Your Data Foundation for AI: Why a strong data foundation is the key

AI is all the rage, as businesses and employees strive to become more competitive and leverage the latest tooling. The tricky bit? When it comes to getting the most out of your AI tools, the data its working from is make or break.

Data is the foundation for AI, bad data means bad outputs. But equally, with an effective data management strategy in place AI can be transformative for a wide variety of organisations. A robust data foundation for AI is the cornerstone that underpins any successful digital transformation or innovation strategy.

Where does data fit in wider digital transformation initiatives? The bedrock of digital transformation

Data is at the core of every facet of a digital transformation journey. It sits at the heart of every product, system and service integrated into an organisation. The most common challenge we see is when an organisation moves to adopt one of these, eager to see the benefits it promises but find their data isn’t where they need it to be to realise those benefits.

We often see customers turning to us when they’re grappling with disparate systems that don’t naturally talk to each other or which weren’t set up to do so. Often, new systems and platforms are implemented at pace to remedy another challenge or to replace outdated systems, without considering how data will flow between them. As a result, we see data stuck in silos on incompatible platforms and cumbersome manual processes slowing teams down.

We always recommend keeping data access and integration at the front of mind when implementing new systems to keep progress flowing. Organisations that take this approach, don’t find themselves needing to extract their data and centralise it before they can get stuck in to the next phase of their digital roadmap.

Without this step to establish the data foundation for AI, businesses face hard yards later trying to get their data into shape to see the outputs they need. Having a solid data foundation for AI saves time, unlocks insights and paves the way for more advanced innovation down the line.

How can data help organisations innovate? Driving innovation through connected insights

The real power of data is clear when previously isolated datasets come together. We often see organisations come to us with a small, specific project in mind, like automating a manual finance report or building a dashboard. But it’s when they see the results, see the time savings, and see what’s possible across the organisation that they’re keen to rethink their data altogether.

It’s the holistic approach that can be transformative, by connecting data across functions, finance, sales, operations and beyond, organisations can move from isolated snapshots to a complete view end-to-end. That’s when you start spotting patterns, trends and customer behaviours you couldn’t see before.

One of our retail customers totally transformed the way their team worked, once they saw the power locked away in their data. We worked with them to consolidate their data into a central repository that not only improved internal reporting but allowed them to set up automated integrations with third-party platforms like eBay. This took previously manual, slow and error-prone processes and created a smooth workflow so their team could focus on the priorities that moved the business forward.

Another customer in property management took a similar approach, streamlining fault reporting and maintenance workflows and removing the need for manual inputs in the middle. As a result, their team spends less time moving data from one place to another and their tenants see their maintenance requests fulfilled quicker than ever.

With a strong data foundation for AI, businesses can evolve from basic reporting to predictive analytics, forecasting and even real-time insights. This transforms the way teams approach goal-setting, financial forecasting and even industry-specific use cases like the layout of retail spaces.

What changes are you seeing customers make based on their data? Insights into action

Once businesses see the power of the data that’s been under their nose, the focus shifts from understanding what has happened, to what will happen. Historically, forecasting has been based on vast spreadsheets and a healthy dose of gut-feeling. But, when you’ve got years of high-quality data you can start applying predictive models and advanced analytics to support those decisions.

Data doesn’t replace human judgement and insight, it enhances it. If the data supports your vision it strengthens your case for the way forward. If it contradicts it, you can investigate why and adjust accordingly. The blend of human expertise and nuance, with data-driven strategic planning gives organisations the ability to process mass amounts of data without losing that human touch.

How should businesses approach their data if they want to get the most out of it?

The place to start is with your Data and AI strategy, it’s the foundation that underpins your data and AI aspirations. Without a clearly defined strategy, businesses risk taking a piecemeal, reactive approach that fails to deliver long-term value and potentially causes problems further down the line. It might seem like an optional step, and businesses can be keen to get stuck in without one, but a data strategy can be the difference between a project that pushes you forward and one that falls flat.

A data strategy should map your organisation’s entire data footprint and prioritise which data sources are the most important to your organisation’s success. A data strategy ties into the wider technology strategy too, not only helping you understand what data you have and where, but how it can integrate with the rest of your tech stack and support every line of business.

It’s also vital to include stakeholders from across the organisation early on. From sales and procurement to HR and operations, they all have valuable perspectives to ensure your data strategy and use cases are impactful across your organisation. And remember, a data and AI strategy is a dynamic living thing, and needs to remain agile. The tech moves quickly and your strategy needs to evolve constantly to keep pace.