Copy of presentation delivered at the CHASS 2015 National Forum in Melbourne (October 2015), The Council for Humanities, Arts and Social Sciences in Australia is the peak body supporting more than 75 member organisations in their relationships with Federal and State Government policy makers, Academia and the broader community within Australia.

1. Thriving in the world of big data
Exploring the opportunities and challenges facing
organisations.
CHASS 2015 National Forum
ROB LIVINGSTONE
- Fellow, University of Technology, Sydney
- Principal, Rob Livingstone Advisory Pty Ltd
© All rights reserved. Rob Livingstone Advisory Pty Ltd.

2. Theme of this presentation
Big Data…..
• Easy to say
• Hard to do

3. Easy to say…..
• Analysts, vendors and the media are awash with impressive projected
(and actual reported) compound annual growth rates (CAGR) of
spending in Big Data.
• Despite these compelling numbers, the reality is that the majority of
organisations are still coming to terms with Big Data.
“ ….only 13% of organizations have achieved full-scale production for
their Big Data implementation.”*
“…..only 27% of respondents described their Big Data initiatives as
“successful” and only 8% described them as “very successful”. *
• These trends are also echoed elsewhere.
*Capgemini 2015 - ‘Cracking the Data Conundrum: How Successful Companies Make Big Data
Operational’
Hard to do……

4. Theme of this presentation
3 Fundamental issues:
• Business + Big Data = Big Value?
• Privacy + Big Data = Big Brother?
• Cybercrime + Big Data = Big Risk?

5. Big Data - a brief 3600
Key attributes
• Volume: Lots and lots of data – and growing exponentially.
• Velocity: Data is time-sensitive.
• Variety: Data in various forms, formats and from different sources.
• Validity: Interpreted data has a sound basis in logic or fact.
i.e. correct logical inferences.
• Veracity: Conformity to facts, data quality, accuracy.
• Value: Its importance, worth, or usefulness.

6. Big Data - a brief 3600
Other key considerations:
• Visibility: Assured accessibility.
2 sides of the same coin:
- Risk that critical data that is available but not visible – wrong decisions taken.
- Included data that should have been excluded – wrong decisions taken.
• Volatility: Managing change.
- How adaptable is the information architecture to change?
- How adaptable are your risk and governance processes in the face of change?
- Recognise that change can come from anywhere.

7. Other key considerations:
• Visibility: Assured accessibility.
2 sides of the same coin:
- Risk that critical data that is available but not visible.
- Included data that should have been excluded – wrong decisions taken
• Volatility: Managing change.
- How adaptable is the information architecture to change?
- How adaptable are your risk and governance processes in the face of change?
- Recognise that change can come from anywhere:
Big Data - a brief 3600

8. Big Data - a brief 3600
Other key considerations:
• Visibility: Assured accessibility.
2 sides of the same coin:
- Risk that critical data that is available but not visible.
- Included data that should have been excluded – wrong decisions taken
• Volatility: Managing change.
- How adaptable is the information architecture to change?
- How adaptable are your risk and governance processes in the face of change?
- Recognise that change can come from anywhere:
• Vendors – Understand your need and their value proposition.
- Eyes wide open!
- Evidence!

9. Big Data – Opportunities for organisations
• Depends on a range of factors such as: your industry,
market, compliance and regulatory mandates, business
strategy, risk profile / appetite.
• Opportunities can include:
Improved decision making (cognitive bias, accuracy,  timeliness, etc)
 Internal cost, waste and inefficiencies
 Time to take action
 Revenue (e.g.: Monetising data, new information based value-added
services or products, etc)
 Model and simulate business scenarios with increased accuracy and speed
(e.g. predictive analytics)

10. 1. Executive’s understanding:
– Consistency of understanding at Executive level. Enterprise Big Data initiates are
everyone’s job, not just IT or the vendor’s.
2. Scrutinise the business case carefully. Then repeat the process.
– Expose and validate underlying business assumptions carefully.
– If anyone says it’s easy, insist on a proof of concept then seek evidence
3. What’s worked over there, may not work here.
– Other organisation’s success in Big Data will not automatically translate to yours.
– Beware of the bias of perceived success: Organisations & vendors promote success
stories, however failed projects may never see the light of day.
Big Data – Challenges for organisations

11. Big Data – Challenges for organisations
4. Assess your internal IT capabilities:
• Industry research* also indicates that executives’ perceptions of enterprise IT’s
performance remains largely negative.
– "...confidence in IT’s ability to support growth and other business goals is waning...."
– "... Moreover, IT and business executives disagree strongly on the function’s overall
priorities...“
5. Got the technology strategy, architecture and operations sorted?
* Arandjelovic, P., Bulin, L. and Khan, N. [2015], ‘Why CIOs should be business-strategy partners’, McKinsey & Company
Internal? Hybrid? Outsource?

12. 6. Skills shortage in data science:
– Expertise needed to understand the statistics, mathematics, computer and
information science, operations research, etc. .
– Must also be skilled in working with new technologies, data interpretation and
visualisation as well as understand the business context.
7. IT architecture
– Getting the range of data sources and formats to play nicely together
– Ensuring security access control and identity management works!
8. Intra-organisational collaboration
– Data interpretation and finding meaningful business insights cannot, for the most part,
be done effectively within a functional silo.
– Collaboration depends on organisation’s culture, business model, incentive schemes
and structure.
Big Data – Challenges for organisations

13. 9. Rate of technological change:
– ‘Future-proofing’ is a challenge where underlying technologies have a short half-life.
– ‘Outsourcing’ or public cloud solutions abstracts this challenge.
10. Protecting your Intellectual Property
– Do you have any IP that needs protecting? Data analysis algorithms, schemas etc?
– Ensuring security access control and identity management controls are secure.
11. Intra-organisational collaboration
– Data interpretation and finding meaningful business insights cannot effectively be
done within a functional silo.
12. Cybercrime / IT Security
– Unfortunately data breaches are almost routine.
– Cybercrime – State sponsored or ‘free market’ is a well resourced, highly skilled and
innovative threat.
Big Data – Challenges for organisations

14. • Big Data is all about extracting valuable insights from large volumes
of diverse data – like mining for diamonds – and then taking
appropriate action.
• Can be a game changer if your organisation gets it right.
• Be prepared, however to make some changes along the way, such as:
– Become a collaborative organisation – redesign jobs, processes, structures.
– Build a strong analytics capability internally.
– Adjust incentive schemes to successful outcomes
– Don’t assume ‘big-bang’ projects will succeed. Adopt lean startup principles to
your Big Data initiatives.
• Expect change and ensure you have effective governance in place.
Big Data – In summary

15. Thank you
W: www.rob-livingstone.com
E: rob@rob-livingstone.com
P: +61 2 8005 1972
M: +61 419 632 673
F: +61 2 9879 5004
Tw: @rladvisory
ROB LIVINGSTONE
- Fellow, University of Technology, Sydney
- Principal, Rob Livingstone Advisory Pty Ltd
© All rights reserved. Rob Livingstone Advisory Pty Ltd.