Data is being elevated from an inwards-facing function to be more commercially aligned. The aspiration is that data can be harnessed to produce or power external-facing products, and become a profit-generation engine in its own right.
But elevating data to this extent is not easy.
A recent study commissioned by Snowflake shows that the vast majority of organisations aren't set up for it: only 6% of businesses globally use, access, and share data in a way that grants them all the business benefits provided by a robust data strategy.
The barriers to that are fundamentally twofold: leadership and technology
For businesses with higher order data ambitions, it is well worth understanding what stands in your way, and how to pursue meaningful resolutions.
Levelling with leadership
Only 45% of Australian businesses have a C-level mandate to become more data-driven, which is below the Asia Pacific (47%) and global (51%) average. That is likely to be a key reason why just 41% of Australian businesses make most or all of their decisions with data.
Australia isn't alone here. The most common position worldwide is that 'some' decisions are informed by data, while others aren't.
That's a gap that we all have to work to close, or else an entire 'data economy' of opportunities will be missed – and ultimately lost. These are opportunities that can enable businesses to tackle complex problems, gain a competitive edge, and build new revenue streams by taking tailored data products and services to their customers, partners, and any other data economy participant.
Leadership is a necessary input, but also a problem for some businesses: 15% say the "leadership team isn't sufficiently involved in or invested in their data strategy", and another 19% say their organisation "doesn't have a strong culture of using data", another very top-down problem.
For a business to become a 'data-forward' business, a C-level mandate is needed. Without strong backing from the top, it may not be possible to elevate data beyond a more traditional operational view – as a key input to producing reports or dashboards – in such businesses.
Organisations that achieve success with data are consistently those with CEOs that believe in the power of data and that are invested in harnessing its potential.
Separate research by Gartner shows that the most successful chief data officers (CDOs) are those that report to the CEO. Close ties to the CEO invite a different type of conversation and engagement: one that brings the opportunities of the data economy into full focus. The CEO does not have to be a data or technology professional, but they should be able to articulate, clearly and loudly, what data-driven insights mean to the business. And the CEO should empower their CDO to implement the organisation's data-forward strategy.
"High-performing CDOs are significantly more likely to have projects with the CEO that focus on value outcomes. To increase the attention of the CEO and other business executives, the CDO should seek out data projects that focus on revenue generation, data monetisation and productization, improving customer satisfaction and removing obstacles to data sharing," Gartner counsels.
For almost one in three Australian businesses, tooling also constrains their data-driven ambitions; 16% say they lack the right tools or platforms needed to centralise, access, integrate, analyse, and share data; and a further 13% say "lack of technology" has other regulatory-related impacts.
Complicating things, data is often not held in one place: only 9% of Australian businesses have all their data in one cloud repository; 57% have all their data in the cloud but spread across different platforms, and a further 30% have their data split between cloud and on-premises systems.
At the core of every data economy technology strategy is a modern, fit-for-purpose data platform with near-instant and infinite storage and computing that can scale up and down – and on the fly. This solution should also be flexible in order to centralise, integrate, analyse, and share various types of structured, semi-structured, and unstructured data.
It should also have other characteristics: be flexible and versatile, capable of executing diverse analytic workloads; have resilient data security features baked in; and be fully managed by the platform vendor, minimising platform maintenance and administration, so that IT and data professionals can focus on high-value, strategic projects that allow data economy ambitions to be realised.