Creating and retaining competitive advantage will increasingly mean leveraging data to make strategic decisions, improve operational efficiencies, and drive sustainable growth and innovation.

With every swipe, click, like, search, stream and purchase, data is being created to the tune of 2.5 quintillion bytes every day, according to Domo, the cloud-based operating system provider. And by 2020 it reckons an astonishing 1.7 MB of data will be created every second for every person on earth.

No surprise then that leveraging data has become a major objective for both companies and governments and given rise to the ‘data economy’. Consultant McKinsey estimates that better access to, in particular, open data – public information and shared data from private sources that everyone can access and use – can help unlock US$3-5trn in global economic value  across seven sectors alone: education, transportation; consumer products; electricity; oil and gas; health care and consumer finance.

Flows of data now play a much bigger role in tying the global economy together, says McKinsey, pointing out that global online traffic across borders grew 18-fold between 2005 and 2012, and could increase eightfold more by 2025. It believes digital technologies and data flows are increasingly “becoming the connective tissue of the global economy”.

More specifically, the European Commission reckons that in the EU alone this data-driven economy had a value of almost €300bn in 2016 and that it will more than double by 2020, reaching €749bn.

Among technologies that will support the rise of the data economy, artificial intelligence is expected to play an especially important central role. McKinsey foresees at least one type of artificial intelligence technology being utilised by 70% of businesses by 2030. That increased adoption of AI technology would be worth around US$13 trn to the global economy. AI could, furthermore, expand employment by around 5% by 2030 as well as improve productivity by about 10%.

While governments are increasingly leveraging open data for improving the quality of life of their citizens, it is corporates that have to date benefitted most from the data revolution, most spectacularly a small band of ‘digital first’ companies with a combined value of US$4trn: Amazon, Apple, Facebook, Google and Microsoft.

As the data revolution gathers momentum, ‘physical first’ companies – the overwhelming majority of corporates and financials globally – will need to learn from the success of the digital firsts as they too look to leverage data and monetise it. The challenges ahead for them are varied and many: exploiting new technologies like AI, Internet of Things (IoT) and 5G; dealing with regulations such as PSD2/Open Banking and GDPR, developing new business models; addressing the needs of millennials and native digital generations that follow as customers; and ensuring data security, to name but a few.

However, as Nigel Dobson, Banking Services Lead and Leigh Mahoney, Head of Wholesale Digital, Institutional, ANZ point out, while the challenges for organisations are many, there will also be many opportunities for them that will emerge as the data economy evolves.

It’s a new frontier, and those who are accountable for delivering the insights have a huge responsibility to get it right, reassuring all stakeholders that the boundaries within which they are operating are appropriate.

Nigel Dobson, Banking Services Lead, ANZ

Creating and retaining competitive advantage will increasingly mean leveraging data to make strategic decisions, improve operational efficiencies, and drive sustainable growth and innovation.

In commercial terms, few could dismiss the importance of data; and fewer still could deny that competitive advantage awaits organisations able to quickly access, integrate, refine, analyse and share data.

“It’s becoming increasingly evident that the value of data, and data analytics, as a support to business is a tremendous opportunity,” says Dobson. However, he notes that for every action, there is an equal and opposite reaction.

In this instance, unbounded data analytics is met by regulatory forces acting to protect citizens – particularly measures such as the EU’s GDPR, Australia’s Consumer Data Right (CDR) and Singapore’s Personal Data Protection Act (PDPA).

Value versus risk

These Acts are empowered to heavily penalise organisations that do not compliantly manage data storage. In GDPR’s case this could be up to €10m, or 2% annual global turnover – whichever is higher. For CDR, a fine of up to AU$2.1m for businesses is possible. And for PDPA, it could mean a fine not exceeding S$100,000. They could add up to a significant disincentive for firms seeking to engage with the new data economy.

“The narrative is reaching new highs in terms of the commercial value of data and analytics, but the consequences of getting it wrong have similarly increased,” notes Dobson. This, he believes, has led some organisations to adopt a more conservative approach to the handling of their data assets.

It is also unhelpful for many firms that siloed data has created for them enterprise-wide divisions. Finding a single customer-reference across a number of products can prove difficult in these circumstances, says Dobson. The customer annoyance this typically presents – explaining a case repeatedly or receiving the same information multiple times – is not uncommon.

These data siloes have a negative internal impact too, he notes. In the banking sector, for example, where data management is characterised by some of the highest required levels of privacy and security, the “self-erected barriers” of product silos and customer segmentations can lead to sub-optimal performance, certainly from the perspective of additional timely customer insights.

For many banks though, the notion of providing value by using data analytics to help customers gain a deeper understanding of their own and their competitors’ business activities, is a key differentiating factor. Indeed, for all regulated institutions, getting accurate data into the hands of the right customers in a manner that is timely, secure and compliant is vital.

The imperative for banks and corporate clients to find quick answers to some of their most pressing business concerns is leading to the deployment, or at least the consideration of real-time technologies, comments Mahoney. He believes this state of affairs is heralding an urgent overhaul of risk management processes.

The ability to share the vast computing power offered by providers such as Google, Amazon and Microsoft is a major benefit, but at the same time, warns Mahoney, organisations taking this huge step forward need to find a way of balancing speed of data processing with appropriate controls around security and compliance.

“Controls must be established around who has access to data, when and for how long, because across many organisations increasing processing speeds and the interconnectedness of data pools now demands it,” he explains.

New responsibilities

The rise of the new data economy is made yet more complex by a simultaneous shift of focus from data about ‘things’ – metrics describing the movement of goods or money, for example – to data about people, notes Dobson. “As a bank, we’ve always had data about people, but the idea that we would do more with it other than store it is relatively new.”

Where metrics on liquidity management or account consolidation reporting focus on aiding the banks and their clients’ own needs, there is now a great interest in quantifying human activities, offering new levels of insight and understanding.

Whether it’s for autonomous vehicles on the roads, automated medical procedures or a host of other possibilities, improvements in data transmission could open up industries where precision-machinery communicates in ways that, today, we can only dream of.

Leigh Mahoney, Head of Wholesale Digital, Institutional, ANZ

As the focal point shifts, access to cloud-based data solutions and almost unlimited computing power is delivering some highly articulate results. But concerns are rising around privacy and accuracy of the data held.

Indeed, notes Dobson, there is increasing general discomfort around organisations forming and acting upon deeper data analytics-derived insights into individuals. The opportunities for organisations to push the boundaries of what is acceptable here are a constant reminder that “technology leads and regulation lags”.

Says Dobson: “It’s a new frontier, and those who are accountable for delivering the insights have a huge responsibility to get it right, reassuring all stakeholders that the boundaries within which they are operating are appropriate.”

Levelling the field

Of course, availability of technology is not always followed by its adoption. In this respect, the utility that corporates can gain from data, either created in-house or imported from third parties, largely correlates with an organisation’s technological capacity and willingness to invest in leveraging data. The current degree of variance in technological uptake is noteworthy.

The Australian mineral and energy resources sector is particularly well-evolved in terms of technology and use of data, notes Dobson. This follows from the intensive automation programmes seen across the supply chains of major players, from extraction through to delivery. With drones and GPS-assisted self-driving trucks in remote sites, and the heavy adoption of the IoT to monitor progress, commodities could easily be considered a leader amongst all sectors in Australia. With the country’s iron ore exports alone accounting for 58% of a global US$66.6bn market, it’s not hard to see how optimising efficiencies can make a huge difference.

Many other sectors are just beginning their journey towards optimising data-usage. These players are not necessarily laggards and, for Dobson, “there is a correlation between sectoral appetite for data analytics, and the sensitivity of the data held by the sector”.

The highly asymmetric risk faced by companies holding sensitive data – especially given the new power of the regulators – has the effect of curtailing their desire to move too far ahead of the rule-book, he explains. “These businesses are as interested in being trailblazers as any other, but the consequences of non-compliance with data regulations can be severe.” As such, most ensure their investments in the area of leveraging personal data move strictly in alignment with the industry and the law, but as explained earlier, “technology leads and regulation lags” and so it is perhaps inevitable that they appear to be slow on the uptake.

Greater understanding

Where freely given personal consumer data (as might be harvested by supermarket loyalty cards) is leveraged, Mahoney notes that it can drive revealing discussions around demographics, customer behaviours and loyalty. With more accurate insight than simple ‘gut feeling’ or customer anecdotal evidence, the effect can be to steer better decisions on investments in product development or business expansion, for example.

Exploitation of private personal data, such as medical or employment records, crosses the regulatory boundary but businesses in this space can still use generic ‘anonymised’ data to gain a deeper understanding of customers.

That said, as people become more aware of the power and value of data, there is an even greater effort towards securing their own privacy. Some of the recent highly publicised data breaches and the exposure of behaviours on certain social media platforms have sounded the alarm bell for many individuals in this respect. Where once they gave their data freely, a more guarded attitude prevails; people know and understand the rights afforded them by the regulators, and why those rights exist.

The development of open banking is also driving further awareness of the value of data, says Mahoney. “With the discussion comes a greater understanding of the consent management frameworks supporting the roll-out of APIs.” Increased adoption of IoT is also shifting market dynamics. This is a technology capable of generating vast amounts of highly specific data with which businesses can potentially target even the most niche areas of consumer life. Once again, as its benefits are explained, Mahoney sees it raising levels of awareness around how data is being used.

Commensurate with this greater understanding are the policy-driven initiatives designed to return rights to the individual. This is changing the dynamics of the relationship between data subject and data holder, but it is also helping to construct a solid framework of understanding for the digital age, enabling the next wave of innovation to push ahead – and businesses to leverage the new data economy in safety.

Riding the next wave

With 5G networks rolling out across the world, the capacity of data transmission is mounting. This, says Dobson, is empowering all stakeholders and giving rise to new sources of data. In the future data economy, he suggests machine-to-machine communication could be amongst the most powerful.

“Whether it’s for autonomous vehicles on the roads, automated medical procedures or a host of other possibilities, improvements in data transmission could open up industries where precision-machinery communicates in ways that, today, we can only dream of,” says Mahoney.

The nature of machine-to-machine data transmission may have a huge impact on the nature of commercial models and economies in general. As cutting edge solutions become commonplace, it will impact core commercial activities such as payments and collections. With real-time data, the rise of fractional or micro-payments begins to emerge.

Treasury tends to think in terms of end-of-day batch payments. But where the transmission method increases in velocity, so too does the data flow. This, suggests Dobson, will lead to a “profound change to the way commercial entities operate”.

Indeed, instant automated micro-payments could be made to suppliers based on devices sharing job completion data, potentially several times a day as a project progresses. With confirming transactions taking place at near-instantaneous speed, the velocity of commerce increases in parallel. Batch processing may be fine for now but the positive implications of real-time data exchanges for treasurers are significant in terms of liquidity and working capital management.

Getting ready

With the increasing speed of networks and data transmission, Mahoney believes that the power of data – and thus its value and price – becomes “inextricably linked to the solution providers capable of transforming data to solve real business challenges”.

However, rather than acquiring data assets en masse, or implementing a broad-sweep approach to the new data economy, he advises corporates to adopt a focused ‘use-case’ approach. Building a use-case first requires data to be extracted from the right sources – potentially challenging in a legacy environment. The data haul must then be transformed into value-adding information; appropriate platforms and in-house skills must be available to achieve this. The final high-level consideration is data distribution. This means getting the insight to the right place, at the right time, in the right format and in a secure and governed way.

For use-cases to succeed, and for businesses to engage successfully with the new data economy, it becomes incumbent upon each function to identify and understand their particular challenges or goals before deciding on the scale of investment. At this point, it is advantageous to work closely with external partners, particularly relationship banks who can offer an appropriate wide-angled view of the business itself and the environment in which it operates.

As the data economy gathers momentum, competitive advantage will most likely be found by businesses capable of leveraging internal and external data. Indeed, when it comes to making effective strategic decisions, driving operational efficiencies, and ensuring sustainable growth and innovation, access to the new king would appear to be vital.