Over the past few years there has been a vast increase in the amount of information generated by individuals, companies and on social media, which has led to an unprecedented growth in the sheer weight of data that is being stored. Whilst ‘big data’ may seem like a relatively new concept, it has actually been present within logistics and the supply chain for the past 20 years, although its use and significance is increasing all the time – and arguably at a faster rate now than ever before.
Big data has a range of uses within logistics, such as route optimisation and the monitoring of stock levels. Whilst it is clear to see that big data can be incredibly useful within our sector, it also presents us with new challenges that need to be overcome, not least the complicated task of integrating data at different points of the supply chain. Data overwhelm is another challenge that we face, so it is essential that we are collecting suitable data and have the required technology to make use of it. Here we will look at the types of data available to us, and how big data can be utilised to improve our operations.
STRUCTURED & UNSTRUCTURED DATA
Data can be split into two categories: structured and unstructured. Structured data refers to information that is stored via traditional means in databases, reports and spreadsheets. By contrast, unstructured data refers to data that is collected from suppliers, customers and other outside sources. Unstructured data can be analysed to provide forecasts and predictions on a range of issues, such as demand patterns, stock replenishment and market trends.
MAKING USE OF DATA IN LOGISTICS
With the complexity of the supply chain and the fine margins that we work within, there are a number of ways that data can be used to increase efficiency and speed up our operations.
GPS and intelligent traffic systems can be used for route optimisation, ensuring that deliveries arrive as and when they are meant to, and preventing avoidable delays. As a problem at one point in the supply chain can create bottlenecks elsewhere, making best use of the optimisation tools available to us is vital.
Data can also be used in the storage and transportation of stock, by monitoring environmental conditions so that fragile and perishable stock is kept in the best possible condition at all times, as well as allowing us to forecast when replenishment will need to take place. Inventory levels can also be monitored in real-time, to prevent shortages in supply.
Further to this, we can use data to predict and understand consumer preferences and market trends, allowing us to create accurate forecasts for scheduling and estimations of demand patterns. By doing this, we can be proactive rather than reactive to changes in the environment that we work in, and prevent costly wastages.
As the supply chain is made up of a complex web of interaction between hubs, plants and warehouses, data can be analysed and used to better integrate the workings of the various stages in the chain. This has the end result of greatly improving efficiency, with problems spotted at the earliest opportunity and dealt with in the least disruptive fashion.
We need to understand the difficulties presented by big data if we are to unlock its many undoubted advantages. By utilising the data that we collect in the correct manner, we are able to operate more efficiently and be proactive in our decision making.
The technology we use at DriveForce is at the cutting edge of what is available, which allows us to process and analyse the data we collect in order to constantly improve the service that we provide. We take immense pride in our staff training levels and expertise, which are vital in allowing us to fully manipulate and benefit from the data systems that we have in place. The combination of our highly-skilled workforce and state of the art technology means that we are able to provide consistently excellent logistics solutions for all of our clients, with a guarantee of satisfaction if you choose to engage with us.