Process optimisation: small changes, big impact for food retailers

‘On time’ and ‘in full’

To ensure that shoppers enjoy the best-possible experience, retailers must achieve an on-time and in-full service performance when it comes to activities within their distribution centres (DCs). Replenishment times are fast, planning is strict and delivery trucks cannot be delayed. Put simply, any product that is not on the truck cannot be sold.

Therefore, having control over the output is vital and this is what we, as Vanderlande, can deliver to our customers. While the choice of automation inside a DC is crucial, food retailers stand to make significant efficiency gains through process optimisation. By collecting and analysing fact-based insights about these systems, we are able to cultivate a culture of continuous improvement for them.

Understanding and using data

In recent years, we have been harmonising data and the way we measure system performance all over the world. Take for example that many leading food retailers worldwide use our automated case picking system, STOREPICK. Vital information is part of every system we deliver allowing us to standardise our data offering.

This is because we are able to understand the individual performance of every product that comprises STOREPICK (for example, an ADAPTO AS/RS shuttle or a robotised palletiser). By gathering a huge volume of data from our systems, we can execute analytics, translate our findings into KPIs, and identify operational improvements. Standardisation also means that any improvement will benefit everyone using our systems.

Creating global synergies

Here, we must give credit to our 60 process engineers all over the world, who continuously benchmark system KPIs (such as throughput and availability) via a centre of excellence (CoE). Every day, they monitor system activity and look for synergies in the benchmarked information in order to make continuous improvements.

We like to think of our process engineers as being like a ‘spider in the web’, looking at system performance from a long-term factual perspective. In analysing discrepancies, they can identify whether an issue is process- or maintenance-related. By sharing best practices and lessons learned, improvements can then be made for food retailers globally.

Often working in unison with other departments of the global organisation such as R&D, process engineers can identify root causes in any area of the system. Using smart dashboards, they can see why a truck was delayed or why a robot palletising cell might not be performing optimally, for example. All of these insights feed into a continuous improvement programme that can be tailored to any individual retailer.

Sharing the same end goal

Process optimisation can also have an impact on areas that are usually outside of Vanderlande’s scope. Here’s an example that might sound familiar: imagine that a box of products is delivered, but its dimensions differ from those agreed with the supplier. This can lead to system downtime, as well as negatively impact on-time and in-full deliveries.

By working closely with a customer to share insights, we can still help them to accommodate such a change. In my opinion, we are always working on the same end goal as an extension of their teams. In some ways, process engineers are decoupled from any ‘customer/supplier’ mentality, they are only thinking of the best way to improve the system.

The key aspect of process optimisation is that it’s all about small, incremental improvements, which all contribute to an excellent performance. Generally, low-hanging fruit has already been ‘picked’ and improved. As such, we work in daily or weekly cycles with our customers and Vanderlande experts to identify and solve the next optimisation challenge, always working towards ‘every day better’.

A proactive position

It’s never easy to make predictions, but if we could consolidate our vision on process optimisation it would be that we will move away from a reactive position. By continually gathering more insights, we will mature our proposition to more of a data science, offering predictive and prescriptive advice.

Having that standardised approach we mentioned above will also allow us to evolve the continuous improvement culture we share with our customers. We are incredibly excited by the next steps in terms of predictive insights. What if food retailers could predict their own on-time and in-full performance? That would be most interesting.