Start with “why” when building your data-first modernisation strategy

Back in 2017, The Economist ran a cover story arguing that the world’s most valuable resource was no longer oil, but data. “Data is the new oil,” it proclaimed — a notion that many of us could not yet see.

Fast forward to today, where virtually every aspect of one’s personal life has gone digital: from online banking to grocery shopping, restaurant delivery, dating apps, taxi booking, and beyond. As we experience highly targeted online marketing and social media ads, it could not be clearer that everyday interactions and transactions are generating vast amounts of data, feeding into a digital economy that creates value from the insights organisations extract from this growing pool of data.

It’s safe to say that every company is a ‘data’ company, or is pivoting to become one thanks to the global pandemic. Over the last two years, we’ve seen that it is virtually impossible to keep businesses running without robust IT infrastructures required to host the sea of applications needed to support remote work and digital commerce.

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No doubt, digital transformation has become a business imperative. The question is where to start, and how to build a data-first modernisation strategy that is effective and futureproof. While jumping into a data-first model is compelling, don’t overlook understanding your business KPIs and establishing a framework before you’re off and running. For technology companies, it would be easy to think of data-first modernisation as a technology challenge. Data fabric, data cleansing and tagging, data models, containers, inference at the edge — cloud-enabled platforms are all “go-to” conversation points.

While the instinctive response to the issue of being data-driven can focus on “What is it?” and “How to do it?”, it’s important to step back from the noise and structure your thoughts about “why” data-first?

Being crystal clear about “why” will provide the vision for the use case you can seek to develop; it will force you to derive a compelling value proposition and identify the KPIs that will guide and measure success. There are four business-driven agendas associated with how to navigate a data-first modernisation. The first two expose the value of data applied at the digital edge.

The experience agenda

With nearly 6 billion people connected to the internet in 2022, the opportunity to provide value through digital engagement channels remains top of mind. This is especially true for those companies that have experienced the impact of the global pandemic, and how that stress-tested their existing business model.

Digitally resilient business models are becoming mainstream concepts that thrive despite global disruptions. As organisations around the world pivot to digital channels for value exchange, the key differentiator will be the experience.

Given this context, the experience agenda is a breeding ground for new use cases fuelled by data. Areas such as hyper-personalisation, behavioural analytics, and predictive recommendations are good examples of where data-first modernisation can be put to work. KPIs such as customer loyalty and satisfaction (net promoter scores), citizen engagement, recurring purchases, digital revenue streams, or even productivity (if aimed at internal personas) typically emerge as quantitative ways to measure your effectiveness under the umbrella of this agenda.

The digitisation agenda

With an exponentially bigger scale, nearly 75 billion Internet of Things (IoT) devices will be connected by 2025. The scale of this opportunity unlocks the ability to blur the physical and digital boundary. Often associated with initiatives that seek to provide a digital twin of a physical reality, organisations are increasingly able to sense and instrument the world in real time.

Value in this agenda is heavily linked to the physical world. Connect a stadium and you can deliver enhanced fan experiences; connect an airport and deliver passenger experiences. Connect manufacturing equipment and you can drive down overall equipment effectiveness (OEE), improve quality, and increase throughput. Connect a city and you can bring smiles to the faces of your citizens as they get connected to city-wide services more seamlessly.

Connect car sensors and you can start to push on the frontier of autonomous driving. Let’s also not forget smarter working in intelligent spaces, creating efficient and beneficial employee experiences. But most of the effort still focuses on what differentiates you. In other words, your edge is unique, so too is the potential you can unlock to create and exchange new digital value.

Being data-first equips organisations to mine these new sources of data at the edge. It requires an agility that is fuelled by being cloud-enabled, and there are two clear cloud agendas.

The platforms agenda

Establishing a digital platform is a foundational element to exploit and potentially monetise data. Cloud-enabled architectures are the de facto way forward due to their inherent ability to scale dynamically. Organisations can view a platform’s agenda through two basic categories depending on how “elevated” the platform is in creating value.

At the more basic level, a platform can simply provide a collection of business and/or technology capabilities that other products or services consume to deliver their own business capabilities. Think of this as compute, storage, and networking as a service. At the highest level, platforms enable a “platform business model.” This is key in understanding the scope and breadth of the platform agenda. Initiatives inside this agenda can seek to establish a foundational capability for others to use, or it can in fact become the basis of the business.

Think of companies like Facebook and Netflix. Their digital platform is what their business model is based on. As organisations seek to exploit a data-first modernisation approach, establishing how platforms will contribute to the ambition will give clarity and definition to the purpose.

The engineering agenda

As vital as the platform agenda is in navigating a data-first modernisation approach, any value must be engineered before it can be brought to market. Once in the market, that engineering agenda will set the tone for how rapidly improvements, new features, and continuous innovation can be applied to the experience. This agenda has seen tremendous innovation over the last decade.

The engineering agenda provides the collective home for these initiatives. All of them centre around the basic goal of speeding up time to value and reducing friction in the innovation cycle. Increasingly critical to this engineering agenda is how these engineering teams can leverage data services inside the organisation to help improve and differentiate the digital experience. On-demand access to deep learning services that allow engineering teams to exploit these new insights and embed them in data-driven outcomes will be critical to cross the data-first divide we see opening across organisations.

For example, if you are a bank developing hyper-personalised offers through your digital banking app, your engineering team requires access to customer insights (e.g. spending and saving patterns) that you gain by transacting with them through a digital channel. Data — and more specifically, insights — will be the frontier for engineering the next generation of digital outcomes.

These key business-driven agendas of experience, digitisation, platforms, and engineering offer organisations a simple map to lay out their data-first modernisation efforts, but there are also a few foundational agendas that should also be considered.

Mining data for intelligence will continue to push areas like AI into mainstream adoption. Democratising access to services like high-performance compute is a core HPE prediction. Establishing trust with data will be critical if your customers or citizens are willing to engage and advocate for your digital offering. Trust will most certainly require organisations to elevate beyond simple regulatory compliance, into areas like transparency and ethical dimensions.

Make no mistake, if you are not looking to evolve your operating model so that the value of the technology you deploy can truly unlock your full potential, then you will never scale value across your organisation.

Figure out the “why” behind your organisation’s data-first modernisation effort first, and the rest should become more apparent on your digital transformation path.

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