What the new digital playing field looks like

Our lives are going digital. To successfully compete and grow today business models must fundamentally evolve - as quickly as underlying technologies.

Rapid shifts to mobile, rich content, social media and, critically, ecosystem platforms which intermediate the buyer/seller relationship give consumers significantly more knowledge and price transparency which translates to more power in the buying experience.

"Rapid [tech-driven] shifts in the buyer/seller relationship have empowered consumers with significantly more knowledge and price transparency."
Darren Abbruzzese, GM, Data, ANZ

That means if companies are going to stand apart they must do something different.

Organisations can innovate on product features which may for a brief period of time provide a point of difference but new features are often quickly copied by competitors reaffirming, levelling the playing field – but still leaving companies with greater internal complexity to manage.

To standout and succeed in the digital age organisations need to focus on delivering an intuitive, personalised and seamless customer experience driving stickiness, loyalty and long-term relationships.

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By leveraging data analytics, organisations can develop highly engaging customer experiences as a key way to build a growing and sustainable market share, while avoiding a margin-destroying race to the bottom on price.

Native digital disrupters and ecosystem drivers such as Amazon, Apple, Google, Airbnb and Uber implicitly understand the value of data analytics and employ these to enrich customer experience.

Think of Amazon suggesting items you may like based on your purchase and those of previous customers or Uber’s aggregation of customer demand, traffic conditions and expected travel times to implement ‘surge pricing’ attracting more drivers into the system during busy periods.

These digital leaders treat data as a strategic asset, valuing and leveraging it to improve the user experience, integrating their product seamlessly into their customers’ lives. In doing so, they set a new minimum level of experience customers just expect and for others to match.


The use of data to deliver a personalised experience isn’t limited to digital natives, pre-digital organisations can also capitalise on the unique data they possess.

Southwest Airlines runs speech analytics over their service centre calls to extract a deeper and more meaningful understanding of what their customers need. A major Australian telco analyses searches on their website and sends signals into their call centre router, connecting customers deemed at risk of leaving to crack sales staff.

Opower, a US-based utility company, uses big data to analyse fine-grained customer consumption from smart meters and feeds this back to customers with value-added insights, allowing them to monitor and change their habits to be more energy efficient.

Disney puts big data to great use in their theme parks by combining purchase and ride histories with RFID-enabled wrist bands to direct your favourite action heroes and fairies right to where you are for live, personalised performances.

Most companies these days, digital natives and otherwise, will already be capturing the data they need to develop truly engaging customer experiences. Customer static data, transaction data, website access logs and search strings, product financials and usage patterns are easily sourced from frontline systems.

Further, the technology to bring this data together, model and analyse it for valuable experience-creating opportunities already exists and is readily available in an ever-expanding and maturing array of open source, proprietary and cloud-based solutions.

What is lacking is a top-down led desire for an enduring customer relationship, one than transcends organisational silos, where raw data assets from across the company are brought together to create a defining customer experience proposition.


It was 1965 when Intel co-founder Gordon Moore predicted the number of transistors on an integrated circuit would double every year and the trend would continue for the foreseeable future.  Now known as ‘Moore’s Law’, this is really a working example of exponential growth. 

Moore was almost right. The rate of doubling has worked out to be closer to two years but the effect is essentially the same.

State-of-the-art chips in 1965 had a few hundred transistors; in 2016 that figure has reached more than 15 billion with the rate of growth unchanged. The iPhone in your pocket now has 100x the processing power of the most advanced supercomputer in the late 80s, without the multi-million dollar price tag or the need to wheel around your own mini power station to run it.

This explosive rate of growth isn’t isolated to just computing power.  Computer storage, both disk space and memory, is also growing exponentially with total world computer storage only describable by a number the human brain can’t comprehend (for the curious, it’s a one followed by 22 zeros in bytes).

I used to have a lot of DVDs. If you were to save all the data onto DVDs, put each DVD back in its plastic case, you’d create a wall of DVD cases that would circle the Earth 10 times.  By 2018 we’ll wrap the Earth in DVDs another 10 times again.

While a lot of this data is structured data, meaning data you can easily represent within an Excel worksheet, the big growth in data is from unstructured data, things like video, voice recordings, and free text such as news and social media posts.

In banking, the data landscape is no different.  At ANZ, data volumes - collected through customer interactions and transactions, and what is produced internally - are continuously growing, as is the ability to harness and process data using technology.

‘Big Data’ is the buzzterm to describe the tsunami of data volumes companies now face. These massive data sets can be analysed to reveal patterns and trends, especially relating to human behaviour and interactions. Given its size and scale, Big Data has its own specialised tech.


Often called ‘Hadoop’, it takes the explosive growth in computing power and storage, all of which is getting cheaper by the day, and throws it at our vast amounts of data. This technology allows us to collect, model and analyse our data in ways we’ve never been able to before and do so at massive scale.

The use cases for big data tech are expanding all the time. Current approaches include analysing our internal network traffic for security threats, reviewing customer transactions for misuse and fraud, and searching for patterns in our data to better tailor our products and services through offers and campaigns.

Future use of Big Data in banking will be heavily customer-centric as the sector aims to build a world-leading customer experience. This is where big data will make a big difference not just to banks, but also customers and communities.

Darren Abbruzzese is GM, Data at ANZ

A version of this story originally appeared in APAC CIO Outlook Magazine

The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.

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