The fast-moving consumer goods (FMCG) sector is facing unprecedented change in the face of growing e-commerce volumes and the need for increased speed of delivery.
As volume move towards on-line platforms from in-store shopping and the speed of delivery increases as customers become more demanding, the pick and pack of goods will have to become more efficient. Here are some trends within the warehouse software space that helps support the growth of e-commerce expectations:
There is an increase for voice picking solutions, which is more hands free and faster. There are further trends towards more pick to light systems with mobile put walls. This
pick to light is a light-directed picking technology that provides an accurate and efficient method of paperless picking, putting or sorting and assembling products, while put walls are a cost-effective way to assemble multi-line orders for e-fulfilment. In a put wall, a warehouse management system (WMS) disaggregates the order lines from different customer orders.
The automation with robotics and artificial intelligence solutions would increase across the supply chain. South Africa is already starting to enquire about the availability of these products locally and there is increased inquiries for local suppliers offering support.
As warehouses and distribution centres have had to operate at the same or even better levels but with reduced number of staff, the FMCG sector has seen some real challenges in the past few months.
If one considers the increase in online-shopping and expected delivery turnaround times, the last mile distribution can now include the stores where customers can either collect or have goods delivered.
Pick and pack for these deliveries is from the closest most convenient place, if not the DC’s then from within the stores especially for the more outlying areas. This is a challenge for the store when it comes to demand planning as they now have to cater for both in store and on-line orders simultaneously.
In light of this changing environment demand planning for stock to stores especially where expiry dates and shelf life was involved were critical.
This is where data collection and interrogation will have to play a big part helping to forecast demand per area.