Rapid development of ecommerce has fundamentally changed how consumers around the world shop, with innovative shopping events, enhanced user experiences and the influence of social media all transforming how this industry operates. Yet businesses working in all sectors and of all sizes are facing challenges when trying to achieve efficient e-fulfilment operations.
From labour shortages and rising staff costs to utilising space effectively and ensuring returns are processed efficiently, there is a growing opportunity for new technologies and approaches in ecommerce distribution to meet pressing challenges.
Thanks to mobile robot solutions, operators are now able to work two or three times more effectively than normal methods of order fulfilment as these tools remove the need to walk around the warehouse. The stock picker can efficiently work on a larger batch of orders simultaneously without needing to move their IT equipment and in-progress work around the building.
“By keeping the picker in a single position, the work area can be better organised and the information displayed on larger, easier-to-use displays, which speed up the operation and reduce the training requirements,” says Tim Wright, managing director at Invar Systems, leading warehouse and order fulfilment solutions experts that offer world-class engineering, consulting, project integration and software.
Unlike manual options, robot solutions can store products in a higher density as there is no need to provide access aisles for pickers, with robots automatically moving products according to their demand to optimise the availability of stock and improve the responsiveness of the system.
When order fulfilment and returns processing are improved, companies are able to reduce physical storage space and rent, as well as enabling staff to complete tasks more quickly. According to the Reverse Logistics Association, the return rate for online shopping is at least 25 per cent, indicating the huge amounts of returns retailers are dealing with on a daily basis.
Traditional automated solutions clearly have an important role to play in ecommerce distribution, but robot solutions are available at a lower initial investment and the incremental costs, timescales and impact of scaling are lower. The robot solutions offered by Invar Systems have a track record of providing organisations tangible benefits. These flexible, modular robotic solutions provide a notable challenge to the large capital-expenditure projects designed around future volumes.
“Companies that want to have a higher level of physical flexibility with their automated systems can benefit from robots being easy to move from one location to another, whereas other options need a large investment in equipment, which take a long time to manufacture, install and are not easily adapted,” adds Mr Wright.
At a time when business agility is increasingly important for companies in all industries, robot solutions can provide a vital competitive edge as they require minimal physical installation and are easily expanded in different ways to adapt to changes in demand and storage requirements.
Moreover, robots can easily manage random storage without any significant degradation in picker performance, allowing them to store unsorted stock, such as returned items, effectively.
Invar Systems have worked with innovative companies, such as Superdry, to deliver solutions to cope with immediate demand and then scale up as demand changes. Their experts can create custom-tailored ecommerce fulfilment system solutions that are responsive, efficient and dynamic.
By partnering with Invar Systems, businesses can establish a flexible automation system for e-fulfilment operations no matter their size. Such solutions can increase profitability per order, accelerate order fulfilment at lower costs, and expedite reverse logistics and returns. “We offer steadfast and proven solutions, but aren’t afraid to apply emerging technologies when appropriate for the application,” Mr Wright concludes.
For more information please visit www.invarsystems.com