Cloud strategy for industry and logistics: Create control in a connected reality

Why is the cloud a prerequisite for industry and logistics?

AI, real-time analytics and interconnected production generate data volumes that traditional on-prem infrastructure is not built for. The cloud provides scalability, computing power and the ability to connect plants, warehouses and partners in a common data environment.

But it's not just about capacity. It's also a matter of pace. Predictive maintenance, dynamic route optimisation and automated quality controls require data to be processed and acted upon quickly. The cloud enables this in a way that local systems rarely can.

Hybrid solutions for industry and logistics

Most industrial companies already operate in hybrid environments, often without a strategic foundation. ERP may run on-prem, CRM in the cloud and IoT data on yet another platform. The result is a systems map that has grown randomly rather than being consciously designed. Hybrid solutions within industry and logistics are therefore often not an active choice, but a starting point that needs to be managed.

But how do you do that then? Developing infrastructure without stopping production requires a step-by-step approach.

• Start with a pilot in a defined process or facility.
• Run parallel operations where old and new coexist during the transition.
• Replace legacy step-by-step, prioritised based on business criticality and risk.
• Plan changes based on service windows, shift changes and production cycles
• Have a rollback plan in place if the implementation affects operations or safety.

The logistics industry's own cloud challenges

Many logistics players have come far with SaaS-based TMS and WMS, but control is lacking. Data resides with the provider and it is unclear who owns what. The ability to move or combine data is often limited.

Multi-partner environments make it especially complex. Data is shared between shipping companies, customs, terminals, and end customers. Your cloud architecture must support this flow reality, not just internal system integration but an entire ecosystem of data exchange.

Create control with data classification

Different data requires different protection. A production recipe and a sensor reading from the warehouse have completely different protection needs, but are handled in many organisations with the same logic. A simple classification model helps you distinguish between what requires strict access control on-premises and what can reside in the cloud or on the edge. The point is not where the data is stored, but that each data type is stored consciously, with the right protection in the right place.

Zero trust in the hybrid environment

Data classification determines what belongs where. The zero trust principle ensures that access reflects the protection needs. With "never trust, always verify" as the motto, zero trust becomes particularly valuable in a hybrid environment where the boundary between IT, OT and cloud is blurred. It means identity-based access, micro-segmentation and continuous verification regardless of where the user or system is located.

Cost control with FinOps

In data-intensive environments such as industry and logistics, cloud costs tend to spiral. With the right FinOps principles, you gain insight and control over costs without stifling innovation. The aim is not to save at all costs, but to know what you are paying for and why.

Avoid lock-in by building exit readiness

Production-near systems such as MES, ERP and IIoT platforms are often deeply integrated. Replacing a component can mean production stops, causing you to stay not because the solution works well but because it is too expensive to leave. In logistics, lock-in looks different but is just as strong. Platforms managing bookings, routes and customer relationships carry years of transport history, tariff structures and customer integrations.

Solid exit planning is crucial. All suppliers create some form of dependency; the question is how transparent and manageable they are. Build readiness on several levels:

• Map dependencies. Which systems and integrations are connected to which supplier? Where are the toughest lock-ins?

• Secure data portability. Can you export data in open formats? This should be a question already at tender, not something you discover on the day you need to move.
• Regulate the agreements. Data access, export formats, exit costs and supplier obligations at termination. What is not in the contract does not exist when it is needed.
• Ensure competence. Do you have your own capacity to carry out an exit, or do you need a partner with experience of both IT and OT who understands migration in mission-critical environments?
• Choose a partner who contributes to freedom of movement. A mature IT partner offers open APIs, builds integration layers that reduce direct dependencies and proactively regulates exit terms.
• Test before you need it. An exit plan that has never been tried is just a document. Verify that data export works and that you know how long a transition actually takes.