Jeroen Coussement on , updated
Open access to real-time plant data is raising productivity, cutting waste and lifting engagement. Here’s how data democracy works in production, and how modern data historians help scale these benefits sustainably.
Your factory is drowning in data. Machines, sensors, processes, they all talk, all the time. But when something goes sideways, people still end up guessing.
You know the drill: something’s off in production. Everyone feels it. But no one sees it. And by the time you get to the bottom of it you’re days later as you have to ask the insights to the data team. Once you get the insights your best process engineer is on holiday and you’re still stuck.
The root cause? Your data exists somewhere, but it remains trapped in static reports, scattered across production systems, or locked away behind specialist access. By the time someone finally gets the answer, the moment to act has already passed.
Jeroen Coussement, Factry’s CEO, sees it happening all the time: “Operators or line managers notice an anomaly or quality issue. They have a hunch about what’s causing it and want to investigate. But first, they must file a ticket with IT and then wait three weeks. Eventually, they stop trying. It slows the whole organisation down.”
At the opposite end is the concept of data democracy: giving employees the freedom and tools to explore data, spot inefficiencies, and take immediate action. It shifts away from centralised data control, to a model where data becomes part of everyone’s job and responsibility. The goal is to empower employees at every level to make informed, data-driven decisions.
Imagine this:
But simply flooding people with raw data won’t cut it. To be genuinely useful, information must be aggregated, easy to interpret, and tailored to each user’s needs. Operators require a quick overview of today’s critical parameters. Line managers track issues and patterns across shifts. Engineers need in-depth analyses without Excel headaches. Only then can data democracy really work.
Democratising data remains a challenge for many manufacturers. Yet the urgency is rising: production teams need to react faster, manage tougher KPIs, and meet stricter sustainability targets, while margins keep getting thinner.
On top of that, more non-technical roles demand to access and analyse plant data. This reflects a broader industry shift, says David Ariens, industrial data strategist and co-founder of IT/OT Insider, whom we interviewed at Hannover Messe 2025.
Ten years ago, IT/OT convergence was all about infrastructure. Connecting systems, securing networks. Today’s challenge is data convergence. Not just as a technical issue, but as a business strategy. It requires operations, IT and data teams to collaborate closely toward a shared goal. This also changes who needs access to data, and how easy that access should be.
David Ariens
Co-Founder The IT/OT Insider
Manufacturers must shift their mindset radically, from systems to users, argues David Ariens: “Empower everyone in your organisation to become a citizen data scientist. A technician, quality manager or process engineer should be able to act on data without relying on a data team. Stitching SAP, MES, and quality data together in Excel shouldn’t be their job. If that is what it takes, it won’t happen.”
To turn raw production data into useful insights, you need a data historian. They collect, store and structure data from equipment, sensors and production lines, making this information accessible for analysis and decision-making.
But as demand for accessible data rises, many factories still run on legacy historians such as AVEVA Pi or GE Proficy. While reliable at capturing data, these systems lack the scalability, flexibility and ease of use that are required these days. Steep licences restrict access, complex interfaces demand specialists, and anyone outside engineering needing data ends up exporting spreadsheets, or giving up altogether.
Modern and open data historians solve exactly that. They capture data from PLCs, SCADA, and IoT devices, structure it, enrich it with operational context (like batch events, shifts or downtime), and deliver it through intuitive, browser-based dashboards. Employees can now easily access data directly and independently. This eliminates restrictive licences and IT bottlenecks, and fundamentally shifts the mentality within teams – empowering them to start new data-driven initiatives independently, taking ownership of their processes and driving continuous, data-driven improvements across operations.
The Capgemini Research Institute found in its 2025 ‘Sustainable Business Value’ report that manufacturers cut energy, water and waste by 8 to 20% within two years by integrating real-time production data into day-to-day decisions. The World Economic Forum’s 2024 Lighthouse plants show the same pattern at scale: on average, labour productivity rises 50%, energy use falls 22%, and scrap drops 55% when end-to-end data visibility is in place.
Our CEO Jeroen Coussement isn’t surprised: “As soon as you give people the tools, human curiosity kicks in, and that’s where the real value starts. We’ve seen businesses save substantial money through improvements they hadn’t even originally targeted – savings from energy, from water, from product overfilling, from machine stops – just because teams had access to data and spotted opportunities on their own.”
At Agristo, process engineers noticed a recurring inconsistency in product texture during one of the process steps. Using Factry Historian, they could quickly filter the relevant temperature tags, review the trends across shifts and find the root cause: a temperature deviation in one specific line setup. With that context, they could adjust the process, stabilise quality, and resolve the issue.
The whole cycle from observation to fix took less than a shift.
At one AGC Glass Europe site, employees uncovered a hidden energy leak in a washing unit. The system was using far more water than expected – something no one had noticed before because it wasn’t being measured. Heating that excess water also drove up electricity use. With the data now visible through Factry Historian, the team quickly resolved the issue, driving significant ROI.
Agristo and AGC didn’t map out a proof of concept. The ROI didn’t come from AI models or advanced analytics. It just came from enabling people to ask their own questions, test their own ideas and act on the results. Curiosity became a driver of continuous improvement. What started as one person solving one problem became something others could repeat across the enterprise.
When teams can see what’s happening and act quickly, their motivation increases significantly. “When people pull real-time data without filing a ticket, changes are visible almost immediately,” says Jeroen Coussement. “They fix one small issue, share findings with the night crew, and momentum builds. It’s just motivating to see the numbers move because of your own actions.”
Research agrees. A 2019 meta-study in the Journal of Applied Psychology found that autonomy is a strong predictor of motivation, job satisfaction and performance. More recently, research from MIT Sloan Management Review showed that teams with open data access take more initiative and act faster. In other words: when teams can work with the data, they’ll take more responsibility for what they see.
Implementing data democracy ultimately impacts culture. It fundamentally changes how people use data in daily operations. In companies where frictionless data access becomes the norm, job roles evolve and expectations shift. Data proficiency becomes part of daily operations, and often, part of new job descriptions.
Jeroen Coussement
Founder & CEO at Factry
Launching one successful improvement initiative is fairly straightforward, but replicating it effectively across multiple sites often proves challenging.
The critical ingredient for scaling successfully is a reusable data infrastructure: standardised naming, consistent event contexts, and uniform user interfaces across plants. This structured backbone allows rapid reuse of insights without rebuilding from scratch every time. A fix on line 3 becomes a template for line 30, and a dashboard in plant A works unedited at plant B.
Without it, each new use-case turns into a one-off: custom queries, manual exports, separate dashboards. It’s a model that burns time and resources. “Most companies are now realising that without a strong data foundation, nothing scales,” says David Ariens. “You can’t skip that step.”
Digital manufacturing expert Willem Van Lammeren, fellow co-founder of IT/OT Insider, and also interviewed by us during Hannover Messe 2025, advises a balanced approach: “Some companies launch ambitious grand plans, others get stuck with tiny pilots. Neither method works. My advice: start small but think big. Evaluate ROI not only on the pilot itself, but on the impact once you roll it out across all plants.”
Once your data foundation is in place, teams across departments can not only work from the same reliable input. Each improvement builds on the previous one, with a lower marginal cost every time. And as more teams see and act on data, the gains no longer stay local: they scale up, multiply, and drive systemic improvements across the enterprise.
Willem Van Lammeren
Co-Founder The IT/OT Insider
Factry Historian gives data democracy a practical backbone, replacing scattered tools with one aggregated, context-rich data layer.
The platform collects high-resolution data from control systems, and adds built-in logic that makes it usable for any role, from machine operators to line managers and process engineers. That includes detecting batch events, contextualising machine stops or structuring data around assets and processes.
Teams can explore trends, investigate issues and compare performance without technical knowledge, without switching tools, or having to start from scratch with each question. Everyone works from the same reliable foundation, whether they’re solving line or quality issues, comparing OEE or setting up an AI project.
Instant visibility into plant operations transforms decision-making across every organisational level. Operators or engineers who monitor real-time machine data can catch deviations before they escalate. Production managers can spot bottlenecks from their chairs. Leadership teams don’t have to wait for weekly reports: they can track KPIs across sites and adjust their strategy as needed.
The impact of data democracy goes far beyond efficiency gains. It reshapes how people work, make decisions and collaborate across functions. But these cultural and operational shifts only happen when teams can rely on the same structured data, every day.
Our advice? Don’t settle for siloed systems or static reports. Give your people one shared source of truth they can trust, question and act on. That’s how you turn better data into better performance.
Too many factories still run on historians that can’t scale, connect or share. That slows everything down, from reporting and root cause analysis to AI and enterprise integration. Our CEO Jeroen Coussement breaks down what modern manufacturers should expect from a historian today: structured data, built-in context, real-time access, and zero friction between OT and IT.
Developments in the process industry in 2025 will be marked not only by technology, but also by reporting, transparency and, as usual, the relentless quest for bigger margins and efficiency. Companies that jump on the bandwagon will not only take a big step towards compliance but, in their drive for innovation and digitalisation, will also open the gate for competitive advantage and employee engagement in the workplace.
The new release of Factry Historian (v7.2) puts usability front and centre. We’ve added features to convert time-series to length-based data, which is especially relevant to industries that produce products by the meter. Furthermore, we introduce customizable MQTT payload formatting for data egress, Parquet file enhancements, and a new event detection method.
