The Explosion of Data

Data fascinates me. In 2024, 149 zettabytes of data were created, captured, copied, and consumed. The volume of data is expected to rise to 181 zettabytes by the end of 2025. To attempt to explain how insane this number is, I want you to think of your smartphone. The average smartphone holds 128 gigabytes of data. To store 181 zettabytes of data, you would need 1.4 trillion smartphones, close to 175 smartphones for every person on Earth.

It gets crazier when we consider that approximately 90% of the world’s data has been generated within the past two years, and the volume of data is doubling roughly every four years. This surge in data paints an interesting picture: the leaders of tomorrow aren’t those who have the most data. They’re the ones who know how to turn raw data into insights, action, and competitive advantage. Raw data without structure and strategy is like crude oil: valuable, but only if refined.

From Chaos to Clarity

I recently read an internal announcement regarding the creation of a new data analytics team in Ultimo . The positioning of this team caught my eye: “This dynamic team is set to revolutionize how we leverage data to drive informed decision-making and strategic initiatives within our organization.” I had the pleasure of sitting with Gerhard van de Krol , Team Manager of this new ensemble, and asked him about the inception of this team:

“We’ve been working on business intelligence for years, but all ad hoc, mostly for fun, but not the highest level of professionalism. Every team had someone dabbling, experimenting. We collected a lot of data, but it was messy, inconsistent, and often duplicative. Then you get the inevitable debates: what’s the truth?”

We collected a lot of data, but it was messy, inconsistent, and often duplicative. Then you get the inevitable debates: what’s the truth?

This is reflective of where most industrial maintenance organizations find themselves. They are often surrounded by data, but without the means, the approach or the manpower to extract, manage, and govern it. The inception of this new team signals the start of a new way of working with data. Gerhard agrees:

“We realized it was time to take a professional approach. There’s now a whole array of tools, like those from Microsoft , that make it possible to consolidate, clean, and centralize. Instead of everyone pulling their own datasets, we’re moving to a centralized data lake that feeds structured, reliable data out to departments. Daily refreshes, controlled access, clean models. It’s a complete shift in mindset.”

Ultimo’s journey toward a more centralized, consolidated data strategy is not unique; it is happening across industries. Data is no longer just a by-product of maintenance. It is the most strategic thing you have. The focus has shifted, and all eyes are now on how we can use data to build a strong foundation in order to propel innovation.

Data’s Big Impact

Data offers up huge potential, and huge value. I asked Gerhard what he thinks the biggest impact of data will be for the Company.

Gerhard put it sharply:

“What we haven’t even tapped yet is the ability to compare data across customers, of course in an anonymized, aggregated form. When you can look at 1,500 customers all doing asset management, you can start to benchmark, build models, and spot common patterns. Imagine knowing which assets are most prone to failure, or which industries face similar challenges. That’s hugely powerful.”

Imagine knowing which assets are most prone to failure, or which industries face similar challenges. That’s hugely powerful.

The opportunities extend far beyond enterprise software. This almost bolsters a universal truth: whether in healthcare, logistics, manufacturing or field service, organizations are moving from isolated datasets to networked insights. This allows for more accurate and insightful benchmarking, predictive modeling on a much larger scale, and the kind of market intelligence that was previously unattainable.

In Gerhard’s words:

“I’m sure companies with machine problems want to know: who else has this same machine? What’s the fix? Who can I call? That’s the kind of connection data can unlock.”

Data supports a move from reactive problem-solving to proactive collaboration. With great potential certainly comes great responsibility. That’s where data governance and data quality come in.

Why Governance & Data Quality Are Non-Negotiable

It’s important to note that data in and of itself will have a fairly limited impact and reach. Data quality and the way it’s governed are key when it comes to building trust. If people can’t trust the data, they will revert back to their own fragmented data sources, and the whole system crumbles. Gerhard agrees that governance is imperative:

“Who can access what? Who’s allowed to see which data? Right now, in many places, it’s not properly controlled because people can access too much. That’s why we’re putting in layered governance: from a bronze lakehouse to a gold lakehouse, using semantic models and setting up access through defined audiences. Whether you’re in sales or operations, you only see what’s relevant and authorized.”

It’s good to emphasize that addressing data quality is a shared responsibility. Everyone has a role to play in improving data quality.

Gerhard emphasized:

“We often build a page into Power BI reports showing which data is incomplete. End users can see what’s missing and help improve it. That’s a crucial step: mobilizing the user, showing them they have a role in improving data quality.”

They (the user) have a role in improving data quality.

What we can take away from this is that central control is not the same as central governance. Strong governance empowers users, and allows them to work within a structured, reliable system.

Looking Ahead: The Role of AI

No conversation on data is complete without a mention of AI. In many ways, looking at the future of data, and looking at what data analytics can bring to the table is very much a discussion on how we prepare for the future of AI. Gerhard seems to agree:

“AI is the obvious next step. I don’t think we’ve even seen the start of it yet. If you have clean, well-structured data, you can set up AI agents that act on it. Maybe in five years, you won’t even need to create a work order. The system will just handle it automatically.”

The role AI is set to play will be nothing short of impressive. Across industries, AI will allow organizations to harness their data to shift to predictive and prescriptive forms of maintenance, further eliminating costly downtime. Automated decision-making will start to find its way into every step of the supply chain and manufacturing process at large. Self-optimizing workflows across various business-critical processes will further enhance efficiency and propel productivity. But in order for this not-too-distant future to become a reality, you’d better handle your data with the utmost care.

“It all stands or falls with how clean, how neat, how readable your data is. Even the naming of columns: you need meaningful, consistent names. You need to treat your data with care.”

It all stands or falls with how clean, how neat, how readable your data is.

Personally, I’ve seen how organizations can transform once they stop treating data as an afterthought. You cannot automate what you do not understand. You cannot optimize what you do not measure. And you cannot lead, if your decisions are based on guesswork. Treat your data like you treat your assets, and invest in cleaning your data like you would cleaning your machines.

Those who recognize this, who invest equally in their data infrastructure, governance, and talent, will not just survive: they will lead us into the future.

The future belongs to the organizations that turn data into an engine for growth, innovation, and leadership. Make sure you are ready to lead the charge.

What is your opinion on the potential of data? How are you using data to make more confident decisions? I’d love to hear from you! Send me a message here or via berend.booms@ultimo.com