Big Data Logistics Case Study

6 Ways Blockchain Will Change Commercial Transportation
winnesota.com, Jan 25, 2018

Successful Blockchain Trial Concludes in Singapore
Port Technology (PTI), Feb 26, 2018

From new kid on the block to blockbuster tech
SGInnovate, Sep 28, 2017

Singapore exploring use of blockchain to link National Trade Platform to trade platforms in other countries
Priyankar Bhunia, Oct 10, 2017

How to deliver large scale process automation RPA
Nick Andrews, Oct 27, 2017

Seven Virtuous Steps For RPA Implementation (part 2 Of A Series)
Makarand Pande, Oct 10, 2017

Logistics firms pioneer AR technology to boost productivity, profits and worker safety
Numadic, Oct 17, 2017

Blockchains Can Be Strongest Link in Food Chain
AgWeb Editors, Sep 25, 2017

Can blockchain reduce supply chain complexity and costs?
Kirsty Adams, Oct 6, 2017

Robotic Process Automation (RPA): Keys to a Successful Implementation
Feb 16, 2017

Blockchain: A Single, Immutable, Serialized Source of Truth
Jim Haughwout, Oct 18, 2017

Robotic process automation (RPA) - A path to the cognitive enterprise
Deloitte, Sep 14, 2016

Robotic Process Automation (RPA): Closer to a Rules Engine than to Artificial Intelligence (AI)?
Dick Weisinger, Oct 3, 2017

Lots of Noise around Blockchain in the Supply Chain, But Lots of Challenges
Steve Banker, Oct 12, 2017

The Pentagon Has the World’s Largest Logistics Problem. Blockchain Can Help
Elana Broitman, Oct 3, 2017

January 25, 2016By writika.bhaskar

Take the plunge instead of just testing waters. Big Data is more than a buzz word and is here to stay with a promised future. The first-generation Big Data tools that are available to the Logistics and Transportation industry mostly focused on Sales, Marketing Customer relationship management and other day-to-day operational functions.

So, it is not surprising that Big Data will keep disrupting the way data is treated. The Logistics and supply chain industry is full of transaction-based processes and generates a huge amount of data itself. We are yet to include Giant Big Data Generators- Social media, shopping websites and search engines.  Here are the core-functions in Supply Chain and Logistics industry that Big Data can really help with.

  • Business Planning
  • Operations
  • Customers

In this article, we will touch upon each of these core-functions and support it with use-cases available across globe that is already helping companies with meaningful gains.

 

Business Planning:

Supply Chain industry is the backbone of global economic landscape. So far the economists and analysts have depended upon macro indicators like goods’ category, demand volume, production and supply levels etc and have forecasted the oncoming impact. However, Big data brings a paradigm shift in Analytics as it zooms-in distribution-network and extracts micro indicators that have significant impact on the business as well as global economics.

  • Demand and Supply Chain Forecasting

    This is the first application of Big Data analytics. Every transaction in Supply Chain is generating data and every actor involved in it is releasing information. Big Data is compounding the structured and unstructured data into actionable insights that is further analysed across various geographical and economic segments giving even a more precise forecast.

  • Sales and Marketing Intelligence

    Order Management Software and Mobile Apps are accumulating valuable information related to shipments and customers which can turn into useful marketing intelligence. With Big Data Logistics and Supply Chain company can have their own customized market research and venture into new geographical markets, target potential customers segments and new product lines backed with quality research.

  • Hyper Local Business Models

    Local Logistics providers are already powering their operations with IoT-based Fleet Management Solution. The new data sets available from GPS, embedded sensors and mobile apps are enabling the existing players. They are becoming hyper-specialized and developing a launch pad to augment new value-added services. For example, C2C Logistics (consumer-to-consumer) ecosystem that would allow shipments to flow from one consumer to another.

 

Operations

Big Data has contributed immensely in increasing level of transparency in operations, optimizing resource consumption, maximizing asset utilization and standardizing services. Big Data continues to create a “bigger picture” for the leadership teams as they pave their way to “Safe and Smooth” Operations.

  • Crowd-sourced pickup and delivery�

    This is a bold and innovative application of Big Data in Logistics industry, where the travellers or customer’s themselves can pick and drop packages instead of the traditional “last-mile” service provider. Crowd-shipping platforms are powered by Big Data technologies as the capacity of everyone logged as potential delivery driver has to be matched with the requests on real-time basis. “Last-mile” delivery services have been reinvented and have become possible to implement as Big Data can dynamically match thousands of such requests within the given variables.

  • Operational Intelligence�

    Operational efficiency is maximum output at minimum cost. Therefore, Capacity planning, route planning and monitoring for different supply chains is crucial but ability to respond to bottlenecks in real-time is what brings the difference. But the data is too big for the existing ERP and SCM systems to manage. With millions of transactions happening every day and multiple data sources both internal and external is even complicating further for Supply Chain companies. Big Data Application can manage transactions of high volume, velocity and variety to provide automated reporting, pattern identification to point out risks and opportunities and avenues to cut-down cost.

  • Safe and Green Logistics

    Supply chain companies can make deliveries keeping fuel consumption, mileage, engine conditions, emissions, driver’s behaviour and speeding habits in check while executing multiple drops and collections that can be personalized or rescheduled at any point in the day. How? The answer is simple. Big Data Application that will execute Dynamic route optimization after with data received from fleet telematics, customer mobile App and other sources about roadblocks or breakdowns.  With a Big Data powered Route Optimization tool, companies can manage thousands of reschedules per second to achieve less environment impact and better customer service all within budget.

 

Customer Service

  • Customer Retention

    Big data combined information of customer’s complaints, requests, appreciations and other interactions from island-like conventional CRM and combine it with publicly available sentiments on news, annual reports and social media to identify patterns that can point out potential attrition in the customer. The Big Data Applications can further be programmed to automatically trigger loyalty programs.

  • Service Performance Continuity�

    To measure and tune supply chain performance, customer feedback provides valuable insights. The traditional CRM is focused on case management and customer surveys. However, the customers now are discussing the brand, services and products on social networks and discussion forums. Big Data techniques now are analysing unbiased customer sentiments from the huge text, audio, video data etc can identify correlations between various parameters and can be broken down by location, action and time.

0 Replies to “Big Data Logistics Case Study”

Lascia un Commento

L'indirizzo email non verrà pubblicato. I campi obbligatori sono contrassegnati *