Why top enterprises are creating a data-driven cloud strategy

'The customer is king' is arguably the marketing industry's most famous – and hackneyed – mantra but the digital revolution is forcing companies and organisations to pay it more than lip service.

Advanced data analysis techniques and tools are helping businesses of all stripes predict client needs and find new pathways to profit.

They do so by enabling organisations to extract valuable information about the motivations, preferences and behaviours of those who buy their products and services, from previously inaccessible warehouses of customer data.

Cutthroat competition for customers has seen financial services institutions embrace this push with gusto.

The profiling of individuals and market segments is delivering unprecedented insights into buying patterns and is driving the creation of marketing programs and services which anticipate and respond to customer needs and wants comprehensively and intuitively.

The focus is on the 'three Ds' – the discovery of information about what makes customers tick, the design of more compelling customer experiences and the delivery of 'always on' marketing programs that engage with customers, at the right time and in the right way.

It's this obsession with keeping the customer satisfied that's made the conversation about shifting key systems and applications into the cloud a matter of not whether, but when – and how.

Moving towards the cloud

Spending on public cloud services in Australia is predicted to hit $4.6 billion in 2018; an increase of 18.5 per cent on the previous year, with software-as-a-service expected to comprise the majority of this sum.

Financial services firms are likely to account for their fair share of this spend. The banking and securities sector is not known to stint on high tech investment and its total ICT spend in Australia was expected to reach $14.8 billion last year, according to Gartner.

In my observation, financial services firms can typically be found at one of three waystations on the journey to wholesale adoption of a data-driven cloud strategy.

Slow movers are still attempting to quantify the value proposition – exactly how much benefit they can expect from their initial investment buck. Those in the middle have a defined cloud strategy and are implementing some standalone systems. And advanced players have moved towards wholesale adoption of the public cloud and are reaping the exponential benefits – and resultant business advantages – cloud-based analytics can deliver.

Regardless of their progress, the end goals are the same: to use data from more sources to improve the customer experience; and to use the public and private data in their possession to inform investment decisions across the organisation.

Going all out – or easing on in?

While the benefits of adopting a data-driven cloud strategy may not be in dispute, security and compliance standards developed for on-premises infrastructure and systems in the pre-cloud era can be a roadblock for some institutions.

Those building a business case need to make the executives who set up and monitor these standards part of the conversation or risk being derailed by concerns about the security of the cloud model.

A push to the cloud – and the accompanying abandonment of on-premises systems – can also be the catalyst for a turf war of sorts, if 'ownership' and management of the initiative and infrastructure come into question.

These things are unlikely to be issued if there's buy-in from the top. In such cases, security validation is typically followed by an assessment of whether applications can be scaled, if migrated to the cloud, and the launch of one or more pilot projects to demonstrate the value and potential of the move.

It can be somewhat more challenging if the Board is yet to get on board or has done so with reservations.

A foot-in-the-door approach, whereby sponsors of the cloud strategy develop and pilot a discrete use case and conduct a business value assessment, can be the best way to move forward.

The beauty of the cloud model is that it allows organisations to start small and spend small before committing themselves wholesale – a welcome contrast to IT projects of yore, which called for high upfront investment in the hope of a business benefit months or years down the track.

Data warehousing technology that supports the shift

Successful migration of applications to the Cloud hinges on the deployment of data warehousing technology that's fit for the purpose and makes the process of amassing and analysing data, and extracting the insights it contains, simple and cost-effective.

Snowflake's cloud-based data warehouse has the capacity to process the explosion of semi-structured data generated by mobile and social media systems and the burgeoning 'internet of things'.

The technology separates storage and computing functions; thereby sidestepping the problems of redundant storage space and high costs historically associated with data warehouses and big data platforms.

Financial services institutions which use this scalable, pay-as-you-go technology to underpin early forays into the Cloud, or the wholesale migration of their data analysis function, will be well placed to reap the resultant productivity and profitability dividends.