MES: Make or Buy? A strategic decision in the age of No-code, Cloud and AI

A Manufacturing Execution System is critical for monitoring and optimizing production processes, increasing efficiency, and ensuring quality. It bridges the gap between the enterprise level (ERP) and the manufacturing level (automation).

The key question for many companies remains: Should we develop an MES ourselves (“Make”) or purchase a standard solution available on the market (“Buy”)?

Classic criteria for the Make or Buy decision

Historically, the criteria for buying versus developing in-house were primarily assessed from the perspective of the IT department and the availability of internal resources:

• Cost: Comparison of development and licensing costs, as well as implementation and maintenance expenses
• Time: Duration of in-house development vs. implementation time of a standard solution
• Adaptability: How well can the solution be tailored to specific company processes?
• Know-how and Resources: Availability of internal developers, subject matter experts, and project management capacity
• Risk: Development risk in in-house projects (errors, delays) vs. vendor dependency when purchasing externally
• Scalability: How flexible is the solution in meeting growing demands?
• Competitive Advantage: Can an in-house development create a real competitive edge through unique features?

Digital transformation has lead to many innovations in the area of MES solutions. This is where the “new” factors come into play, significantly influencing the make-or-buy decision.

1. Focus on Citizen Development:

a) In the Past: Software development was the exclusive domain of professional programmers. Business departments depended on IT, often leading to long wait times and misunderstandings.

b) Today: With no-code/low-code platforms, employees with specific know-how in different departments – so-called “Citizen Developers” – can create their own applications or process automations. They understand operational requirements best and can quickly develop prototypes or adapt and expand specific MES functionalities. This significantly reduces the “requirement backlog” for IT and accelerates digitalization.

For an MES, this means: Smaller, specific modules or dashboards can be created by users themselves to close gaps in a standard solution or to map special processes.

2. No-code- and Low-code options

a) In the Past: In-house development meant extensive programming from scratch, often in complex languages, with high maintenance requirements and significant demands on organizational knowledge management.

b) Today: No-code platforms offer visual development environments with drag-and-drop functionality and pre-built components. This enables Citizen Developers to create fully functional applications without writing a single line of code.

For an MES, this means that specific process steps, data entry forms, or reports tailored precisely to a company’s needs can be implemented quickly and cost-effectively – even if the core functionality is purchased. This makes a hybrid strategy particularly attractive.

3. The cloud as an enabler:

a) In the Past: MES systems were often installed on-premise, requiring significant investments in hardware, infrastructure, and maintenance.

b) Today: Cloud-based MES solutions offer a high degree of flexibility, scalability, and reduced operating costs. Implementation is faster, as there is no need to build a dedicated server infrastructure. In addition, cloud solutions often provide better integration with other systems and make remote access easier.

For the make decision, the cloud means that infrastructure is no longer a limiting factor – custom-built solutions can now run in the cloud. For the buy decision, companies benefit from Software-as-a-Service (SaaS) models, which include updates and maintenance provided by the vendor.

4. Artifical Intelligence (AI) opens up new possibilities:

a) In the Past: Data analysis in MES was often reactive and based on historical data. Predictive maintenance or process optimization required extensive programming and specialized knowledge.

b) Today: AI enables predictive analytics, automatic error detection, optimization of production workflows, and even autonomous decision-making. AI-powered features can significantly enhance off-the-shelf MES systems.

For the make decision, AI frameworks and services in the cloud offer the opportunity to develop custom AI models and integrate them into in-house solutions without having to reinvent the wheel.

In today’s landscape, the strict separation between “make” and “buy” is often outdated. Many companies instead pursue a hybrid approach:

Buy the Core: Proven standard solutions are purchased for the essential, standardized MES functionalities. This ensures fast implementation and access to best practices.

Make the Difference: Specific, company-specific requirements that create a competitive advantage or reflect unique processes can then be developed using no-code/low-code platforms – either by Citizen Developers or specialized IT teams – and seamlessly integrated into the purchased system. Dashboards for specific KPIs, interfaces to niche systems, or custom workflows are common examples.

AI for Optimization: Regardless of whether you make or buy, integrating AI for data analysis, forecasting, and process optimization should play a central role. Whether this is achieved through built-in AI features from the MES provider or through in-house developments depends on the complexity and specific goals.

The strategic make-or-buy decision for an MES is more complex and at the same time more flexible than ever before. No-code systems like manubes make the targeted “make” approach easier than ever.

But even as a hybrid addition, they unlock potential through greater transparency and flexible extensions.