Systems

e.g. Watson Engagement

Advisor

e.g. ELIZA

Vertical

Specific True Q&A Systems

Pseudo Dialogue

Programs

FAQ Assistants

e.g. NextITAlme

Source: IBM, Institute of Business Value, Evolution of cognitive: Where we’ve been and where we’re going

Significant progress has already been made in the “Engagement” capability

40

Assisting users retrieve insights through Q&A

Watson Explorer

ExploreAnalyzeInterpret

Customer support R&D Marketing & SalesCorporateGovernance

Security

� Secure access to internal and external information

� 360-degree information applications

� Advanced NLP and content mining

� Cognitive services

Advantages of Explorer over conventional searches• Contextual search – results dependent on user needs• Allows search in natural language• Allows real-time insights into unstructured data feeds

Implementation of Watson Explorer (WEX) Enterprise Edition

41

Allowing for knowledge which is available at users fingertips will transform the customer experience

Watson Explorer 360-degree information

application

Personality Insights service provides the user with a more detailed profile of the client

Data from enterprise systems such as CRM, DBMS, CMS and SCM

Analytics, in context

Activity feed for up-to-the-moment information

Data-driven alerts

Content analytics to reveal insights from unstructured data

Collaboration and information sharing

Source:Implementation of Watson Explorer (WEX) Enterprise Edition

42

Enrich existing Advanced Analytics Models by allowing scientists to tap into real-time unstructured data sources (1/2)

Trend + Seasonality + Employee but, sometimes a miss Forces may be in play

?

Can we spot the residuals and, determine causation Trend + Seasonal + State Space

?

Consider an example of forecasting which traditionally relies on time series data.....

Explorer can help us detect and evaluate attributes from unstructured sources which can help predict patterns at an individual SKU level

Source: Implementation of Watson Explorer (WEX) Enterprise Edition

43

Enrich existing Advanced Analytics Models by allowing scientists to tap into real-time unstructured data sources (2/2)

Unstructured

Extract and structure relevant context from unformatted

sources. i.e. PDF, newspapers

Streaming

External DataSources gathered across multiple platforms that

simulate and forecast local conditions.

i.e. Eventful, NOAA, Census

Real-Time MonitoringAbility to react to forces

instantly creating additional flexibility.

Structured

Structured

Internal Data

TransactionsStore profilesAdvertising

Social

Social Media (GNIP, Board Reader)

National NewspapersLocal NewspapersWeather Blogs

Source:Computing & Analytics for a Retail Supply Chain

How is Cognitive Computing likely to be consumed in future?

45

Watson Development Cloud is putting the capabilities of cognitive computing in the public space

A collection of REST API’s and SDK’s which allow developers to build apps which rely on cognitive computing

These Apps will allow for easier integration of Cognitive Capabilities

into current industry solutions

46

Summary

• Product differentiation likely to reduce with several disruptive technologies arising

• Service will be the new battlefield in an increasing number of electronics sub-industries

• A key challenge in service differentiation will be the ability to ingest and develop insights from a multitude of customer data

• Cognitive computing will help organizations tap into unstructured data

• There are 3 main branches of cognitive computing (engagement, discover, decision)

• Engagement is the most mature of the 3 branches with several use cases

• With the announcement of Watson development cloud, the costs of development is likely to come down significantly while helping adoption

47

Thank You

48

Citations

• Robotics icon- Created by AhaSoft from Noun Project• 3D Printing icon - Created by iconsmind from Noun Project• Analytics icon - Created by Ollie Taylor from Noun Project• Internet icon - Created by Shelten Davis from Noun Project• Opensource icon – Created by Bjorn Andersson from Noun Project• Dog icon – Created by Norman Ying from Noun Project• Book icon - Created by Jon Testa from Noun Project• Brain icon – Created by Marcus Micheals from Noun Project• Weather icon – Created by Mateo Zlatar from Noun Project• Economics icon – Created by Juan Pablo Bravo from Noun Project• Family icon – Created by Luis Prado from Noun Project• TV icon – Created by Mike Ashley from Noun Project• Web icon – Created by Martin Vanco from Noun Project• Mobile icon – Created by Hhari Davodpour from Noun Project• Store icon – Created by Edward Boatman from Noun Project• Network icon – Created by Gilbert Bages from Noun Project• Cart icon – Created by Hello Marry from Noun Project• Data Pic - https://commons.wikimedia.org/wiki/File:DARPA_Big_Data.jpg• Social Media Pic:

https://commons.wikimedia.org/wiki/File:Social_networking_services.jpg• Internet of Things Pic:

https://commons.wikimedia.org/wiki/File:Internet_de_las_Cosas.jpg