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Data driven: how warehouse and logistics can drive business value using data

Data driven: how warehouse and logistics can drive business value using data

According to PwC, in 2013 there was 4.4ZB of data in the digital universe - by 2020 that figure is estimated to reach 44ZB by 2020. Just to clarify a ZB (or zettabyte) is 1,0007 bytes  - too many zeros to write out here. With the advent of new technology such as the IoT, driverless cars and wearable devices, the growth of data is hard to predict but most will agree that it’s set to reach unimaginable levels in the near future.

For many businesses simply storing this increasing volume of data is challenge enough, so how can organisations collect, store and analyse that data to improve decision making and drive greater value back to the business? This was the main discussion point at a recent roundtable hosted by automation company Conveyor Networks, software business imio Software Solutions and assistant editor David Tran. Around the table were representatives from delivery group Yodel, advisers Logistics Partners Consultancy Ltd, Professor Phil Greening from Herriot Watt University, and retailer Pets At Home

What is clear is that now, more than ever before, warehouse and logistics functions play a central role in the management of data. According to Adam Gerrard, Chief Digital Officer at Yodel, data visibility is key to their business model. According to Adam Gerrard, Chief Digital Officer at Yodel, data visibility is key to their business model. “We’re constantly tracking events – whether that’s scanning a product or moving something onto a truck – we understand the flow of events around the business. We use those insights to make decisions about what can go wrong, and inform changes to the process. We help retailers utilise these insights to make better decisions themselves.”

But just how well those organisations utilise data is proving a challenge. With so many factors at play, retailers, 3PLs, e-commerce businesses and logistics are being faced with both internal and external challenges that are proving difficult to overcome.

Professor of Logistics at Herriot Watt University Phil Greening, comments, “Logistics is a data business. So why do we not know where the data is and how to use it? Nothing was ever shipped by accident. We should know all about the data we generate, but often we don’t.”

Ensuring that data management sits at the heart of the organisation and isn’t treated in silos is key to managing it successfully, according to Gerrard. ““We’ve invested a lot. We’ve had the same data team for five years, which makes it easier to understand the data the business is generating. To help manage the amount of data we gather we have a master data model and strategy, and store it in a data lake. This means we can respond quickly and efficiently because we’ve been consistent with the management over the past five years.”

Independent logistics consultant Lynn Parnell adds, “Approaching data from a whole company perspective and not just from distribution/warehouse perspective is key, but it’s often harder if you’re a retailer where logistics can have a lower profile.” Terry Siddle, director of logistics & distribution at Pets At Home, agrees, “Data management is focused on the customer side because this is where regulation has most impact – data generated by the warehouse is at the end of the process and as a result less of a priority.”

Regulation is proving to be a challenge. In the main most participants agreed that new laws, such as GDPR, has had an impact on the way data is managed but that it is a ‘journey’ rather than a single process. Marcus Uprichard, sales and marketing director at Conveyor Networks, comments, “Automation systems are generating more and more data. That means that organisations need to think about regulatory issues at a warehouse level. And regulations and security needs are constantly evolving, which can make it harder for businesses to manage.”

Outside of regulations, internal processes and knowledge are also hampering efforts to utilise data effectively across businesses. Uprichard observes, “When we start working with a customer we often find that they struggle to send data to us in an organised and structured manner. We need forecasts, throughputs, shift patterns and so on to help build automated systems, but often this data is raw and kept on a spreadsheet. We harness it, and then turn it into something that can be used for planning.”

Gerrard agrees, “It’s not our data that’s the issue – rather it’s the format we receive it in from retailers. We restructure it and then use it to make more accurate forecasts based on data over the past five years. And we can do this better than the retailer because we can access insights across a number of retailers. This work is currently being done by data scientists creating algorithms, but in the future it will be achieved through machine learning.”

The growing volume of data is creating rising costs, according to Philip Rowlands, head of software delivery at imio Software Solutions. “The access and speed of processing data can be a massive cost to a business. Focusing on data for one business process at a time is a logical best approach but inevitably it means that another process gets ignored.” Greening adds, “It’s the competency trap at play. While one set of data will give you one set of value, it comes at a cost of missing out on the value that another set can deliver.” Gerrard agrees, “We write a list of 400 things that we want to use data to change, but then have to prioritise 10. What’s the impact of not doing the other 390?”

Parnell believes that the key to overcoming this challenge is to have two different data teams working across the business. “You should have one team focused on how data can be used to improve business objectives, and a second team who should just review and analyse data as a whole set, looking for innovation. This is how some of the biggest changes are made.”

Working in silos clearly is hampering efforts to utilse data to make organisations more agile in their approach. Parnell adds, “Agile working is key. Having an agile approach to software and processes is fine, but we need businesses to think agile. Warehouse and logistics often operate in silos and so does the data

According to Philip Rowlands, head of software delivery at imio Software Solutions, there is sense of inertia in businesses.” So much investment is made in old systems and processes. We need to take small incremental steps with small teams to make small changes quickly. This is how we win hearts and mind changes.”

Better decision making using data is happening across the warehouse and logistics industry but the key is to be able to show how it delivers value. Gerrard says, “We see the value of data everywhere. Take returns for example, we can use data to show retailers that their average return rate might be 30% but in some postcodes it’s as much as 60% - so they can market to those customers differently. That’s value.”

ROI doesn’t always need to be financial however. Parnell adds, “Sometimes it’s enough to show a clear benefit to the business.” This might well be reflected in the industries need to be more environmental.

Respondents were clear that warehousing and logistics functions can use data to resolve many of the environmental challenges faced by the industry today. Zero emission vehicles supported by small local hubs could reduce road time; better forecasting means less products sent to warehouses and then distributed; all trucks filled to capacity before they hit the road; returns being re-sold and re-packaged out of trucks rather than warehouses; and even shared deliveries over the last mile could reduce the current environmental burden.

It’s clear that data has a big role to play in changing the warehouse and logistics function. Respondents were unanimous in their belief that if those analysing data were able to apply its value further down the supply chain – from manufacturer to retailer to distributor – it will drive a much bigger role for the warehouse and logistics function in the future. According to Uprichard, “We’re so busy trying to make changes for the future based on what we do now, instead we need to focus on making changes now, so we’re ready for the future.”

Conveyor Networks will feature in the upcoming issue of SHD July.

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