Tag Archives: Anlaytics

BIG DATA transforms Logistics industry in BIG way

With the internet usage around the world and especially in developing countries such as India increasing at an exponential rate both in the terms of individual as well as business, humongous amount of data is bound to be generated. No business vertical can afford to not put to use this valuable data and extract useful information which would empower them to take prudent business decisions. And yes, Logistics & Supply Chain industry is certainly one of the early movers to have embraced this DATA revolution.

The term BIG DATA Analytics refers to the processes, methodologies and algorithmic techniques employed by the businesses to analyze the enormous amount of collected data, make sense out of it and take critical business decisions which would eventually improve their operational efficiency and improve customer satisfaction. In other words, BIG DATA enables the businesses to predict the probability of the occurrence of an event from the past trends and thereby take judicious and timely decisions.

BIG DATA transforms Logistics industry in BIG way
BIG DATA transforms Logistics industry in BIG way

As an instance, for the Logistics and Supply chain industry, extracting useful information from the huge unorganized data collected through different platforms will help the supply chain professionals to gain insights into the various business parameters such as operational risk management, layout optimization, pricing strategies, improved product and service delivery.

So what encompasses Analytics Domain?

In the complex information flow of the SCM and Logistics industry, BIG Data Analytics encloses three major areas: –

  • Descriptive Analytics where in a past business situation is described in a way of trend/pattern to provide an insight into any forthcoming event. This is normally done using Standard reporting dashboards, Alerts.
  • Predictive Analytics uses the REAL time data and historical data to make predictions about the events having the probability of occurrence in the future. These mostly include Time Series, Regression analysis.
  • Prescriptive Analytics uses the predictions based on past trends and data and also suggests a set of action/s that could be undertaken for a possible foreseeable event.

BIG DATA to reap BIG Benefits

In the field of Logistics and SCM, Big Data Analytics uses all the three above mentioned techniques to synchronize the end to end logistical chain thereby making an incremental impact on the supply chain drivers such as inventory planning, facilities /warehouse management, transportation management, sourcing and procurement, pricing.

  • Warehouse management: – Using Advanced Analytics based on the collected data the organization can take a judicious decision on the location and capacity of the proposed warehouse facility and even monitor it’s
  • Inventory Planning: – Having an extremely optimized inventory planning model would go a long way in improving the responsiveness and efficiency of the organization.
  • Transportation Planning: – The application of BIG DATA analytics in devising an optimal travel route for the material and goods transfer has gone a long way in improving last mile delivery, identifying risk areas, predicting accurate delivery times and most of all making transportation safer both for the material and people involved.

 

In a developing country such as India where the Logistics and Supply chain industry is in a very chaotic state yet in a stage from where it is to grow beyond one’s imagination, effective use of available analytical techniques such as BIG DATA       will help companies to standardize their decision-making process. Of course, the recent decision of the Govt. of India to introduce the GST (Goods and Services Tax) by next fiscal will only help the logistics industry to streamline it’s processes and costs making the industry leaner.

Logistics and Supply chain is an industry which is driven by quantifiable performance indicators and hence “Real-time Analytics” of rapidly increasing, huge and unstructured data is inevitable.