There is a rapid change in manufacturing. What was once an industry that made heavy use of supervision, manual entries, and unique equipment has transformed into a highly connected, information-driven, and smart ecosystem. At the core of this digital revolution is the need to modernize manufacturing execution systems (MES) and SCADA platforms.
The traditional functionality of these systems has been operational monitoring, production control and process automation. But older versions of such systems present more of a challenge than an opportunity now - they do not facilitate innovation, reduce real-time insight, or prevent bigger digital transformation projects. app modernization.

With the adoption of Industry 4.0, artificial intelligence (AI), cloud computing, digital twins, and the Industrial Internet of Things (IIoT) in manufacturing, traditional MES and SCADA systems are no longer effective in supporting these changes.
It is at that point that app modernization comes into the picture, enabling businesses to upgrade to the next stage of on-premises, monolithic MES/SCADA to a flexible, scalable, secure and cloud-enabled connected environment.
This article discusses why legacy MES/SCADA migration is a priority, the role of app modernization, the financial and operational risks of aged systems, and how manufacturing businesses can strategically navigate this change.

Why are legacy MES/SCADA systems failing today’s manufacturing needs?

MES and SCADA systems, back in the day, were designed to fulfil requirements for production monitoring, measuring equipment, fault monitoring, and reporting. Nevertheless, they never intended to support the needs of the modern world, such as integrating AI, predictive analytics, global manufacturing visibility, cybersecurity, or flawless connectivity across supply chains.

Today, many manufacturers continue to use MES/SCADA platforms that are between 10 and 20 years old, and the upgrades are not consistent, with complicated customizations, and siloed data models. Such systems tend to be very reliant on human intervention, vendor lock-ins, custom-coded scripts and on particular engineers who are familiar with the old architecture.

Manual data entry is one of the major problems. According to a study by the Manufacturing Leadership Council, about 70% of manufacturers still manually collect production data, often via paper or spreadsheets.

This leads to time wastage, reporting that is prone to errors, time-consuming compliance management and poor performance insights. Plant-floor data silos compound the challenges of integrating plant-floor information with enterprise information systems such as ERP, PLM, SCM or predictive maintenance platforms.

Moreover, IIoT-enabled devices do not always support legacy MES/SCADA systems. To manufacturers wishing to be data-centric, this non-integration is constrained to the limits of automation, real-time intelligence, and predictive analytics processes.

The growing cost of downtime with legacy MES/SCADA

One of the most critical challenges associated with outdated MES/SCADA systems is unplanned downtime. Downtime used to be seen as an operational inconvenience, but now it is a financial, strategic, and reputation risk.

A survey by ABB found that unplanned outages cost industrial manufacturers around $125,000 per hour, with most companies facing at least one outage every month. A study in ISM Magazine further revealed that downtime eats up around 11% of annual revenues for large organizations, amounting to over $1.4 trillion globally.

Legacy MES/SCADA systems, due to ageing hardware dependencies, slow data processing, and poor fault detection, significantly increase downtime risks. They struggle to perform real-time diagnostics, automated alerts, and root-cause analysis, which are essential for predictive maintenance.

Consequently, failures are not realized until there is system break down. Modernization of apps will bring predictive maintenance powered by data, and will make MES/SCADA and AI-enabled monitoring tools, minimizing failures and downtime significantly.

Why modern MES and app modernization are business drivers

The manufacturing industry has already started moving toward modernized MES platforms. According to Strategic Market Research, the global MES market is valued at $15.2 billion in 2024 and is expected to reach $28.5 billion by 2030, growing at a 10.8% CAGR.

Improvements in the systems are not only related to the growth; it is a wider transformation to an intelligent manufacturing infrastructure. The manufacturers are now demanding MES and SCADA systems that would easily integrate with AI platforms, digital twins systems, cloud apps, ML-enabled quality management, ERP/SAP and real-time dashboards that would give full supply chain visibility.

Modernization of the apps can unlock this value through re-architecting MES/SCADA systems to be scaled, interoperable, cloud capable, and have data integrity.

What app modernization looks like for MES/SCADA

Modernization of apps does not simply refer to the software upgrade, but a transformation of monolithic, closed, vendor-reliant systems to contemporary, cloud-capable, modular platforms that enable flexibility, global integration, predictive services and sophisticated decision-making, which is data-driven.

Here is how app modernization transforms MES/SCADA landscapes:

From monolithic to modular microservices

Legacy MES is loosely integrated with SCADA, PLCs, reporting modules, databases and proprietary extensions. Modernization disintegrates these monoliths into microservice-based architectures so that individual components of the system, say quality management, batch processing, reporting or traceability, can be updated without impacting the rest of the system.

Cloud-enabled, edge-aware operations

A future-ready MES/SCADA architecture leverages hybrid cloud and edge computing. Edge computing guarantees continuous local functionality, equipment real-time control, and machine data acquisition, whereas cloud systems are used to analyse data, AI modelling, historical data, process optimisation, and cross-site analytics.

Data-centric manufacturing intelligence

The current MES/SCADA designs enable the real-time flow of contextual, time-stamped, and structured data between IoT sensors, ERP, MES, quality systems, and predictive maintenance platforms. This removes manual labour, brings visibility and enables autonomous decision making.

Better user experience (ux)

The contemporary MES/SCADA platforms offer convenient Dashboards, mobile access, and role-based visual platforms that significantly decrease training time and enable an operator to track QPIs, batches, asset health, and quality notifications comfortably.

The migration roadmap- From legacy to future-ready MES/SCADA

Legacy MES/SCADA migration involves a systematic migration process. It is not always an overnight transition; rather, it must be modernised in stages by strategy planning, data transfer, integration of equipment and selective replacement.

Phase 1: Assess the current MES/SCADA landscape

The first step is to sketch all the systems in connection, assess the present state of MES functionality, PLC connections, SCADA infrastructure, custom-written scripts, equipment compatibility, data flow, and variations across multiple sites. It is common to have several plants with different manufacturers having entirely different versions of MES, and thus inconsistent performance.

Phase 2: Build a business case

Leadership buy-in is crucial. Present the statistics that display the downtime losses, manual dependency of data, scrap rates and compliance fines to demonstrate the dangers of remaining with the old systems. It is simple to relate this story to the operations KPIs (OEE, MTTR, lead times, traceability accuracy) and make the funding approval easier.

Phase 3: Design an app modernization strategy

This move identifies the applications that will be rehosted, replatformed, refactored, or replaced. There are legacy systems which might be powerful and only need to be migrated to the cloud. Some might require total restructuring.

Common modernization strategies include:

• Rehosting MES reporting modules on cloud platforms such as Azure or AWS.
• Refactoring MES logic into modular microservices (batch management, quality tracking, order scheduling).
• Replacing outdated SCADA systems with newer platforms capable of IIoT integration.

Phase 4: Build a scalable integration framework

The new architecture should be linked with the ERP systems, SAP, predictive analytics engines, IoT data lakes, and manufacturing intelligence platforms. This is to ensure that MES/SCADA remains a central intelligence hub rather than a mere monitoring program.

Phase 5: Data migration and compliance alignment

It is one of the most complicated phases. Manufacturers have to determine what information they have to migrate, what to do to ensure transaction consistency, and what to save in terms of past production to meet the regulatory requirements. It should be a structured migration and thorough testing, lest operational disruption take place.

Phase 6: Pilot, optimise, and scale

Deploy one production line or plant to test system stability, to test user adoption, data accuracy, simulate downtime, and add predictive maintenance. When approved, scale to additional plants.

Phase 7: Change management and workforce training

Migration of MES/SCADA is not only a technical change, but it is also a people change. The operators, engineers, IT departments, quality inspectors and plant managers will have to become acquainted not only with a new interface but also with a new philosophy of operation, which will be data-driven, automation-based, and preoccupied with real-time analytics.

Final thoughts

The decade of manufacturing that follows will be characterized by information, connectivity, predictive business, and responsiveness. The old MES and SCADA systems developed in disconnected and mostly reactive systems cannot provide that future. Modernization of apps is important in changing these systems to enable real-time decision making, cloud-driven insights, IIoT connectivity, and AI-based optimisation.
The element of a gradual, well-coordinated migration strategy, focusing on business convergence, innovative structure, information integrity, and talent preparedness, will enable the manufacturers to seize control of their digital transformation process.
Modernization in MES/SCADA is not only associated with technology. It is regarding increasing the rates of productivity, enhancing visibility, minimizing downtime, ensuring compliance, and making production smarter, more scalable and resilient than ever.

In the digital era, the role of legacy app modernization in driving digital transformation cannot be overstated. VE3 can help with the expertise in app modernization solutions. Our innovative solutions encompass cloud migration, cybersecurity, DevOps, API management, and AI integration. We assess your unique needs, develop tailored modernization strategies, and oversee the transformation process. Our proven track record attests to our capacity to guide companies in rejuvenating their legacy systems into dynamic, agile assets.