Architecting The Data-Driven Organisation: Why A Proper Strategy Is Crucial

by Asgarali Mia – Head of Technology: iOCO Data and Analytics, and Candice Solomons – Business Executive, iOCO Data and Analytics.

In much the same way that modern skyscrapers won’t remain erect without a skilled architectural design, solid foundations and appropriate structural engineering, data-driven organisations will not thrive into the future without the right blueprints, people, processes, and technologies.

Despite strong intent, we continue to see leading organisations struggle to achieve even a common customer or product view. Most aspire to a 360-degree understanding of their customer or operations yet focus heavily on the front-end of single-view applications while neglecting the back-end data foundation that must enable it. A reliable, well-governed data layer is critical to achieving the unified view executives expect.

Broad, agile data strategies 

While most organisations have already started their data journeys, as the environment changes, they frequently find their foundations aren’t solid enough to support scaling and changing technology.

Many start their journeys with analytics, then realise later that they need to improve governance, security, and accountability . They discover that data management is becoming a challenge, and data silos are hampering optimal utilisation of that data. They learn too late that they should have started with the right plans and roadmaps.

Another key lesson learnt is that developing a solid data strategy should not be an exercise done only once every five years. Because the environment changes so rapidly, organisations need to address and update their data strategies on an ongoing basis. We recommend that they institute a data governance forum where business and IT come together regularly, focusing on shorter term strategies that are more agile.

They must consider the human component, the processes, and the policies around their data. Data strategy should not be the preserve of IT alone – it must include business, the people that are accountable for it, the business rules, the technology that enables it and the security and governance around it.

Laying the right foundations

A well-designed data strategy must begin with a clear understanding of the organisation’s data maturity. This includes the strengths, gaps and risks within the current environment, and what architecture and governance structures are needed to achieve business objectives.

Businesses need to assess the strengths, gaps and risks in their current data environments, and what architecture and governance structures are required to achieve business objectives. If inconsistencies are to be addressed, companies may also need to create structures for accountability. These will be dependent on the company and whether it is using federated or centralised models. Within the federated model, data owners and data stewardships should be created and aligned with business rules and policies, rolling off into a governing body to support control, governance, and compliance.

Architecture recommendations should support consolidation, accessibility and trusted data for analytics and AI.

Many businesses are concerned about shifting data physically, or change ownership of the data, for it to be consolidated in a central location that will support analytics and AI. However, there are solutions such as data virtualisation, where organisations can leave their data where it is – even in siloed environments. These solutions enable organisations to apply standardised governing principles while allowing ownership to stay within the original environments. This delivers a highly governed, secure, top quality environment into which the advanced analytics and AI capabilities can be plugged.

Skills, security, and governance structures are equally critical. Without the right people and safeguards, even the most sophisticated architectures fail to deliver value.

Enabling AI-driven futures

Organisations that build solid data foundations are better positioned to scale AI effectively, reduce operational risk, unlock new efficiencies, and compete in a rapidly shifting business environment. iOCO’s well established data practice can help businesses to develop a comprehensive, agile data strategy, which can create the roadmaps and capabilities needed to become future-ready and data-driven.