Unleashing data's true potential: the rise of data intelligence

Data intelligence unlocks data's potential through real-time insights, agile decisions, trustworthy AI, personalised experiences, and a data-centric culture
Andy Baillie
Data graphic

Our customers tell us that traditional ways of managing data just aren't going to cut it anymore.

Data management used to mean collecting, storing and maintaining data integrity within siloed systems and databases, usually for compliance purposes. Now, to truly succeed, businesses have to move beyond those legacy methods and fully buy into data intelligence – a mindset that optimises every phase of the data lifecycle and unlocks the full value and insights trapped within a company’s data assets.

With this capability, businesses can respond swiftly when market conditions shift, customer preferences change, or competitors make a bold move. They can pivot strategies, tweak products and services, and seize new opportunities before rivals even know what hit them. This agility is absolutely paramount these days, where making informed decisions quickly can make or break success.

However, our recent survey reveals a stark reality: only a quarter of business decisions are actually based on solid data.

Many companies still lack the tools, processes, and mindset to truly leverage their data assets across the organisation. To bridge this gap and harness the power of data intelligence, organisations must prioritise three crucial things: fostering a data-driven culture, building trustworthy AI models, and delivering personalised experiences.

Forging a data democracy

Data intelligence starts with improving data literacy amongst employees at all levels, fostering a culture where data truly drives individual decision-making and continuous improvement from the front lines. With self-service analytics tools, employees can tap into and analyse data without handholding from data specialists.

For instance, at a high-speed manufacturing plant, line workers could use data intelligence tools to monitor equipment efficiency, output quality, and wastage rates in real-time, allowing them to quickly fine-tune processes and drive improvements.

Eliminating AI’s ‘black boxes’

Clean, well-organised, and well-governed data is essential for training AI models that are accurate, transparent, and able to explain their reasoning – ensuring reliable outcomes and maintaining trust in AI capabilities. Achieving data intelligence means building a foundation of high-quality, comprehensive data needed to build AI systems you can actually trust, free from bias and able to justify their recommendations, especially in high-stakes environments like healthcare.

For example, data intelligence can merge and clean diverse datasets like electronic medical records and clinical trial data, fuelling AI models that develop personalised treatment options and accurate diagnoses while explaining their recommendations in a way that earns trust from patients and doctors.

Another use case is customer chatbots on brand websites. When fed the right, accurate data, AI chats can resolve customer queries without human intervention. By adding pre-prepared queries, you can guide customers to the right resolution quickly and minimise disruptions – Amazon is a key example of this method. 

Delivering hyper-personalisation

In today's experience economy, customers expect highly personalised products, services, and interactions tailored to their needs. By capturing, integrating, and analysing customer data from all touchpoints, data intelligence provides that unified view, enabling businesses to create detailed customer profiles and adapt offerings in real-time as preferences shift.

Retailers can leverage comprehensive customer data – demographics, past purchases, browsing activity – to power AI recommendation engines, dynamic pricing, targeted marketing, and personalised experiences that keep customers engaged and loyal. A prime example is Spotify using AI to curate personalised playlists and concert recommendations based on listening habits.

Facilitating an end-to-end approach

Modern data intelligence tools offer automated functionalities for data discovery, structuring, and quality monitoring, ensuring data reliability and trustworthiness. They enable self-serve data preparation and analysis, empowering teams throughout the business. These tools also facilitate collaborative data enrichment, establish a unified "golden record" through master data management, and maintain regulatory compliance through data governance and security controls.

As data accumulates at an unprecedented pace, organisations can no longer afford to ignore the wealth of untapped data trapped in siloed systems. By adopting the right tools and a data intelligence mindset, businesses can dismantle internal barriers, create a data-centric culture, and secure a competitive edge by deploying smarter, insight-driven strategies that drive continuous innovation and growth.

Written by
May 7, 2024