Smooth upgrade Multinational bulk distributor, Lubna Foods, has gained significant efficiencies after a smooth installation of STL Evo, the most modern, intelligent and flexible business management platform in wholesale. It’s integrated with STL’s Point of Sale, Track & Trace and Android-based picking solutions, plus SwiftCloud’s eCommerce app.
Nasser Ali, Director, said,
‘The prospect of migrating all our data to a new system was daunting, but STL clearly understood our business as well as our IT needs. They walked with us every step of the way to ensure the minimum disruption to trading.’
Flow of information
Now, customer orders go straight from Lubna’s SwiftCloud app into Evo’s sales order processing function through to its warehouse – without the need for any rekeying.
Pickers also save time with STL’s handheld apps, which keep track of goods in and orders out, help locate items, efficiently group and prioritise fulfilment tasks, and immediately alert pickers of any errors.
Similarly, at Lubna’s popular market-based cash & carry, Evo automatically handles card payments, promotional discounts and TPD operator checks at the point of sale.
This enables the site to instantly report all sales and stock levels to head office, while complying with both the tobacco trading requirements and Lubna’s multiple supplier arrangements.
All this eases the administrative effort for the accounts team, provides timely information for the replenishment team, and reduces the potential for out-of-stocks and customer dissatisfaction.
A big difference Nasser said, ‘Evo far exceeds anything we’ve used before. By enabling data to flow smoothly across all our systems it gives us a really clear, up-to-date picture of our whole operations – one that’s easy to drill down into, to identify where we might reduce costs, increase efficiency or better respond to buying trends.’
Lubna is so impressed that it’s looking to add new modules, such as STL Q-Buster – a clever app that takes STL’s tilling and stock management software ‘mobile’, allowing operators to quickly answer customer queries and prevent the build-up of check-out queues during peak trading times.