EssilorLuxottica: How to Automate Distribution Effectively

EssilorLuxottica is a global leader in eyewear and eye care, with a mission to help people everywhere 'see more and be more'.

The organisation brings together advanced lens technology, iconic brands like Ray-Ban and Oakley and one of the world’s largest retail and eye care networks.

At the helm of distribution network is Naveen Chandra, who oversee teams responsible for slotting, warehouse optimisation and orchestration across multiple facilities and channels.

Here, Naveen explains why human-machine orchestration, well-trained teams and structured processes are essential to making automation work.

Many people view warehouse automation as a purely technological challenge. From your experience, why do robots often fail without the right human processes in place?

In my experience, robots rarely fail because of technology itself. They fail because the human processes around them haven’t kept pace. Too often, automation is treated as a plug-and-play solution. A company installs robots, but keeps running outdated practices in slotting, wave release, or exception handling. Everything may appear well-optimised in reports, yet on the warehouse floor you see congestion, underutilised equipment and service commitments still slipping.

What I’ve learned is that automation must be viewed as part of a socio-technical system. Robots don’t operate in isolation. They interact with people, workflows and decisions that shift by the hour. For automation to succeed, there must be an operation–automation match, where the technology aligns seamlessly with how work is planned, released and executed. That’s why I focus heavily on orchestration: making sure labour planning, exception management and system logic are in sync before automation ever arrives. I’ve even built a framework for this, the Automation Readiness and Integration Framework (ARIF), to help organisations avoid those pitfalls.

When you get the human processes right, the technology delivers. Without that alignment, automation often magnifies inefficiencies instead of solving them.

You’ve emphasised the importance of orchestration between humans and machines. Can you explain how orchestration software actually bridges that gap on the warehouse floor?

When people hear the word ‘orchestration,’ they often imagine a control tower sitting above the operation. But on the warehouse floor, orchestration software is much more practical: it’s the layer that connects human judgment with machine execution in real time.

For example, a robot may know how to retrieve a tote from storage, but it doesn’t know whether it should do so now, later, or in coordination with ten other orders. Orchestration software makes that call, balancing work release, picker availability, congestion in certain zones and service-level priorities. At the same time, it pushes dynamic instructions to associates which cart to pick, which task to prioritize, so that people and robots are never working at cross-purposes.

In my work, I’ve described this as moving from isolated automation to a true socio-technical system. The orchestration layer becomes the translator: it converts strategic goals like throughput or SLA compliance into real-time decisions that align both machines and people. Without that bridge, warehouses risk having powerful tools that operate independently, but not effectively together.

What cultural shifts are required inside organisations when automation is introduced and how do you overcome resistance from frontline teams?

Introducing automation is as much a cultural transformation as it is a technical one. The first shift required is moving away from the fear that ‘robots are here to replace us’ toward the mindset that automation is here to augment human work. In every warehouse I’ve worked with, frontline associates are quick to spot when technology is poorly aligned to their reality. If leaders don’t engage them early, resistance grows quickly.

The second cultural shift is trust in data-driven decision-making. Automation and orchestration software often reallocate work dynamically, which can feel disruptive to teams used to fixed routines. Building trust means showing operators how the system’s choices improve safety, reduce wasted motion and make their jobs easier.

I’ve found success by co-designing workflows with associates, not for them. When they see their input reflected in task design or exception handling rules, adoption skyrockets. Equally important is investing in training that frames automation as a skill-building opportunity. In the end, culture shifts when teams feel like participants in innovation, not passive recipients of it.

In your rollouts at Medtronic and DHL, what were the biggest surprises or hidden challenges that emerged during implementation?

At both Medtronic and DHL, the surprises were rarely about the technology itself, they were about how technology interacted with scale and people. At Medtronic, we were deploying automation in a highly regulated, healthcare-focused environment. What surprised us was how small workflow mismatches, like how replenishments were triggered or how exceptions were logged, had outsized impacts on throughput. It taught me that in sensitive industries, automation success isn’t just about speed; it’s about precision and process discipline.

At DHL, the challenge was very different. The technology scaled well, but what caught us off guard was the variability in customer order portfolios. Some clients were heavy on pallet-in/pallet-out, others needed each-pick fulfillment and a single automation footprint couldn’t serve all equally well. It was a lesson in what I call operations–automation match. Ensuring that the design of the system matches the actual flow of work, not just averages on a slide deck.

In both cases, the hidden challenge was the same: integration with human processes. Automation succeeds when it’s flexible enough to adapt to both operational realities and cultural context.

The true intelligence of automation lies not in the machine, but in the people who design and operate it.

Looking ahead, what role do you see orchestration software and human-machine collaboration playing in the next wave of warehouse transformation?

The next wave of warehouse transformation will be defined less by individual technologies and more by how they are orchestrated together. Automation, robotics and AI are advancing rapidly, but their real potential is unlocked when they operate as part of a coordinated, human-centered system.

Orchestration software will play a critical role as the decision-making layer, ensuring that machines and people complement each other rather than compete. For example, robots may handle repetitive transport tasks, while orchestration systems direct associates toward higher-value activities such as exception handling or quality control. This not only improves productivity but also builds resilience, a lesson we’ve learned after years of disruptions.

Human–machine collaboration will also shift culturally. The warehouse worker of the future will not just ‘use’ automation, but actively partner with it, receiving dynamic guidance, contributing feedback loops and adapting in real time. I believe the facilities that thrive will be those that treat orchestration as a capability, not just software: the ability to continuously balance human judgment with machine efficiency in pursuit of agility and scalability.