The warehouse and logistics sector is harnessing data to make strategic decisions and drive business growth, according to participants at a recent roundtable hosted by warehouse automation company Conveyor Networks. But many are facing challenges in managing the huge volumes being generated at warehouse level and turning it into something of value, suggesting that some growth opportunities are being missed.
The roundtable bought together representatives from 3PL provider, Amethyst Group, parcel carrier Yodel, consultants Logistics Partners Consultancy Ltd, Professor Phil Greening from Herriot Watt University, retailer Pets At Home, and warehouse management software company imio.
While it appears that the warehouse and logistics industry is typically slow to adopt new technology, with only 65.1% of warehouses having completed a WMS implementation (according to a 2018 WERC DC Measures survey), data insights are already helping the sector to drive key improvements across their organisations in customer satisfaction, employee productivity and operational decisions.
Visibility of transport and distribution data is just one way to improve both customer and client satisfaction, according to the panel. As well as giving customers real-time parcel tracking and delivery updates, Adam Gerrard, chief digital officer at Yodel, believes this data can be used to make delivery more efficient; “Delivery is just a series of events that we track as they happen. From this we’re able to make process improvements. For example, our data helped us to establish that some packages were getting stuck in an endless loop between delivery and return. We used this data to help clients tweak their returns instructions accordingly and ultimately improve customer satisfaction.”
Data generated in the warehouse is also being used to maximise employee productivity, says Terry Siddle, director of logistics and distribution at Pets At Home; “We use our WMS to monitor both individual and group performance using data capture points throughout the process. Moving forward we’re focusing more on the flow of packages through the process and using automation to minimise manual processes and increase output.”
However, it appears that the sensitivity of customer data and regulation can also be challenging. Terry added, “Data can be dangerous. I think there’s still a widespread lack of understanding around GDPR. Data is captured in discreet pots, in software and spreadsheets, but linking it all is difficult.”
GDPR compliancy was identified as a common challenge by roundtable participants, with warehouse data often taking a backseat to sensitive customer data and becoming less of a priority. Independent logistics consultant, Lynn Parnell, says the starting point is knowing exactly what data you already hold and building a solid foundation; “Your decisions need to be made on data that is accurate. Start with a small pool of data and then build, and if you’re new to it, start by making one decision at a time. Ideally you need two groups of people looking at different areas of data; ones that can use data to support incremental growth and the other that analyses it to deliver radical change. The combination will drive significant benefit to the business.”
Marcus Uprichard, director of sales and marketing at Conveyor Networks, commented, “Automation enables us to collect a huge amount of potentially valuable data, and it’s important for businesses to realise how this data can be applied to provide a case for strategic decisions that will ultimately add value to the business and the end customer. For those that feel overwhelmed by the sheer volume of data created at warehouse level, the best logical approach is to focus on data for one business process at a time.
“The roundtable highlighted a number of different ways that data can be used – and is being used – across warehouse and logistics sectors to drive business growth. It’s promising to see that so many businesses are already basing decisions on existing data patterns and insights, and by being vigilant and investing the time and resources into analysis, we expect to see data-led decisions increase in the future. “
