Conference Day One: Tuesday, 26 September 2017

8:00 AM - 8:30 AM Coffee & Registration

8:30 AM - 9:00 AM Opening Remarks from Conference Chairperson


Top 5 to Discuss and Solve:
  • Assessing the options: How do you select the right application of AI for your business strategy?
  • Strategic workforce planning: How will machine learning and artificial intelligence change the job landscape?
  • How can you become agile to ensure ease of transition and implementation of technology to keep up with advances and developments?
  • What impact has AI already had on Financial Services, Marketing/Advertising, Law and Healthcare
  • How can you use AI to remain one step ahead of the competition?


Dan Taylor

General Manager, Innovation
Tal Group

Andrew Lim

Head of Data

Gavin Artz

Business Development Manager, Technology and Creative Industries
Investment Attraction South Australia

9:40 AM - 10:20 AM International Keynote: Accelerating Machine Learning and Steering Strategy Within Your Organisation

Dr Andy Pardoe, REF Global Development Manager, Credit Suisse
Dr Andy Pardoe has been listed by IBM Watson as one of the top 30 AI influencers globally. He has a PhD in AI, specifically neural networks.

Credit Suisse has developed sophisticated machine learning capabilities and is ramping up its adoption across the organisation. Its internal ML working group is set up to accelerate adoption across the firm, steer strategy and help teams that want to use ML but don’t have the expertise. ML has gone exponential, with the firm running a large number of proof of concepts to get them into production systems.

Key Question: How do you accelerate the adoption, while improving the quality and accuracy of ML in your organisation?
Focus: Machine Learning, accelerating adoption, expert working group, steering strategy
Biggest Hurdle Overcome:

Dr Andy Pardoe

REF Global Development Manager
Credit Suisse

10:20 AM - 10:50 AM Solution Provider - Edgeverve

10:50 AM - 11:10 AM Speed Networking

11:10 AM - 11:30 AM Morning Tea

11:30 AM - 12:00 PM How To: Create the conditions for AI success: TAL’s Incubator

Dan Taylor, General Manager, Innovation, Tal Group
TAL has established an incubator focused on leveraging AI and data, but also more broadly, emerging technology. They have ensured that rather than just securing the right talent, they have provided the right environment for that talent to flourish and innovate in a sustainable way, and a number of pilot projects are now being implemented as a result.

Key Question: How do you focus your AI program to deliver early results, while also creating the roadmap and environment for long-term success?
Focus: Incubator, pilot projects, talent acquisition, culture, successful environment, understanding how AI projects work, scoping projects, roadmapping projects
Biggest Hurdle Overcome: Establishing a sustainable model to apply data science and showing tangible results/impact


Dan Taylor

General Manager, Innovation
Tal Group

12:00 PM - 12:30 PM How To: Leverage Analytics and AI Applications to Improve Efficiency and Standardisation

Heike Magura, Director Performance & Analytics, Mater Health Services
Mater Health deals with a huge amount of data on a daily basis. It is \lLeveraging this valuable but dispersed dataset to create AI applications to gain a single view of the customer and visualise the patient journey and resource utilisation to improve efficiency and service. For the past 12 months, it has been linking all data sets and reducing the isolation of information to inform effective resource allocation and standardise operations and care in an application called A&P Insight.

Key Question: How do you leverage analytics and AI applications to standardise operations and improve customer service?
Focus: Big data, predictive analytics, data modelling, standardisation, resource allocation, efficiency, customer journeys
Results to Date:
· Reduction in length of stay by half a day
· Significant improvement in discharge time and less weekend stays
· Allowing Quality and safety metrics to be linked to patient demographics, procedure codes and nurse hours
· Automation of often labour intensive reporting e.g. Patient Call Bell App
Biggest Hurdle Overcome: Change Management - with staff used to being feed information in canned reports that it has taken a lot of convincing to move people to use self-serve analytics and to find the answers to their own questions.

Heike Magura

Director Performance & Analytics
Mater Health Services

12:30 PM - 1:00 PM How To: Use Predictive Capabilities to Improve Customer Service and Reduce Internal Effort

Davinia Gravesande, Director Analytics Data and Business Intelligence, Optus
Optus is focused on utilising data and data platforms to move toward a predictive customer service. In order to achieve this, they are focusing on understanding different information points for the customer including social media and unstructured data sets.

Key Question: How do we use AI/ML to understand and predict what service the customer wants before they speak with someone?
Focus: Better utilizing information, making sense of big data, chatbots, improving customer service, predictive analytics, legacy data platforms
Biggest Hurdle Overcome: Upgrading legacy data platforms and move toward an end state in tech roadmap

Davinia Gravesande

Director Analytics Data and Business Intelligence

1:00 PM - 2:00 PM Lunch

2:00 PM - 2:30 PM How To: Leverage Machine Learning and Predictive Analytics to Improve Operational Efficiency and Reduce Cost

Murray Adams, Manager Operations Analytics and Reporting, Qantas
Qantas’ operational consumption of fuel is the organisation’s biggest cost, at 25% of the organisation’s $3.2bil cost base a year, and $200,000 an hour. It also has vast amounts of data coming from aircraft operation, (15bil data points a year on one aircraft) and is using intelligent automation and machine learning to improve operational efficiency and reduce cost. It is also implementing AI and intelligent automation to boost customer service capabilities.

Key Question: How do you leverage analytics and AI to improve efficiency and reduce operational cost?
Focus: AI, intelligent automation, predictive analytics, machine learning, efficiency, cost reduction, mass data, customer service
Biggest Hurdle Overcome: Organising the massive amount of data

Murray Adams

Manager Operations Analytics and Reporting

2:30 PM - 3:00 PM How To: Ensure Quality of Data to Set the Foundation for AI

Alan Hsaio, Head of Data Strategy, ANZ
ANZ has made significant progress in engineering its data and data warehouse and developing customer oriented propositions to leverage that information. Data quality is a significant area for improvement, presenting a world of potential waiting to be tapped into. It’s reducing siloes between parallel worlds like the data warehouse to drive metrics and the document and workflow world, which currently have no real interaction with each other.

Key Question: How do you take existing data and make it useful for the customer, as well as developing a better relationship and more personal contact with them?
Focus: Marketing triggers, customer cohorts, using data to advise customers, next generation marketing, convergence of structured and unstructured data, eliminating siloes
Biggest Hurdle Overcome: Shifting the mindset to how they think things should be done, not how they have been done

Alan Hsaio

Head of Data Strategy

3:00 PM - 3:30 PM How To: Use Machine Learning and Advanced Analytics to Drive Growth and Reduce Cost

Siamak Tafavogh, Lead Data Scientist, Coca Cola Amatil
Coca-Cola Amatil began their advanced analytics initiative 1.5yrs ago, trying different cases with different departments to allow staff to realise its potential. They developed a framework of exactly how machine learning and advanced analytics works within the business, the cross functional technology element, and how the project needs to be delivered. 4 projects have been completed, 2 being purely machine learning and predictive modelling, enabling growth and cost reduction across the organisation.

Key Question: What should the structure be around machine learning?
Focus: Machine learning, advanced analytics, strategy marketing, customer cohorts
Biggest Hurdle Overcome:

Siamak Tafavogh

Lead Data Scientist
Coca Cola Amatil

3:30 PM - 4:00 PM Afternoon Tea

4:00 PM - 5:15 PM Interactive Discussion Groups

This is your chance to make your conference experience truly interactive and collaborative. Each IDG is set in a roundtable format and will be facilitated by an expert practitioner and thought leader in the space. In three rotations, each IDG will last for 40 minutes.

Sponsored by: The Eclair Group

4:00 PM - 5:15 PM Clean Data

Key Question: How do you clean the data you already have and identify/collect any missing pieces?
· Efficiently organise data to maximize ROI
· Combine all analytics forms: prescriptive, descriptive and predictive to create a cognitive solution
· Structuring the collection and utilisation of data
· Identify the most critical areas of focus for growth to ensure opportunities for data collection are utilised

4:00 PM - 5:15 PM Cloud Services

Key Question: How do you leverage Cloud and intelligent apps to deliver a quantum leap in customer service?
· The logistics of moving to the cloud platform
· Building on existing cloud infrastructure
· Understanding the potential ROI of intelligent apps
· Deciding if this direction is the best fit for your business

Department of Human Services (TBC)

4:00 PM - 5:15 PM Automating Tomorrow's Enterprise

Key Question:
How does tomorrow’s enterprise win leveraging automation as part of a continuous transformation?

  • Tomorrow’s enterprise is customer first and automation led
  • Adapting to highly disruptive markets demands the ability to continuously transform and evolve
  • How do you organise yourself and where do you begin?
  • Automation enabling the continuous transformation

Sponsored by: The Eclair Group

4:00 PM - 5:15 PM Internet of Things (IoT)

Key Question: How do you take advantage of IoT?
  • Using machine learning to analyse the deluge of performance data and information that all these devices create
  • Gathering the mass data from IoT: cleaning and feeding the right IoT data to your machines
  • Acting on the insight: ensuring you have the right insight to use to advise strategy

5:15 AM - 6:00 AM IDG Report Back

Each group facilitator will share the most crucial points arising from each discussion, including the challenges and solutions surrounding the particular topic.

6:00 PM - 6:30 PM Closing Remarks from Conference Chairperson

6:30 PM - 6:30 PM Networking Drinks