Supernova Award Category
Data to Decisions
The Problem
The shipping industry faces a 15% inefficiency problem as a result of Inaccurate shipping, planning and forecasting. The ability to streamline global logistics and all of its moving parts remains unattainable despite technology innovation. This is due to three prime factors:
1. Ultra-complexity: Global trade is overwhelmingly complex, with an interdependent end-to-end supply chain-- from purchase order through final delivery, and from raw materials to retail store. A typical shipment can involve anywhere from 5-25 different parties and handoffs.
2. Innovation barriers: There has been technology innovation in areas such as cloud, analytics and big data. Yet, true predictive logistics remains elusive. Data is dirty, inaccessible, and siloed away in antiquated systems. Further, existing tools and technologies are inadequate at organizing disparate data, making intelligent sense of it, and allowing this valuable data to be analyzed and made actionable.
3. An Analog Approach in a Digital World: While the shipping industry has historically driven profitability by adding size and scale-- think mega-ships, mergers and alliances, more buffer-- the day has finally come where throwing more resources at the problem is not only no longer helping like it used to but often hurting (think: over-capacity).
The Solution
It’s important to recognize that the critical need to mine, model, simulate and predict global logistics in real time requires four fundamental elements:
Understand the Data: Robust data ingestion capabilities are needed to scrape and cleanly structure data from multiple sources
What-if Scenarios: A simulation engine is essential for running what-if scenarios and analyzing all shipment events and outcomes
AI / ML: Machine learning offers a fundamentally different approach to interpreting data, recognizing complex patterns between parties and events, and dynamically generating highly accurate predictions
Industry-Expertise: To apply this advanced technology and data science to global logistics, a set of custom built solutions are needed for the shipping industry, empowering ocean carriers, freight forwarders, 3PLs, ports, manufacturers and retailers to get the data they need to make optimal business decisions.
The results
Customers are able to centralize and cleanly structure both historical and real-time trade data leveraging ClearMetal’s proprietary ingestion engines. Freight data that was previously dirty, siloed and inaccessible is made machine-intelligence ready for advanced analytics and prediction.
ClearMetal’s industry-tailored machine-learning system predicts nearly all freight booking and transport events, providing an arsenal of predictive intelligence to deliver actionable insights on shipment flows and partner behaviors.
A proprietary simulation engine calculates thousands of what-if scenarios to account for exceptions and irregularities to enable more efficient execution and supply chain reliability.
Metrics
Share the metrics that provide evidence for your "Results" section. Judges prefer solid metrics that demonstrate ROI, business model transformation, etc.
At least $50 billion per year is wasted in the global supply chain due to under-informed decisions, unreliability, under-utilized allocations, missed transshipments and excess inventory.
Every decision made in the global supply chain is based on some kind of a prediction, usually with input from scattered data sources. ClearMetal centralizes all the data necessary to make decisions, cleans it, makes it machine-learning-ready and is proven to produce big cost savings and revenue gains.
Specifically, ClearMetal is proven to increase prediction accuracy by 30-60% over previous methods.
For example, if you’re a carrier and a customer cancels a big shipment a day before your ship moves, significant revenue is lost. ClearMetal tells you the likelihood of that happening so that you can hedge to prevent losses.
For one mid-sized ocean carrier (400K TEU exports out of North America), it was discovered that for North America alone, savings would conservatively be $5M/year + additional revenue.
The Technology
The ClearMetal Predictive Intelligence Platform delivers actionable insights for optimal asset allocation and trade management decisions. Through data science and AI, the events of the global trade network are deeply analyzed and predictive models are generated dynamically to produce the most accurate and detailed event predictions in the industry.
Disruptive Factor
Discuss any challenges faced in the implementation/adoption process. Discuss the impact of your project on your organization and (if applicable) on your industry. Have you changed the status quo? What sets you apart from other technology leaders?
The biggest difference between ClearMetal and other vendors is that other providers take an “outside-in” approach to data. In other words, they rely primarily on external data feeds such as IoT to deliver predictive intelligence. External data is useful, but ClearMetal focuses on data that shippers and trading partners already have - and transforms it into actionable insights.
Shining Moment
We’ve received multiple awards from Lloyd’s List, Supply & Demand Chain Executive Magazine and Frost & Sullivan.