The document discusses the role of CIOs and big data collaboration. It notes that big data is growing exponentially, with 2.5 quintillion bytes of data created every day from a variety of sources. Big data offers significant value if organizations can analyze it, with potential savings in healthcare, retail, and other sectors. However, big data requires collaboration both internally within organizations and externally with partners. The document provides examples of successful big data collaborations and argues that CIOs will continue playing an important role in facilitating information management and digital transformation through big data initiatives.

1. The CIO &
Big Data
Collaboration
Bill Limond
www.limond.com
bill@limond.com

2. The CIO &
Big Data
Collaboration
Bill Limond
Executive Leaders Network
12th November 2015
www.limond.com
bill@limond.com

3. London Eye
Olympic Twitter Mood Meter

4. London 2012
London Eye Olympic Mood
Meter - How?

5. Will CIOs disappear ?

6. CIO Today
The ‘Perfect Storm’
• Mobile
• Broad-band
• ‘Consumerisation’
• BYOD
• Social Media
• Cloud
• IoT
• Digital Disruption/Revolution
• Big Data

7. Or was it BYODinosaur?
Will CIOs disappear ?

8. Big Data?
• Every day create 2.5 quintillion bytes*
• 90% data today created last 2 years*
• Data from everywhere : -
• sensors gathering climate information,
• social media sites,
• digital pictures/videos,
• purchase transaction records, and
• cell phone GPS signals to name a few.
• *IBM This is Big Data.

9. Big Data— a growing torrent
 $600 - disk drive store all world’s music
 5 billion - mobile phones
 30 billion - pieces shared on Facebook every month
 40% - global data growth pa
 5% - global IT spend growth pa
 235 - terabytes - US Library of Congress
 15 of 17 - sectors more data stored
 per company than Library of Congress

10. V Big Data
Big Data =
vast data
too large and complex for
conventional processing?

11. V Big Data
6 Vs:
• Volume - Terabytes to Petabytes, Exabytes & Zettabytes
(petabyte = 500 bn pages printed text)
• Velocity - Near real time sub second delivery
• Variety - Both structured & unstructured data
• Volatility - 100s new online data sources –
new apps, web services & social networks
• Veracity - 1 in 3 business leaders don’t trust the information.
• Value - Opportunity – new competitive insights &
operating models & products based on customer insight & intelligence.
 Big data: The next frontier for innovation, competition, and productivity McKinsey Global Institute

12. Data
capturing Potential Value
 $300 billion pa - US health care— > 2x Spain’s health
care spend pa
 €250 billion pa- Euro public sector admin > Greece GDP
 $600 billion - personal location
data
 +60% - retailer operating margins
 +190,000 - Analysts
 +1.5 million - data-savvy
managers (US)
Big data: The next frontier for innovation, competition, and productivity McKinsey Global Institute

13. • €250 billion value per year
• 0.5 percent annual productivity growth
McKinsey Global Institute analysis
Big data can generate big value …
Europe public sector administration

14. Big data can generate big value…
US Health Care
• $300 billion value per year
• 0.7 percent annual productivity growth
McKinsey Global Institute analysis

15. Big data can generate big value…
Manufacturing
• Up to 50 percent decrease in product development,
assembly costs
• Up to 7 percent reduction in working capital
McKinsey Global Institute analysis

16. Big data can generate big value …
US Retail
• 60+% increase in net margin possible
• 0.5–1.0 percent annual productivity growth
McKinsey Global Institute analysis

17. • $100 billion+ revenue for service providers
• Up to $700 billion value to end users
McKinsey Global Institute analysis
Big data can generate big value …
Global personal location data

18. How to Benefit from Big Data
Multiple Data Sources - Collaborate
 Creatively source Internal and External Data
 Upgrade IT for easy Data Merging
Prediction and Optimisation Models
 Focus on biggest Performance Drivers
 Balance Complexity and Ease of Use
Transform Company Capabilities
 Develop Useable Business-relevant Analytics
 Embed Analytics into Simple Tools for Front Lines
 Update Processes and Develop Capabilities to Exploit
Big Data

19. Personal Big Data Collaboration

20. Big Data Collaboration
 Open Data
 External
 Internal
 “With Big Data the sum is more valuable than its parts,
and when we recombine the sums of multiple datasets
together, that sum too is worth more than its individual
ingredients” (Mayer-Schonberger & Cukier – Big Data).
 Countless tools…but technology is only part of it- it must
be embedded in organisational culture.
Photo: Andy

21. Collaboration – Open Data
TfL ‘Countdown’
Photo: Clive A Brown
Photo: Nico Hogg
Photo:James Darling

22. Open Data Potential Value (US$Bn)

23. Matt Hancock - Minister Cabinet Office
data.gov.uk - Open to Usable
 Published > 20k datasets = £200Bn Public
Spend
 Performance Metrics for All 800
Citizen/Government Transactions
 UK - 1st Global Open Data Index & top
WWW Foundation Barometer
 Defra published LiDAR elevation data:-
 Apps - e.g. flood defences, precision farming,
archaeology, urban planning, Minecraft
 Land Registry released Price Paid Dataset:-
 Apps – RightMove, Zoopla, Develop Valuation
SW, Improve Planning Policy, Market Trends,
Academic Research.
Photo: Derfelphotogen

24. Matt Hancock - Minister Cabinet Office
Next Steps
 Modernise Data Infrastructure: –
 Data Standards & Maintenance
 ‘Dog-fooding’ – eat your own.
 Build Capability across Civil Service
 Put Trust at Heart of Process - CIA
 Collaborative approach to Data Policy & Governance:-
 Data at Heart of Open Government Partnership Action Plan
 UK Lead Steward for International Open Data Charter
 Whitehall Data Leaders Network
 Data Driven Government wants to engage UK’s Data Economy
 Connect with Businesses, Start-ups & Innovators leading across
Data Spectrum
 Network & Interlink currently dispersed and decentralised
Knowledge & Expertise.
Photo: Wesley & Dannells

25. Kaggle
Kaggle data scientists helped automatically
diagnose schizophrenia subjects from MRI
scans in MLSP's research competition ›
GE utilized multiple sources of flight and
weather data to improve runway arrival
time prediction, saving airlines millions of
dollars.
platform for predictive modelling
and analytics competitions on
which companies and researchers
post their data and statisticians
and data miners from all over the
world compete to produce the
best models.

26. Kaggle
Some Customers
Heritage Provider NetworkImproved revenue for hospital network through patient admissions.
Broader recognition of gestures for Xbox Kinect
Earlier detection of driver drowsiness
Better predictability for drug targets.
Better and broader identification of talent
Increase effectiveness of click through rates
Retailer
($10B+ revenue)
Optimized decision for store location
Better and broader identification of talent
Earlier and more accurate detection of seizures in patients with epilepsy.
More accurate airline departure and arrival times; improved hospital
operations.
Improved estimate of customer claims costs; Reduced customer churn.
More accurate imaging of dark matter.
Improved lifetime customer value.
Better predictability for drug targets.
Beverage Co.
($10B+ revenue)
Improved sales and demand forecasting
Oil & Gas Co.
($100B+ revenue)
Improved prediction of oil reserves
Regional Bank in
Northeast
Improved risk profile by identifying financial distress

27. External Big Data Collaboration
‘Big Pharma’ - 3 Different Models
• Project Data Sphere (PDS)
 Objective – accelerate drug discovery & development
 Companies share clinical trial data for Cancer Research:-
o Astra Zeneca, Bayer, Celgene, Janssen (J&J),Pfizer, Sloan
Kettering, Sanofi; National Cancer Inst., Amgen, Quintiles
 EU Legislative Model
 EMA establish publicly accessible clinical trials register -
Targets clinical trial data transparency
 Strict conditions & penalties
 Genentech & PatientsLikeMe - 5 Year Commercial Agreement
 Patients provide their Data during current treatment
 Wide range of conditions, but Cancer lead
Photo: Ynse
Photo: Go2net Vaughn

28. ‘Big Pharma’ 2015 Bio-IT World Conference
3 Big Data Collaboration Tips
Ruthlessly Select ALL Collaboration Partners
 Polygamous
 External and Business Partners & Suppliers
 Multi-cloud solutions becoming popular
Take Coding out of Collaboration
 Flexibility v Standardisation
 Standardised, cloud-based GUI platform
BUT Get Own ‘Big Data’ House in Order
 Internal & External
 Especially Information Security, IAM
Photo: Adam
Photo: Ray Morris

29. Internal Big Data Collaboration
UK Government
Potential Rewards
 Policy makers – think differently & enhance service provision
 Public access ever-increasing, more easily ‘digestible information
aids informed decision making
BIS – Business Innovation & Skills
 Building Data Science capability – interdisciplinary collaboration
 Innovative interactive visualisation UN trade data for Global audience
DWP – Dept. Work & Pensions – Universal Credit Data
 Increase effectiveness of departmental operations
 Jobcentre Plus & other organisations e.g. Housing Associations
understand claimant caseload by location
 Public has UC roll-out timetable by locality
Data Science Competition
 Supported by Government Data Science Partnership (Cabinet Office,
GDS, Go-Science & ONS)
 Using Big Data techniques & SW to answer business questions,
visualise information across wide range of depts.

30. Internal Collaboration
Data driven companies
(McAfee & Brynjolfsson – HBR)
 McKinsey/MIT HBR study 330 N American Companies
 Data Driven Companies better performers than Competitors:
 5% more productive
 6% more profitable
 Reflected in Stock Market Valuations
 Better predictions, surprising sources:-
 Wharton Big Data House Market Prices better than National Association of Realtors
 John Hopkins used Google Flu Trends to predict surges week before Centre for
Disease Control
 Twitter updated & tracked Haiti Cholera spread 2 weeks ahead of Official Reports
 Passur Aerospace – RightETA virtually eliminated gaps between Airline Estimated and
Actual Arrival Times. “Worth $ Millions”
 Sears – Big Data Technologies & Practices (Hadoop clusters) – directly analysed cluster
data. Promotion lead times dropped from 8 weeks to 1 week & still dropping.

31. Internal
Collaboration
 Companies have applied Big Data and analytics capabilities to
sales and marketing data to better understand and engage their
customers, but scant few have directed these types of
technologies ‘inward’ to improve their own organizations.
 Collaboration data can reveal how an organization’s biggest
assets – its people – are working together and what the
organization is really focused on.
 In a Collaboration centric culture, data sharing helps build bridges
and collapse silos to develop competitive advantage
 Today collaboration data is likely the most valuable untapped
data source in the enterprise
http://www.digitalistmag.com/technologies/big-data/leveraging-big-data-
redefine-collaboration-enterprise-01243242
Photo: JP Goguen

32. Collaboration & Security
• Collaboration & Sharing may pose new risks
• Opportunity to advocate & enable secure collaboration in high-risk
environments
• Take both data- & identity-centric approach to controlling information
in collaboration environments
• 4 main steps:-
1. ‘Turn Big into Small Data’ means System keeps up to enable faster, more
accurate & business-relevant decisions
2. Determine Information context; Who communicating How. Leads to better, fine-
tuned decisions.
3. Deploy controls to securely enable on-premise email & collaboration. Then
determine how & where to deploy data controls
4. Deploy controls to securely enable cloud and mobile collaboration. Manage
areas of High Risk
• Instead of security of “No”. Empower security of “Know”
(Tyson Whitten – CA)
Photo: Paulo Valdivieso

33. CIO Role
• Lead
• Business Solutions
• Business Knowledge
• Information
• Governance
• Strategy
• Deliver – Results
• Value for Money
• Informed Purchaser

34. CIO Mission
CIO is Custodian of KEY INFORMATION & DATA ASSETS of
organisation, responsible for Governance, Management &
Security; just as CFO is responsible for financial assets.
CIO mission is to facilitate & improve, cost effectively:-
o ‘Digital Engagement’ with Customers, Clients, Citizens &
Stakeholders
o Secure management & communication of Information &
Data
o Streamlining of business processes
o Sharing of Knowledge, across the organization.
As Peter Drucker said: as Knowledge Workers, All we have to
manage is INFORMATION.

35. Business
Strategy
Direction
Capabilities
CHANGE
IM
Strategy
Possibilities
Business and IM Strategy
INNOVATION
INNOVATIONCHANGE &CIO= ORIGINATOR

36. Value/Knowledge
IT
IS
Knowledge
Sharing
IT
Service
Business
Strategy
IT IS IM & BP Knowledge Sharing
Knowledge
Data
Information
IM
& BP
IM Value Chain

37. • Understand the Business
• Be the Business
• Hybrid
• Exploit ICT
• Bridge the GAPS
CIO or DIM?

38. 1. Let users pull - don't push I.T. (too much)
2. It's easy for the organisation to tie
itself in I.T. knots
3. Harness the potential
4. Keep your balance
5. Avoid the lynching party
CIO Rope Tricks

39. CIOs will disappear ?
• Career Is Over?
• When IT standard, organisations will no longer
need CIOs?
• Information ASSET
• Change & Innovation Originators
• Organisations still need CIOs

40. “In the End
All that we have to manage is -
Information.”
Big Data?

41. Thank You
Bill Limond
Executive Leaders Network
12th November 2015
www.limond.com
bill@limond.com

42. The CIO &
Big Data
Collaboration
Back-up Slides