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EXCLUSIVE: OpenGov Breakfast Insight: Data Monetisation – Transforming Big Data into Big Value

Delegates at the OpenGov Breakfast Insight: Data Monetisation - Transforming Big Data into Big Value

OpenGov’s Breakfast Insight on Wednesday, 17 July 2019 was an intense discussion on Data Monetisation. The insight session focused on financial services and insurance companies gathered together to have an exchange of knowledge on the ways data can be utilised to produce revenue.

Monetisation of data or a modern-day Rumpelstiltskin

Making a reference to the classic Grimm Brothers’ fairy tale, Rumpelstiltskin, Mohit Sagar, Group Managing Director and Editor in Chief at OpenGov Asia, opened the session and delved into how data can be spun into gold. He listed the different ways in which innovative businesses are making use of their data to produce revenue for them.

Mohit Sagar: You can spin data into gold

Mohit talked about how data can be used to generate predictive analysis. Analysis of purchasing data will allow businesses to identify trends and better predict consumer behaviour. They will be better able to personalise their marketing campaigns towards the right target group.

Connecting data and breaking down silos will enable businesses to develop a ‘single customer view’. This will aid them in eliminating errors and developing an accurate view of a customer based on his/her connections

He went on to talk about how it is important to add context to data. Locations and sources of data generate opportunities for businesses to reach the customers they seek, to build loyalty and drive engagement.

He shared on how data is a tool for enhancing customer lifetime value. Data can be employed for futureproofing, safeguarding business, identifying trends, predicting behaviours, measuring the customer experience, and generating hyper-personalised customer engagement strategies.

He concluded with how businesses should use APIs. He talked about how studies show that the use of APIs drove revenue for businesses.

Consolidate, Connect and Accelerate

Financial Service Institutions are constantly upgrading their services and digitalising to make themselves more efficient and to be better able to assist their customers.

Sunil Chavan believes digitalisation makes companies agile, real-time and fast

Sunil Chavan, Vice President of FlashBlade sales at Pure Storage, painted the picture as to how digitalisation is helping financial services in the areas of investing and wealth management, retail banking and insurance.

He shared of how digitalisation in these areas allow for financial businesses to enjoy agile compliance, real-time customer insights and to accelerate underwriting in these sectors respectively.

He proposed that financial services should ensure data consolidation, data correlation and data acceleration to improve productivity and to produce results.

Sunil shared two case studies on the implementation of digital innovations among financial services.

Oil or data – the more valuable resource

Raynor felt that data is the new oil

At one point, gold and oil were one of the most sought resources. Today, the focus has shifted towards data.

Raynor, Infrastructure Management Manger at Bank OCBC NISP, made this lucid comparison, stressing on how the demand for data is growing.

He drew a simple equation for transforming data into information:

unified customer information (data) + machine learning & artificial intelligence (business wisdom) = decisions & actions of businesses (information)

He talked about how our phones contain all data such that information is within the reach of our fingertips. As such, it is crucial to secure this data.

Raynor laid out the different measures for turning data into information:

  • Robust performance
  • Full encryption
  • No Forklift Upgrade
  • Always ON inline Deduplication & Compression
  • Capacity Consolidation – Credit Buyback
  • Predictive Workload Analysis on Cloud using AI/ML

Case Study: Australia Border Control Innovation

Klaus proposed big data with predictive analytics produces big value and faster and smarter decision making

40 million cross the Australian border by air annually. With more airports, more checkpoints, longer queues and, higher costs, it poses a challenge for identifying risks amongst travellers.

These were information shared by Klaus Felsche, Former Director of Analytics Innovation at the Department of Immigration and Border Protection (Australia).

He proposed using big data to produce big value, making faster and smarter decisions using predictive analytics.

Klaus proposed the following steps:

Step 1- Putting together a team:

  • which understands the border environment and processes
  • which understand existing IT systems
  • of data Scientists and data engineers
  • of leaders

Step 2- Examining existing data

  • Airline data
  • Alert lists (Australian)
  • Alert lists (Interpol)
  • Traveller data
  • Visa data

Step 3- Look for platform solutions

  • Robust – must be available when needed (Australia Border System: 100% availability)
  • Volume – must be able to handle today’s volumes and growth for 10+ years
  • Speed – results are needed to support efficient business (Australia border risk system: 1 sec)
  • Accurate – reliable, consistent and trustworthy
  • Agile– must allow continuous enhancement throughout its life
  • Adaptable– must not lock you into proprietary architecture
  • Accepted– workers at all levels must accept the new system
  • Affordable – costs of procurement, maintenance, running, enhancement
  • Sustainable – ability to continue running over time

Step 4- Procure, Develop, Deploy, Maintain, Enhance

  • Starting with small projects and groups for more efficiency
  • Test and prototype solutions
  • Re-use data before searching for new data
  • Build a core system and enhance it later
  • Use agile start-up methodologies
  • Consider multi-cloud, microservices and container technologies

Klaus concluded the presentations with the insight that putting together a balanced and smart team allows for the best build solution and more productive outcomes.

The main takeaway of this session was that organisations should have a data strategy. They need to analyse their data every 6 months to ensure that their data is relevant, secure and accurate. Employing tech services, they will be best able to monetise on their data and produce revenue.

Delegates of the OpenGov Breakfast Insight: Data Monetisation – Transforming Big Data into Big Value enjoyed and benefited from the knowledge exchange. They left with a better understanding of the ways in which data can be monetised. Let this pave the way to more adoption of data monetisation methods and innovations surrounding it!


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