1. What business really needs

2. Principles behind our conversation
Approach
Strategic
Operational
Operating efficiency
Driving shareholder value
Revenue growth
Why do businesses need data?
Practically how could data collaboration impact current business process?
Capital efficiency
Responding to regulation and risk
Risk & Expectations

3. Global market dynamics are causing mass disruption across industries
Business is hard pressed to disrupt or be disrupted
Global market dynamics
A new breed of opportunity, a new breed of competitor
Threats from innovative alternate products
A new breed of customer – empowered, informed, engaged
The blend between product, service and insight
Global regulatory pressure in response to Financial Crime, Anti-terrorist threats and Anti-money laundering

4. Observed business investment in global megatrends
Preparation for tomorrow’s market – a blur between product, service and insight
Global market dynamics
Observed megatrends
Disaggregating forces – the pervasive use of digital connectivity to coordinate and mobilise large volumes of consumers to fundamentally disrupt traditional services
A new level of personalisation comes to retail products, breaking the grip of stagnant, standardised products and experiences.
Next generation of process externalisation – the API economy
The embedding of artificial intelligence, machine learning, social sentiment into customer touchpoints, and back-office operations and processes
Automated advice management, consumer engagement and social trading

5. Data is becoming a vital differentiator
Data is the new oil
Data is becoming a vital differentiator
Global market dynamics
Observed megatrends
Enhanced information about customer
Enhanced information about market
Businesses that can augment their products and services with insights are likely to succeed in the future market.
Collaboration around data between Private and Public sector provides an opportunity to enable our economy to be more competitive.
Enhanced information about competitive landscape
Enhanced information about risk

6. Some pragmatic opportunities to collaborate
Focusing on shareholder value
Streamline customer on boarding – ask fewer questions, allow data to fill in the blanks
Operating efficiency
Enhanced data quality – all businesses are grappling with inconsistencies in data
Revenue growth
Practically how could data collaboration impact current business process?
Capital efficiency
Risk & Expectations

7. Some pragmatic opportunities to collaborate
Focusing on shareholder value
Hyper tailored customer experience - embed information and intelligence into customer experience
Operating efficiency
Hyper personalised product offerings
Revenue growth
Practically how could data collaboration impact current business process?
Improved market research for the identification of new market opportunities
Capital efficiency
Development of new innovative products and services by leveraging shared data
Risk & Expectations

8. Some pragmatic opportunities to collaborate
Focusing on shareholder value
Operating efficiency
Deduplication of financial crime, anti-terrorist and anti-money laundering processes
Collaboration between government, regulatory bodies and business to better manage SA’s risk
Revenue growth
Practically how could data collaboration impact current business process?
Capital efficiency
Risk & Expectations

9. Identified business challenges
Wait what about the obstacles?
Challenges to opening up are not technical, they are cultural.
The principal concern among business is that giving away data gives away value and provides advantage to sharp-eyed competitors.
Businesses feel overwhelmed by their own data, and the processes for managing and leveraging data.
They feel that to share they first need to get their “own house in order”
Business say they are not in the information business, but they know they have loads of data and to participate in the data economy will require too much effort and resources
Opening or selling data will create too much of an administrative & regulatory burden and endanger customer loyalty.
SLIDE KEY INSIGHTS:
Challenge perceptions and culture. Not exploring this will be detrimental to businesses in the future.

10. What could it look like – the data exchange
Models related to open data initiatives
Fully and unconditionally open data
Data that is open for consumption but with limitations for reuse
A combination of open data and high-quality, low- cost data sources
Publicly available data as part of the business model
No legal obligations to producer
Attribution
Freemium use
Syndicated licence
Commercial terms and conditions
SLIDE KEY INSIGHTS:
Open data in its raw form holds little value, elaboration of this data, through augmentation and advanced analytics can be powerful
Demos:

11. Practical example – Panama papers
Leveraging Open Data
Using Panama (off-shore leak data) and corporate registries to identify financial crime activities
SLIDE KEY INSIGHTS:
Open data in its raw form holds little value, elaboration of this data, through augmentation and advanced analytics can be powerful
Demos:

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