One of the biggest lessons from working with data is that having more information does not automatically mean having better insight. Data only creates value when it helps the business make a better decision, catch a problem while there is still time to do something about it and ensure the right information reaches the people who can act.
For a long time, conversations around data were focused on scale. Businesses invested in new platforms with more sophisticated analytics capabilities and more ways of capturing information. The assumption was that if data helps businesses make better decisions, then collecting more of it should create more value. But the reality is that it is not quite that simple.
The challenge for organisations now is not just how much data they have, but whether they understand what data matters, whether they can trust it and whether it is structured in a way that allows people and technology to use it effectively.
That question has become even more important with the rise of artificial intelligence (AI). There is understandably a lot of excitement around AI and the speed at which models are developing is impressive. There are huge opportunities for businesses to automate processes, improve customer experiences and make better decisions but one thing that gets lost in the conversation is that AI does not remove the need for strong data foundations. It makes them more important.
Data the differentiator
As AI models become more powerful and accessible, the technology itself may become less of a differentiator. The biggest difference will come from the quality of the data and context provided to those models. Businesses may have access to similar AI capabilities, but the quality and relevance of the data supporting them could produce very different outcomes.
The technology landscape is changing quickly, but the underlying principles have not changed. Businesses still need reliable information, clear processes and the right infrastructure in place if they want technology to deliver meaningful outcomes.
This is something we think about a lot at HSS ProService Marketplace. We have built a digital marketplace that brings together customers, suppliers, products and services to make access to essential tools, equipment, fuel, training and building materials simpler and smarter. The marketplace combines local and national supplier reach with digital procurement and trusted service in one connected ecosystem.
In a marketplace environment, data is what helps create better connections. Customers need to find the right products and services quickly, and suppliers need visibility of demand and performance. The business needs to understand where the experience is working well and where improvements can be made. The value does not come from collecting information for the sake of it, it comes from having information that helps answer important business questions.
That is where the role of data has changed. Data is no longer just something that sits behind the business, used to produce reports or explain what happened after an event. It is becoming part of how organisations decide what to do next.
Data to help understanding
At HSS ProService Marketplace, we use data from different parts of the business to better understand customer behaviour, improve experiences and support decision-making. This includes customer interaction data, first-party website behaviour and other business information that helps us understand how customers engage with the marketplace.
A good example of this is customer experience. In a marketplace, a customer’s experience is rarely determined by one single interaction. It can be influenced by many different factors, including product availability, supplier performance, delivery expectations and the overall journey they have with the business. The challenge is identifying those signals early enough to act.
Customer experience inputs
We have been developing ways to bring together different indicators to understand where customers may be experiencing problems. This could include things such as refund requests, missed delivery expectations or changes in supplier performance.
The objective is not simply to measure what has already happened, but to help teams understand where intervention may be needed. The same applies to suppliers. A marketplace relies on a strong relationship between customers and the supply network. Understanding supplier performance is therefore important because it directly affects the experience customers receive. We have been developing performance measures to better understand how suppliers are operating and how this impacts customer outcomes.
These examples highlight something important about data strategy, that the goal is not complexity, it’s clarity.
Good AI takes time
One of the risks businesses face in the AI era is assuming that more information will automatically create better intelligence. In reality, adding more sources, systems and data points can create additional complexity if the information is not consistent or understood properly. Good data leadership requires judgement and it means knowing which information is useful, which information is reliable and where investment will have the biggest impact.
Sometimes the most important decision is not what additional data to collect, but what information the business genuinely needs to make better decisions. This becomes even more important when AI is introduced.
AI models are extremely powerful at processing information and identifying patterns, but they still depend on the quality of the data they are given. If the underlying information is incomplete, inaccurate or poorly structured, the output will reflect those weaknesses.
That is why implementing AI properly takes time. It is not simply about adding a new tool on top of existing systems. Businesses need the right data infrastructure to support it. Our focus is on using technology to simplify a complex industry. The marketplace model is about creating a more connected experience.
AI will continue to evolve, and businesses should absolutely explore where it can create value. But the organisations that benefit most will be those that have taken the time to understand their data first. The biggest opportunity is not simply having access to more information or more advanced technology. It is knowing what information matters, trusting the data behind decisions and building the foundations that allow new technology to work properly. Before businesses ask AI to do more, they need to make sure their data is ready to support it.
Immy Ullah is head of data & analytics at HSS ProService Marketplace.
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