Simply efficient picking: designing clarity into every step
In a well-designed fulfillment center, a visitor with no warehouse experience should be able to step into the picking loop within minutes and contribute to real orders.
If that sounds ambitious, it’s worth asking why. The answer usually points directly to where the complexity in a system is hiding.
This month, we sat down with Oda Systems designer Jacopo Colò and data analyst Lovisa Brandrud to talk about the role good design plays in picking efficiency. This is what they had to share:
The most resilient and scalable picking systems are the ones where new team members become productive almost immediately, and where accuracy rates stay consistently high because the process itself supports good decisions. In practice, that level of performance comes from simplicity rather than machinery. When the workflow is clear, the right actions feel natural and the operator can focus on the task instead of the tool.
Design for the operator and efficiency follows
Internal logistics software is notoriously difficult to use. It often assumes deep technical knowledge and treats operators as extensions of the system rather than the people who make it function. A more effective approach is to treat internal tools with the same care as customer-facing products. When tools feel intuitive, efficiency grows without extra effort.
Prioritising clarity
Rather than relying on lengthy instructions, the most effective picking interfaces guide operators through visual cues. Large product photos aid quick recognition, and a map-like view of the station means an operator always knows where they are and where they need to go. When the visual language is clear, cognitive load drops and training becomes short almost by default.
Continuous improvement through proximity
When software evolves in close connection with daily operations, refinement becomes a habit rather than an occasional project. Designers and developers who observe real workflows can identify friction early and remove it through small, frequent changes. Over time, this approach prevents complexity from creeping in and keeps the software focused on what operators actually need.
Process simplicity is more powerful than structural complexity
The most common mistake in fulfillment design is reaching for new technology when the real opportunity is to remove a step. Every task that offers no value to the customer is a task that slows an operator down, and those tasks add up.
Removing friction
Most picking processes carry legacy steps that were necessary at some point but have long since stopped serving a purpose, and eliminating them can make a surprisingly big difference. For example, removing a manual labelling step and placing it earlier in the flow as an automated action can save time and mental energy for every single box. These kinds of micro-improvements compound across thousands of picks each day.
Designing around the realities of grocery
Grocery has its own operational rhythms, where popular staples move constantly while slower items fill out a large and varied assortment. Effective picking systems are designed around that reality, with station-based layouts that place high-frequency items closest to the operator to shorten travel time on the actions that occur most often. A cucumber, for example, might need to be picked every ten seconds throughout a full shift. Most automation systems simply can’t sustain that throughput for a single high-velocity item, which is why station-based layouts that put the most popular products within arm’s reach of the operator often outperform far more expensive solutions.
Accuracy depends on good design, not luck
Human-centric picking often raises concerns about error rates, but in practice accuracy improves when the system itself shapes the task so that mistakes are difficult to make. Item accuracy rates above 99.5% are achievable with a well-designed human-centric system. Oda’s own fulfillment centers operate at that level, and the design principles that get you there are straightforward.
Limiting the surface area for error
A station-based approach narrows the set of products an operator handles at any moment, and sophisticated algorithms can go further by separating items that look similar or share similar names so that confusing them becomes unlikely. Focusing the operator on one item for one box at a time removes multitasking errors and creates a calm, predictable workflow.
Verifying where it matters
Scanning remains an effective safeguard, but it doesn’t need to apply to every product. Items that are visually unmistakable, such as oversized packs or large multi-unit bundles, can be handled without further verification. This balance maintains a high level of quality without slowing the operator unnecessarily.
The overlooked path to profitability
When clarity becomes the foundation of the picking process, complexity disappears from the operator’s workload. That shift results in faster onboarding, smoother flow, higher accuracy, and a system that scales naturally with the volatility of grocery demand.
The most efficient operations are often the ones that feel the simplest to the people running them. By designing for clarity at every level, you can achieve speed, accuracy, and profitability without relying on increasingly complex infrastructure. The smartest system is the one that helps people do their best work with the least amount of thinking.