At a glance
- Data volume isn't the problem - knowing what to look for is
- Fresh perspectives surface opportunities that experienced teams overlook
- AI and analytics only deliver value when connected to the right questions
Featuring Max Rogers
Global Strategic Solution Architect
Two interns walked into a business to analyse data that had already been reviewed by experienced teams, and within a short period of time, they uncovered a revenue opportunity in a part of the operation that had long been treated as a necessary cost.
That part of the business had always been managed with the expectation that it would break even at best. It was understood, accounted for, and accepted as part of the operating model. What changed was not the data itself, but the way it was approached. By looking at the same information through a different lens, the interns identified levers that could be adjusted to generate profit, transforming an overlooked function into a contributor to the bottom line.
For Max Rogers, Global Strategic Solution Architect at COSOL, watching two interns look at volumes of his customer’s data with fresh eyes reflected a broader pattern across asset-intensive industries. His career spans both mining and technology, combining operational experience with a focus on how data and systems can be applied to solve real-world problems. That same approach carried through when COSOL acquired his business, with the alignment in how both viewed data, not as something to accumulate, but as something to apply, making the integration a seamless continuation rather than a shift in direction.
According to Max, organisations are surrounded by vast volumes of data, yet the value of that data is determined not by how much is collected, but by how clearly the organisation understands what it is trying to uncover.
Data has outpaced the ability to use it
Over the past decade, the amount of data generated by equipment, systems, and operations has grown exponentially. Modern assets produce continuous streams of information, from performance metrics and condition monitoring to environmental and operational inputs, creating a level of visibility that was not possible in earlier operating environments.
Sensors capture equipment behaviour in real time, enterprise systems track work and costs across the asset lifecycle, and auxiliary systems add further layers of operational detail.
The challenge, therefore, is not access to data, but the ability to translate it into decisions that improve performance.
The gap between information and insight
Within many organisations, data strategies have focused on collection, storage, and reporting, with significant investment directed toward building data infrastructure and ensuring information is available across the business. While these capabilities are essential, they do not, on their own, create value.
Value emerges when data is connected to a question that matters to the operation, and when the organisation has the capability to interpret what that data is revealing.
In practice, this is where many efforts stall. Data is collected because it can be, systems are implemented to manage it, and reports are generated to summarise it, but the link between data and decision-making remains underdeveloped. Teams may have access to dashboards and analytics tools, yet still rely on experience, intuition, or established routines when making operational decisions.
Without a clear understanding of what the organisation is trying to learn, data remains descriptive rather than instructive. It shows what is happening, but does not guide what should be done next.
The importance of asking the right questions
When those questions are clearly defined, data becomes a powerful input into decision-making. It can be used to forecast failures, optimise maintenance schedules, improve asset utilisation, and identify opportunities to reduce cost or increase throughput.
Without that clarity, data remains underutilised, regardless of how sophisticated the underlying systems may be.
Max’s real-world example of the interns - who were later hired with a full AI analytics team built around them - illustrates how perspective shapes the value extracted from data. Experienced teams had already analysed the same information, yet approached it within the boundaries of how the business had always been understood. The interns, unencumbered by those assumptions, explored the data more openly and identified an opportunity that had been consistently overlooked.
That dynamic is common in organisations where processes and interpretations have been built over time. Teams develop a deep understanding of how the business operates, but that understanding can also narrow the range of questions being asked. Data is interpreted through established frameworks, and insights are often confined to what fits within those frameworks.
“People tend to develop tunnel vision, especially in industries like mining and public transportation, where there’s a strong tendency to promote from within,” Max explains.
Introducing fresh perspectives expands that field of view. It brings exposure to different ways of analysing data, different operating models, and different assumptions about what is possible. When combined with deep operational knowledge, this creates the conditions for more meaningful insights.
Linking data to operational outcomes
Advancements in artificial intelligence and analytics have increased the ability to process large volumes of data and identify patterns that would be difficult for humans to detect manually. These technologies are increasingly being applied across asset-intensive industries, offering new ways to interpret complex datasets and generate predictive insights.
Max sees this as an important development, particularly given the scale of data now available.
At the same time, the effectiveness of these tools is shaped by how they are applied. Technology can identify correlations, trends, and anomalies, but it requires direction to ensure that the outputs are relevant to the organisation’s objectives.
The most valuable data initiatives are those that are directly connected to how the business operates. This means aligning data analysis with the decisions that teams need to make on a daily basis, whether that relates to maintenance planning, asset utilisation, cost management, or compliance.
When this alignment is achieved, the impact becomes tangible. Organisations are able to anticipate issues before they occur, allocate resources more effectively, and respond to changing conditions with greater precision. Data moves from being a background function to a central component of how performance is managed.
From data accumulation to decision clarity
As organisations continue to invest in digital capability, the volume of data available to them will continue to grow, but the presence of data alone does not change how a business performs. What changes performance is how that data is interpreted, prioritised, and applied within the context of day-to-day operations.
For many organisations, the challenge sits in the transition from visibility to action. Data can describe what is happening across assets, systems, and processes, but unless it is connected to a decision that someone is accountable for making, it remains disconnected from the operation itself.
Max frames this shift in practical terms.
This moves the conversation beyond reporting and into discovery. It requires organisations to move past using data to confirm what they already understand, and instead use it to challenge assumptions, surface inefficiencies, and identify opportunities that are not immediately visible.
This is where many data initiatives lose momentum. The infrastructure is in place, the data is available, and the tools are capable, but the organisation continues to operate within existing mental models. Data is interpreted through what is already known, rather than used to expand that understanding.
Max’s experience shows that value emerges when that pattern is broken, when data is used to explore rather than confirm.
About COSOL
COSOL is built on one belief: in asset-centric industries, reliability is everything. We’re a trusted, data-led asset management partner for organisations around the world who can’t afford to fail. And known for our deep expertise, dependable delivery, and ability to keep critical assets performing at their best.
The company recently celebrated 25 years in business, are Australian-owned and operated, and recognised as reliable partners by their clients across the globe.