Connect Big Data with Predictive Analytics for Increased Visibility and Control Over Global Supply Chains

The age of digital transformation is now fully upon us and from a business perspective one of the most active areas of change, impact and opportunity is in supply chain management.

With maritime transport growing at an average rate of over 8.5 percent per year, over 90% of the world’s trade is carried by sea for a total of 23 million tonnes of cargo traveling by ship every day.

Global supply chains are one of the longest and most complex of business process systems due to the many moving parts, multiple transfer points, diverse company types/players involved and the sheer length of these supply chains.
Shippers, carriers, freight forwarders and third party logistic firms are currently spending millions of dollars in resources on ‘estimating’ important metrics such as container Estimated Time of Arrival (ETAs).

As digital disruption continues throughout the maritime supply chain forward thinking firms are investing internally in capabilities to become more data centric.

Most in the know will agree that the amount and sources of Big Data available around supply chains continues to grow geometrically because of increased use of Internet of Things (IoT) technologies, Satellite Tracking (AIS/Automatic Identification System) for ships as well as emerging implementations leveraging blockchain technology.

Artificial Intelligence (AI) and Predictive Analytics are also now increasingly being applied in order to make sense of, and best utilize all of these data sources, which are now clearly beyond the capability of human operators to manipulate, analyze, determine insights and then take action from in any kind of a timely manner.

However, in order for these advanced systems to function effectively requires that Supply Chain Professionals seek out and find the most accurate and diverse possible sources of useful data on all aspects of their supply chains.
Going forward, competitive advantage in digital age will come from harnessing as many sources of relevant big data as possible and then utilizing advanced Predictive Analytics and AI tools to make the best use of these sources.
By combining existing and valuable internal data sources with external high impact third party sources like open ocean AIS (Automatic Identification system) datasets from satellite data firms companies can create proprietary and powerful predictive logistic models to drive competitive advantage.

When it comes to examples of Predictive Analytics firms focused on supply chains Elementum and ClearMetal are just a couple that come to mind. And relative to emerging data sources of relevant Big Data on global supply chains, one very interesting new player is Spire Global.

Data integration via RESTful API connectivity are currently available providing data first supply chain professionals with the below sources for data on ocean going shipping activity for integration into your Predictive Analytics or Artificial Intelligence (AI) platforms.

o AIS Messages API – Modern RESTful endpoint to keep up with the live feed. Includes decoded fields, additional metadata about source and flag country, data filters, and 7-day archive.
o AIS Vessels API – Consolidated list of all vessels known to Spire including all static information, voyage info, most recent position, and historical positions.
o AIS Predict API – Algorithmic “engine” that analyzes historical AIS data to feed computed future positions to the Vessels API for current time plus 30 minute increments for the next 8 hours with prediction error and confidence percentage.

Spire Global has worked with a cutting-edge developer of logistics analytics as their supplier of global Automatic Identification System (AIS) data. The company’s analytics rely on Spire Sense’s fast revisit time over the open ocean to help make their predictive analytics possible.

“Having Spire’s timely global AIS coverage allows us to make much more accurate predictions, leading to better recommendations and increased customer cost savings. Being able to see every vessel in the water in semi-real time means a super fresh picture of what’s going on in the maritime world. In our world, having fresh maritime data has huge impacts on making good supply chain decisions.

Spire’s APIs and super responsive customer success team has allowed us to focus on what we do best (AI) and iterate quickly on our product. ~ Mark Held, CEO at Odyn

Predictive logistics are built from a foundation of simulation and modeling that enables a firm to more accurately predict each step in the supply chain process, highlighting risk ahead of time and helping to drive impactful business value.

As Shippers and Supply Chain Professionals develop their plans for digital transformation one of their key value added roles after sourcing and identifying which Predictive Analytics and Artificial Intelligence solutions they will use, will be to continuously identify, access and utilize accurate sources of both traditional and alternative data to drive success in these endeavors.

Companies and executives who begin to prepare themselves and their organizations for the complex battlefield dominated by Artificial Intelligence and Predictive Analytics solutions driven by the combined power of uniquely identified, sourced data sets.

The time to take up the looming challenge to master the machines and discover the data needed to fully digitize your global supply chain is today, and there’s no time to waste as this race has already started!


This entry was posted in , Emerging Trends, Freight & Transportation, Information Technology, New Ideas, Security, Supply Chain Management, Supply Chain Risk. Bookmark the permalink.

Comments are closed.