3 Ways Big Data is Transforming Modern Supply Chain Management

Big data has become a buzzword in the business world, particularly in marketing and manufacturing sectors - utilising large sets of computer-generated data and Artificial Intelligence (AI) software to reveal patterns and trends that help improve processes and strategies.

However, the impact of big data is also being seen across the supply chain sector too, with many organisations beginning to understand the benefits of using data when it comes to streamlining their operations at every level.

This is what we’ll be taking a closer look at in this post, discussing how big data capture affects the supply chain, and how this can be used by businesses of all sizes to deliver an agile supply chain model - from predicting buying trends and streamlining order processing through to logistics.

Better informed procurement and forecasting

Procurement is the backbone of any supply chain, but making the wrong buying decisions on a product could lead to large volumes of unsold stock or a shortfall in inventory to meet demand. This is where big data can play a pivotal role in informing procurement for both small and large-scale businesses. 

Traditionally, the process of identifying buying trends and calculating forecasts was through analysing structured data from the previous year or quarter’s sales and order tracking, which would inform a long-term strategy. However, AI software provides real-time data on buying trends that also takes into account other external factors such as weather or specific news that can also influence consumer behaviour. For example, if there’s a particularly mild spring, AI will provide data that takes this into consideration, as well as hard sales data, informing procurers of the impact warmer weather may be having on consumer spending. 

The result is more up-to-date data that gives an accurate view of what spenders are doing in the now rather than what they were doing the previous quarter or year. For a supply chain, this real-time data can provide more clarity on specific buying behaviours, as well as allowing greater flexibility to adapt procurement to suit current demands with relevant data to back it up.

Improved transparency

Technology has already transformed efficiency in the supply chain sector from organising stockroom inventory to logistics, but the introduction of AI and machine learning technology now provides even more ways to optimise supply chains to be more agile. The crux of this is the ability to share information from a variety of areas quickly and seamlessly - giving greater transparency across all points in the supply chain. 

With access to data in real-time for any given area of the supply chain, operatives can quickly identify areas that could be slowing down the efficiency of the process. This could be a bottleneck in online orders waiting to be picked and packaged or alerting delivery drivers of traffic delays. With up-to-the-minute data on all areas of the supply chain, staff can quickly pinpoint concerns and notify the appropriate departments before things escalate - ensuring solutions are found faster and more effectively. As a result, this helps to reduce potential delays that can be costly to a business.

In addition to this, introducing AI to a supply chain can help with automating previously labour intensive data analysis, as systems now provide a holistic data gathering capability that can be tailored to a specific business’ needs. Whether it’s tracking order fulfillment in real time or forecasting future buying trends, the ease of having all the data in one convenient system can be the first steps to cultivating a streamlined supply chain model. 

Optimised order processing

A fundamental part of an efficient supply chain is meeting consumer demands, particularly in today’s on-demand economy that’s being driven by the desire for instant gratification, with customers expecting speedy turnarounds and exceptional service. 

In order to achieve this, it’s essential to review your warehouse operations, striving to optimise their efficiency and processes in every possible way. One such area is inventory management, using AI technology to monitor and manage stock levels more effectively in real-time, rather than through periodic stock takes, which can be time-consuming and subject to human error. 

In addition, the advent of AI in the supply chain means there’s the possibility of automating certain processes within the order fulfillment stage as systems are able to identify specific logos, names and more on cardboard boxes. This can contribute to reduced picking and packing time with lower risks to warehouse workers too - all adding to your company’s bottom line. With the use of short-term data, many systems will also provide the capability to monitor shelf usage and storage efficiency overall, pinpointing areas that could accommodate more inventory. This all goes towards creating a lean supply chain that’s designed to meet consumer needs with the rapid order fulfilment they have come to expect.

Implementing big data in your supply chain may seem like a daunting process, but even small steps to embed it into your supply chain can have a valuable impact on improving transparency, efficiency and cost management. This results in cultivating an agile supply chain model that’s designed to help your business grow and meet your customer’s needs in the process.

Author bio: 

Alex Jones is a content creator for No1 Packaging - one of the UK’s lowest cost packaging providers.