Is the Future of MES in the Cloud? Seven Global Trends Transforming Manufacturing Operations
Manufacturers today face shorter lead times, changing customer requirements, labour shortages, cost pressure and increasingly demanding traceability requirements — all at the same time. Responding quickly to these challenges is difficult when information is scattered across spreadsheets, paper-based production reports and summaries prepared only after the event.
This is why MES, or Manufacturing Execution Systems, are moving increasingly into focus. An MES connects the production activities planned in an ERP system with what is actually happening on the shop floor. It can show the current status of each production order, which machines are running or idle, how much has been completed, where scrap or delays have occurred and how production KPIs are developing.
However, the change is not limited to MES functionality. The way manufacturers use software is also evolving worldwide. Alongside large, on-premises systems requiring lengthy implementation projects, cloud-based, modular and subscription-based SaaS solutions are gaining an increasingly important role.
Digital manufacturing is moving beyond isolated pilot projects
In June 2026, the World Economic Forum’s Global Lighthouse Network had grown to 238 manufacturing and supply chain sites. These are facilities that do more than experiment with individual technologies: they deploy digital solutions at operational scale and demonstrate measurable business results.
The latest international experience highlights three major developments:
- artificial intelligence is moving from isolated pilots into day-to-day operations;
- collaboration between people and technology is becoming increasingly important;
- sustainability is becoming an operational driver of cost reduction and competitiveness.
Manufacturers are therefore no longer digitalising individual processes in isolation. The objective is to create a connected operating system in which production information reaches the people who need to act on it — quickly and in context.
1. SaaS MES lowers the barrier to manufacturing digitalisation
Under the SaaS — Software as a Service — model, a company uses an application as a service instead of purchasing a perpetual software licence and building its own server infrastructure. The system is typically accessible through a web browser, while much of the infrastructure operation, maintenance and updating is handled by the service provider.
This is particularly relevant to small and medium-sized manufacturers. A conventional MES project may require investment not only in software but also in servers, databases, system administration, version upgrades and specialist IT resources. A SaaS MES can instead be introduced with a more predictable monthly fee and a phased rollout.
The potential advantages of the cloud model include:
- lower initial investment;
- faster system launch;
- automatic or centrally managed updates;
- simpler support for multiple sites and devices;
- flexible scalability;
- remote access to current production information.
SaaS, however, means more than moving a previously on-premises application to a remote server. Key characteristics of a genuine cloud service include on-demand access, shared and elastically scalable infrastructure, and measurable service usage.
2. Modular solutions are replacing monolithic systems
Many companies postpone introducing MES because they imagine a multi-year project intended to cover every process across an entire factory from day one. The international direction, however, is shifting towards modular architectures that can be deployed and expanded incrementally.
The 2025 update to the international ISA-95 standard also highlights the growing importance of modular, data-centric architectures that can operate on premises, in the cloud or in hybrid environments. Standardised interfaces and shared data definitions help ERP, MES, machine data collection, warehouse management and other applications work together instead of remaining disconnected islands.
A manufacturing SME can therefore begin by addressing one clearly defined problem, such as:
- production planning and resource scheduling;
- digital work instructions and documentation;
- shop-floor production reporting;
- recording machine downtime and faults;
- real-time tracking of production orders;
- OEE and KPI reporting.
Additional functions and integrations can then be introduced based on practical experience and measurable needs.
3. Real-time information is becoming more valuable than retrospective reporting
Traditional production reports often explain what happened yesterday, last week or during the previous month. They are useful for analysis, but frequently arrive too late to support timely intervention.
The purpose of a modern MES is to make the status of production visible when events occur. If an operation has not started, a machine has failed, actual production time exceeds the plan or scrap levels begin to increase, managers should not have to wait for an end-of-shift summary to discover the problem.
Real-time production information can provide fast answers to questions such as:
- What is currently being produced on the shop floor?
- Which production order is falling behind schedule?
- Which machine or resource is idle, and why?
- How do planned and actual production times compare?
- Where are bottlenecks or capacity shortages developing?
- How are performance, downtime and OEE changing?
The value therefore lies not in the volume of data itself, but in whether the information enables people to make better decisions in time.
4. Structured manufacturing data is the foundation for artificial intelligence
Artificial intelligence is spreading rapidly in manufacturing. It can support quality inspection, predictive maintenance, production planning, energy optimisation and anomaly detection. International examples from the World Economic Forum show that AI is increasingly becoming embedded in operations rather than remaining a separate innovation project.
However, AI cannot provide reliable decision support using incomplete, disorganised or delayed data. If a company cannot determine exactly when an operation started and ended, why a machine stopped, how much scrap was produced or which resource performed the task, an algorithm will not have an adequate basis for analysis either.
From this perspective, MES is a foundation for manufacturing AI. It collects and contextualises production data in a consistent structure on which more advanced analytics, forecasts and optimisation tools can later be built.
5. The future will often combine cloud and edge rather than rely on cloud alone
The cloud offers significant advantages, but manufacturing also includes tasks that may require rapid local responses or continuity independent of an internet connection. Examples include certain types of machine data collection, control-system communication and operational safety functions.
This is why cooperation between cloud services and edge computing — local data processing close to the machines — is becoming an important international model. A local component can perform time-critical data collection or temporary storage, while the cloud provides a central database, analytics, multi-site access and scalability.
The right question is therefore not necessarily “cloud or on-premises?” Instead, manufacturers should determine where each function is best placed based on speed, availability, cybersecurity and cost.
6. Industry 5.0 calls for more human-centric manufacturing
The European Commission’s Industry 5.0 concept looks beyond automation solely as a way to improve efficiency. Its three core pillars are human-centricity, sustainability and resilience.
This also changes the expectations placed on MES solutions. A shop-floor application works well when it reduces the operator’s administrative burden rather than adding to it. Operators should be able to see quickly what needs to be produced, in what sequence and according to which documentation. They should also be able to report work, quantities and faults through a small number of clear steps.
Characteristics of a human-centric MES may include:
- a simple interface tailored to each role;
- clear digital work instructions;
- less manual copying and re-entry of data;
- rapid fault reporting;
- multilingual operation;
- a design that supports employees rather than merely monitoring them.
Technology creates value only when people actually use it and the resulting data is reliable.
7. Production data is becoming the basis of sustainability and traceability
Manufacturers face a growing number of customer, regulatory and supply chain requirements relating to energy use, material losses, origin, quality and evidence of production conditions.
The European Union’s strategy for common data spaces identifies manufacturing as a priority area. The goal is to establish secure and governed environments in which companies retain control over the data they generate while being able to use and share selected data with business partners and service providers.
Before a company can participate effectively in such an environment, it must first have structured and retrievable data within its own operation. An MES can help connect a production order with the materials consumed, operations performed, machines used, employee feedback, processing times, faults and quality information.
MES may therefore become more than a tool for production management. It can form part of the foundation for a manufacturer’s industrial data assets and reliable end-to-end traceability.
What does this mean for manufacturing SMEs?
Under the traditional industrial software model, smaller manufacturers often regarded MES implementation as too large, too expensive and too risky. The SaaS model changes this in several ways.
It is not always necessary to digitalise every function and workstation at the same time. A better starting point is often an area in which missing or delayed information already causes a measurable problem. This could be frequent rescheduling, paper-based production reporting, unknown causes of downtime, document version control or delays in management information.
A clearly defined initial scope has several advantages:
- business value can be verified sooner;
- financial and organisational risk is reduced;
- employees can adapt to the new way of working gradually;
- the next development step can be selected using real operational experience.
Digitalisation can therefore become a controlled process of continuous development rather than a one-off project that attempts to change everything at once.
What should manufacturers consider when selecting a SaaS MES?
Not every system described as cloud-based offers the same capabilities. Companies should consider at least the following questions during selection:
- Is the system genuinely browser-based, or does it require special local installation?
- How quickly can the first working process be launched?
- Can the company begin with a small number of users and a limited functional scope?
- How can modules, employee access and connected machines be expanded?
- Which ERP and third-party integration options are available?
- How are backups, user permissions and software updates handled?
- What happens if the internet connection is interrupted?
- Can company data be exported in standard, reusable formats?
- Does the system support the languages and devices used by employees?
- Which services are included in the subscription fee?
The right solution is not necessarily the one with the longest list of features. It is the one that can address the company’s current problem quickly and then expand alongside the operation.
What should manufacturers consider when selecting a SaaS MES?
An MES cannot make manufacturing processes orderly on its own. If master data, responsibilities, operation sequences or reporting rules are unclear, software may simply make the problem visible more quickly.
Successful implementation therefore requires operational decisions as well as technology:
- Which data genuinely needs to be recorded?
- Who is responsible for reporting it, and when?
- Which KPIs should trigger intervention?
- Which system is the authoritative source for each type of master data?
- What should be the first measurable improvement objective?
Technology delivers results when it supports a clearer and better-defined process.
What should manufacturers consider when selecting a SaaS MES?
The future of MES will not be defined by a single technology. Cloud services, modular architectures, standardised integration, real-time data, artificial intelligence, human-centric usability and sustainability requirements are transforming manufacturing operations together.
SaaS MES creates a particularly important opportunity for SMEs: modern manufacturing operations management can be introduced faster, gradually and with a lower initial risk. A company does not need to build an entire “smart factory” immediately. The first step may simply be gaining a real-time view of production and making decisions based on consistent, reliable data.
Discover how Omega MES works
Omega MES is a cloud-based, modular manufacturing operations solution. It supports production planning and resource scheduling, digital manufacturing documentation, shop-floor reporting, machine fault and downtime recording, as well as real-time dashboards and KPIs.
If you would like to explore how Omega MES could be applied to your manufacturing processes, request a personalised online demonstration or try the system with a 30-day free trial.
