Cloud Computing and Big Data for Service Innovations & Learning Up till now, most of the adoption of cloud computing focusses on the automation and consolidation of traditional IT services. As such, the gains are confined to the uniformity of control, cost reduction and better governance. Recent adoption of the cloud has gradually moved into tactical and even strategic levels thereby demonstrating a high level of gains for using the cloud for business transformations and innovations. Such benefits include dynamism in business model compositions and speed and ease in orchestrating service innovations in the cloud. This talk will shed light on how massive and rapid accumulation of data in the cloud can support human-machine cooperative problem solving and re-define the landscape of Open Innovation and Connectionist Learning via a Knowledge Cloud.

1. Cloud Computing & Big Data for Service Innovation & Learning
Professor Eric Tsui
Knowledge Management & Innovation Research Centre
The Hong Kong Polytechnic University

2. Services as % of GDP in OECD countries

3. • Co-creation of value
• Dynamic Capabilities
• Enabling Vs Disruptive
• Open Business Models
• Customer Experience => Efficiency, Integration & Transformation
Some key concepts in Service Innovation
Professor Ian Miles, MBS
Professor Eng Chew, UTS

4. Customers to co-design in a process – DELL Computers & Taggerbags

5. Definition of Cloud Computing

6. 1.On-demand & self- service
2.Broad network access
3.Resource pooling (location independent)
4.Rapid elasticity
5.Agility
6.Measured service (& mostly postpay)
Characteristics of the Cloud

7. Fulfillment By Amazon (FBA) (Replay video at http://amazingsellingmachine.com/how-to-scale/)

8. SAP’s “The SUPPLY UNCHAINED Cloud”?

9. Microsoft’s Azure cloud helps winning the Formula 1 race?

10. A cloud connects computers, data and people at a massive scale

11. A cloud connects computers, data and people at a massive scale

12. 1.Machine to Machine
2.People to Machine
3.People to People
Three types of connections in a cloud

13. 70 billions connections & 1/3 of consumer digital content in the cloud by 2020 & 2016 respectively
In July 2012, there were 955m users in Facebook
In 2012, about 2.5 exabytes are created every day and is expected to double every 40 months. An exabyte is 10,000 times of a petabyte (approx 20 million filing cabinets)

14. The Knowledge Cloud

15. Think Outside The Box
The Cloud as some massively scaleable backend resources with low upfront costs
Intelligent Knowledge Centre with massive data, problem solving skills (processors & humans), & dynamic computational power
The Cloud is Disruptive

16. Human-machine cooperative problem solving

17. •Polymath
oOnline discussions about mathematical problems
•GenBank
oWorld’s online repository of genetic data
•GalaxyZoo
o200,000 online volunteers to help astronomers classify galaxy images
Harnessing Wisdom of the Crowd

18. Any spiral? Which direction?

19. Amazon Mechanical Turk

21. Recaptcha (Human-assisted inexact matching)

22. Replay Webinar at http://webvideo.polyu.edu.hk/p99237461/

23. CDC detection of an epidemic outbreak
Airline ticket prices
Orange car is least defective
Mail to teenager promoting maternity products
Amazon's recommendation engine
Match-fixing in Sumo wrestling
Social Network Analysis for Vulnerability
UPS Fleet Maintenance
ReCaptchas
Google translation
Re-discovery of the English language
Health & Credit check (by banks & insurers)
Big Data applications & cases

24. •Speed of making decision more important that causal reasoning (Knowing “WHAT” first; knowing “WHY” later)
•Trade "exactness" for "approximate" to support fast decision making
•To improve the performance of your algorithm, try feeding it with lots more data (instead of modifying the program)
Re-wiring our brain (impact of Big Data & IoT)

25. HKPolyUX MOOC on KM & Big Data (to be launched in Aug 2015)