By Andy Baillie, below, VP, UK&I, Semarchy
For years, businesses have primarily focused their data efforts on management – handling, governing, and ensuring compliance with regulations. While these are crucial foundational elements, they are simply table stakes in today’s data-driven landscape. To truly drive innovation, maintain a competitive edge, and unlock maximum value from data, organisations need to evolve their mindset and approaches. They need to shift towards data intelligence.
Data intelligence goes far beyond just data management. It’s about comprehensively enhancing and optimising the entire data lifecycle – from how data is sourced, integrated, and organised to how it is analysed, shared, and consumed. With a data intelligence strategy, businesses can generate precise, trusted, and actionable insights. This allows them to identify new opportunities, make smarter and faster decisions, and guide overarching business strategies and operations.
The reality, however, is that according to our recent survey, only 25% of business decisions are truly data-driven. A key reason is that most companies simply lack the tools, processes, and mindset to fully unlock the potential of their data assets across the enterprise.
There are three key imperatives driving the urgent need for organisations to embrace data intelligence:
- Building trustworthy AI models
The rapid proliferation of artificial intelligence (AI) across industries has highlighted the growing importance around developing AI models that are not only accurate but also transparent and explainable. Data intelligence plays a vital role by providing the comprehensive, high-quality data required to create trustworthy AI solutions.
High-quality data is essential for training AI models effectively and ensuring their outputs are dependable and unbiased. Without clean, unified, and well-governed data, AI models can produce inaccurate or skewed results that lead to poor decisions and erode trust in the technology.
In healthcare, for example, data intelligence can consolidate and harmonise diverse datasets like electronic medical records, clinical trials, research papers and more. This trusted, unified data can then power AI models that generate personalised treatment plans and precise diagnoses, while also providing clear rationales behind each recommendation to foster trust among patients and practitioners alike.
- Enabling a data-driven culture
For organisations to truly innovate and remain agile, they need to foster a data-driven culture where employees across different teams and roles can make informed, self-serve decisions. Data intelligence promotes data literacy and democratises access to insights, enabling this self-sufficient decision-making.
Self-service analytics tools that are part of data intelligence platforms allow employees in all lines of business to easily access and analyse data on their own, further empowering them to become data-driven without relying on specialised analysts.
Imagine a fast-paced manufacturing business: data intelligence tools can give employees on the factory floor real-time visibility into key performance metrics like equipment efficiency, output quality, scrap rates and more. This allows them to quickly identify issues, optimise processes and drive continuous improvement on the frontlines without waiting on central analytics teams.
- Delivering hyper-personalised experiences
In today’s experience economy, customers expect hyper-personalised products, services and engagement tailored specifically to their individual preferences and behaviours. Data intelligence is critical for businesses to deliver on these expectations at scale across the entire customer journey.
Without the ability to capture, integrate and analyse customer data from multiple touchpoints, companies are flying blind when it comes to understanding individual customers. Data intelligence provides that comprehensive view, allowing businesses to map intricate customer profiles and precisely tailor offerings, messaging, and experiences in real-time as needs and behaviours evolve.
By analysing comprehensive customer data – from demographics and purchase histories to real-time browsing activity, behaviour patterns and more – retailers can generate rich, unified customer profiles. Furthermore, these insights can power AI-driven recommendation engines, dynamic pricing models, targeted marketing campaigns and personalised experiences that keep customers engaged and build lasting loyalty.
An end-to-end approach
To make this transformational shift towards becoming a truly data-intelligent organisation, businesses need robust technology solutions and strategies. The latest data intelligence tools provide automated data discovery and organisation to simplify access to an enterprise’s distributed data assets. They offer comprehensive data lineage and quality monitoring to ensure trustworthiness and identify issues. These solutions also enable self-serve data preparation and analysis to empower teams across the business. At the core, they provide centralised master data management (MDM) to create a consolidated “golden record”. Additionally, data intelligence tools include data governance and security controls to maintain compliance, as well as collaboration tools to share, discuss and enrich data assets.
The true power of these data intelligence solutions is that they facilitate an end-to-end approach – from optimising how data is sourced, integrated, and curated to enabling self-serve analytics and insights. This creates a virtuous cycle where data becomes more trusted, teams become more data literate, and the entire organisation becomes more data-driven in their strategies, decision-making and operations.
As data volumes continue exploding at staggering rates, organisations can no longer afford to let their data lie dormant in siloed systems and spreadsheets. By embracing data intelligence with the right tools and mindset, companies can break down internal barriers, foster a data-centric culture, and ultimately gain a competitive advantage through smarter, insight-powered business strategies.
