Supply chain and logistics management, an important part of business administration, can make or mar your brand value and impact revenues. Its efficiency is gauged by the client as well as end-user satisfaction.

To create a great experience for clients, it is vital that they have visibility of the processes involved in procuring goods and the ability to identify and respond to any roadblocks that could impact the smooth delivery of products to end-users.

What if your supply chain systems were:

  • Sophisticated in forecasting demand to start packing goods even before an order was received.
  • Capable of sensing potential problems and supply chain disruptions before something goes wrong.
  • Proactive in finding solutions to problems such as bad weather, hurricane, or a transport route shut down during peak season.

A good end-user experience is what your clients look for, and this is where Big Data Analytics can help supply chain and logistics industry.

What is Big Data Analytics?

Well, your data is a treasure house worth millions. When real-time analytics is applied on massive, rapidly growing, structured as well as unstructured data, known as Big Data, you can view a different dimension of data that was earlier dormant.

Big Data Analytics aid businesses in making sense of critical business data to help them understand their operations and market better. It enables them to predict the probability of an event so that they can take timely business decisions and ensure customer needs are met.

Supply chain and logistics industry has always been driven by statistical and quantitative models for a long time now, but only old data was being used for analysis.

What Big Data does differently is that it operates on real-time data and thus can help you take the benefit of complete IT infrastructure in real time, thus giving you more flexibility and agility.

How a Global Logistics Company Utilized Big Data Analytics and Azure Cloud to Transform its Supply Chain?

There are times when a storm affects shipments in and out of a factory. Or a cargo of supplies gets stranded due to container ship crash. Geopolitical reasons too might need you to divert from your planned travel route. During festive season, demand goes high but transportation means become limited. In spite of all such disruptions, it is required for a logistics firm to keep goods moving and business running all the time.

A renowned freight forwarder and logistics management company based in Netherlands uses Big Data Analytics solutions on Azure cloud to let its clients know the number of goods in each container, their location at any given time and the time when they will reach their destination.

They developed a mobile app that tracks purchase orders and determines whether any potential challenges could delay the progress of the order. An another mobile app manages the complex process of calculating tariffs and fees related to the movement (or lack of movement) of shipping containers, giving clients greater insights into financial risk.

These apps make extensive use of Big Data Analytics along with Microsoft Cloud Technologies to combine and analyze external data from news feeds and internal data from the supply chain management solution. This data is ingested, parsed, processed, stored and visualized to turn it into actionable business insights.

Earlier the time it took to identify a challenge, develop a solution and deploy it on premises, used to be anywhere between 3 to 9 months. But now, because a wide range of valuable insights is available early, it has reduced to a couple of weeks depending on the complexity of the problem.

Thus, based on analysis of data from various sources and demand trends, they optimized their expenditure and increased their revenue by many folds.

Conclusion

Big data analytics offers tremendous potential to improve decision-making process and can have a major impact on a company’s overall operating and financial performance.

 

Please find the continuum of this blog:

How Big Data Analytics Can Benefit Supply Chain & Logistics Industry – Part 2