Can your data strategy keep up with cloud innovation?

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Enterprise cloud adoption shows no danger of slowing, and neither does the pace of cloud-based innovation. Gartner has predicted that worldwide end-use spend on public cloud services will grow by 23.1% this year to reach $332.3 billion, even more than the $270 billion spent in 2020 in the wake of the global pandemic.

Leading hyperscale cloud platforms now give organizations everything they need to develop cutting-edge applications, including machine learning and IoT. Cloud has become both fundamental and transformative.

However, unstoppable growth of cloud and the accelerated rate of change creates a challenge for IT, not just in maintaining pace with an ever-changing landscape, but in managing the flood of data that comes with it. At Microsoft’s Ignite conference in March, Satya Nadella said ‘the volume, variety and velocity of data will go through explosive growth in the cloud, and in particular, at the edge.’ In this new era, he suggested ‘data will be more private, more sovereign. Data governance and providence will take on new importance.’

Organizations will need to consider how to capture, store and secure that data, and factor these considerations into business-critical decisions. But many CIOs now find themselves working with five to eight different cloud service providers, complex hybrid environments and a range of different platforms. As a result, creating a data strategy is far from a trivial endeavour. As Microsoft CDO Andrew Wilson said in a recent episode of The Living Enterprise podcast series, ‘there’s a huge challenge and balance between democratization, speed and agility, but also security and appropriate use and access to data.’ All these concerns need to feed into a coherent data strategy.

Developing a data-driven culture

This data strategy must be fluid and agile, but always aligned with the organization’s business goals. That might mean starting small, focusing on one clear need or problem, then expanding outwards to cover more – as KPIs are reached, the road to ROI clears and the organization’s data culture matures.

Or it might mean going big, as Adobe did when it put its data-driven operating model (DDOM) at the heart of its business transformation. Adobe’s strategy is customer-centric, focused squarely on the different phases of the customer journey. It directs how it engages with its customers, how it measures that engagement, and how it knows whether that engagement was successful or not. This approach requires discipline and structure, but this model has enabled Adobe to build and scale its enterprise business and grow revenue from its Creative Cloud service by close to $5billion since 2014.

Today, even as the demand for data grows, the need for a balanced strategy still rings true.

This also worked because Adobe was well-placed and able to develop a data-driven culture, driven not just by data scientists – though attracting and empowering them is vital – but by targeting the benefits at business leaders and end-users. With the resulting buy-in, it was able to integrate business and customer data into every business process in order to drive more informed decision making. What’s more, an effective data strategy always involves working with the needs and parameters of the data and the applications and services it fuels. Data gravity matters, as does performance, storage, sovereignty and security.

Back in 2017, an article in the Harvard Business Review recommended a strategy that balanced a defensive approach to data, informed by risk, compliance and the need for integrity, combined with an offensive approach focused on insight, analysis and supporting customer-focused business objectives. Today, even as the demand for data grows, the need for a balanced strategy still rings true.

An effective data strategy goes hand-in-hand with a data-driven culture, requiring high levels of data literacy at every level of the living enterprise. To find out more about how you can develop your data strategy, download this whitepaper on mastering digital literacy.