In recent years, logistics automation has been widely adopted by manufacturing companies. According to the Logistics Automation Market (2024–2029) report by MarketsandMarkets, the sector will continue to grow at a sustained pace, driven by increasing volumes, cost pressures, and the need to improve service levels.
The Italian context confirms this trend as well: the “Gino Marchet” Contract Logistics Observatory of the Politecnico di Milano highlights how more and more companies are investing in automation and digitalization to make warehouses more efficient, flexible, and resilient.
Most organizations are not starting from scratch, warehouses already exist, with established layouts, processes, and systems. In this scenario, an important shift is emerging: as highlighted by Interact Analysis, investments are gradually moving from building new facilities (greenfield) to optimizing existing assets (brownfield). This shift favors the adoption of micro-automation and modular solutions, which are faster to implement and more economically sustainable.
The challenge, therefore, lies in understanding which technologies to choose and, above all, how to avoid investments that are not aligned with real processes. Today, the problem is precisely the abundance of available solutions: different technologies, often very valid, that generate value only if applied in the right context.
TakeawaysIn a brownfield warehouse, the most advanced technology does not win—the most suitable one for real constraints does. Space, layout, and existing flows are the true drivers of choice.
Warehouse automation technologies are not interchangeable. Each solution (AMR, goods-to-person, assisted picking, sorter) solves a specific problem.
Density and productivity are not the same. Increasing storage capacity does not automatically improve operational performance.
Micro-automation is often the most effective choice in brownfield environments. Modular solutions improve individual processes without disrupting the warehouse.
AMRs enable flexibility, but only if flows are well designed. Without a clear operating logic, they risk replicating existing inefficiencies.
Goods-to-person systems increase productivity and density, but require adequate volumes.
Real value comes from integration between technologies. Without orchestration between WMS and automation, inefficiencies arise.
The most common mistake is starting from technology instead of the process. Automation works only if designed around real flows.
Warehouse automation today offers a very wide range of options: mobile robots, goods-to-person systems, sorters, assisted picking technologies, vertical systems, and computer vision solutions.
However, this decision goes far beyond technology, as it involves processes, people, structural constraints, and business objectives. For this reason, it is also one of the most complex decisions to tackle.
Each solution is designed to meet specific needs and can become inefficient—or even counterproductive—if applied in the wrong context.
In brownfield environments, this complexity increases further due to:
structural constraints (existing layouts, limited heights, predefined flows);
legacy systems (WMS, ERP, and established procedures);
the need to ensure operational continuity without long downtime.
Additional challenges include difficulty in accurately defining real operational needs, limited knowledge of available technologies, and strong pressure on ROI and payback time.
As a result, many companies risk oversizing solutions, choosing non-integrated technologies, or creating isolated automation islands. The most common mistakes stem from this misalignment: starting from technology instead of the process, overinvesting beyond real needs, and underestimating integration with existing systems.
To navigate effectively, it is necessary to simplify the problem: in a brownfield warehouse, the technological choice almost always revolves around three key variables:
the type of process to optimize (picking, handling, sorting, storage);
structural constraints (space, layout, existing systems);
sustainable investment level and expected ROI.
When discussing brownfield warehouse automation technologies, the most common mistake is focusing on individual solutions rather than their operational impact.
In existing warehouses, the most advanced technology does not win—the one most aligned with processes, constraints, and business goals does.
For this reason, warehouse micro-automation is gaining ground: modular, scalable, and quickly deployable solutions designed to improve specific activities (picking, handling, sorting) without requiring a complete layout redesign.
This approach allows companies to:
achieve tangible results quickly;
reduce investment risk;
maintain operational continuity;
build a scalable, evolutionary path.
Picking is one of the main drivers of automation, especially in environments with micro-orders and high variability. The most effective technologies include:
Pick-by-light / Put-to-light: guide operators visually, reducing errors and time;
Voice picking: enables hands-free operations, improving ergonomics and productivity;
AMR pick-assist: mobile robots that support picking activities, reducing operator travel time.
For example, in a zone-based warehouse, the operator stays in a designated area while AMRs transport containers between zones or to consolidation points.
AMRs are among the most widely adopted technologies in micro-automation thanks to their flexibility. Unlike AGVs, which follow fixed paths and require dedicated infrastructure, AMRs move autonomously and adaptively.
They can be used for:
• pallet transport;
• bin handling;
• support for picking flows.
In manufacturing, AMRs play a strategic role by dynamically connecting different operational areas, such as:
• feeding production lines (material replenishment);
• transfers between storage, picking, and shipping areas;
• movement across functional zones;
• separating transport tasks from picking tasks.
However, their effectiveness depends on flow orchestration: without clear operational logic, they risk replicating existing inefficiencies.
Goods-to-person (G2P) systems are among the main technologies for brownfield automation. Their selection depends on available space, required density, throughput, and flexibility.
Common solutions include:
Grid-based systems. Enable very high storage density by maximizing available volume. Ideal when space is the main constraint and volumes are stable.
Multi-directional shuttle systems. Offer high throughput and are suitable for structured flows and high volumes but require more rigid layouts.
Robotic tote/bin systems (high-density). Autonomous robots operate directly on racks or dedicated structures, handling containers even in multi-depth configurations.
Grid-based systems are effective when space is the main constraint, while shuttle systems suit high-throughput environments. Robotic tote systems are particularly interesting in irregular brownfield contexts due to their adaptability. In manufacturing, these technologies are effective when combining compact storage with production service, managing components or semi-finished goods efficiently. It is crucial not to confuse density with productivity: high-density systems do not automatically guarantee high throughput.
High-density solutions work best with standardized items and predictable rotations. When variability increases, accessibility and flexibility become more important.
With increasing order fragmentation, sorting has become a major bottleneck, especially when the challenge shifts from picking to sorting, consolidating, and routing items.
Common solutions include modular mini-sorters and compact sorters, ideal for increasing speed without introducing overly invasive systems. In brownfield environments, sorting adds value when it absorbs variability and peak demand while maintaining flow control.
However, performance depends not only on the machine but also on process balance. High-performance sorters in unbalanced systems can create downstream inefficiencies.
Buffering and sequencing logic are often required to synchronize picking, consolidation, packing, and shipping.
A critical but often underestimated factor is the level of integration between technologies and IT systems. Brownfield warehouses often include heterogeneous solutions from different vendors. The real value lies not in individual technologies but in their coordination. This requires orchestration capable of:
communicating with the WMS;
synchronizing operational flows;
managing missions across automation systems.
Without this, isolated systems may work locally but fail to improve overall performance.
When to avoid certain automation technologies
One of the most common mistakes is confusing storage density with operational performance.
High-density systems (grid-based, tote solutions) increase storage capacity but do not automatically improve throughput, order processing speed, or peak handling.
This misalignment occurs when decisions are based on static metrics (capacity, space utilization) instead of dynamic ones (flows, rotation, picking frequency).
Consequences include:
longer ROI;
underutilized systems;
operational inefficiencies.
To avoid this, companies must analyze:
order lines per hour;
SKU distribution (ABC);
access frequency;
volume variability.
High-density technologies deliver value only with stable and sufficiently high volumes. In brownfield warehouse automation, the starting point is always the logistics system as a whole: flows, constraints, product mix, and business goals. There is no universally best technology, only solutions more or less aligned with the context:
micro-automation is the most effective approach;
AMRs bring flexibility but require structured processes;
goods-to-person systems provide density and productivity with sufficient volumes;
sorting becomes critical when bottlenecks shift downstream.
A key takeaway is the distinction between capacity and performance: more space does not mean more productivity.
Finally, automation value lies not in individual technologies but in their integration within a coherent architecture. The most effective solutions are those that address real operational needs, adapt to constraints and evolve over time.