ClearMetal’s Data-First Approach & AI Adoption: How It Matters?

These days, digital transformation has emerged as a central theme within the world of logistics and supply chain. This isn’t breaking news, but it is new for the industry! Again and again, digitization and data have been at the heart of panel and networking conversations. Actually,

Marquee speakers are professing “data got sexy” and data is now a core strategy for companies looking to succeed. And ClearMetal – the leading predictive logistics company – is not an exception!

Let’s read on to figure out how ClearMetal has adopted artificial intelligence to partly revolutionize the industry of logistics and supply chain management – which is a notoriously outdated and labor-intensive process – as well as resolve its pressing challenges of data access and quality!

ClearMetal: The Story of Innovation

Before going into great detail, it’s important to first grasp basic understandings as to ClearMetal and its innovative strategies!

Located in downtown San Francisco and advised by World Shipping Council Chairman Ron Widdows, ClearMetal is a Supply Chain Visibility Software company that uses data science and AI to unlock unprecedented efficiencies for global trade. They build out data-driven products to tackle the most complicated operational problems in the supply chain, empowering supply chain and logistics professionals by making trade data organized, accessible, predictive, and actionable. 

ClearMetal, whose customers already include logistics provider Panalpina and paper goods giant Georgia-Pacific, was created since its founding team “saw a multi-trillion dollar global trade industry that moves 90 percent of everything around the world wasting billions of dollars as a result of not having the right tools and technology to handle the ever-increasing complexities of the supply chain,” co-founder and chief executive officer Adam Compain shares at TechCrunch.

Whereas several companies still rely on spreadsheets and legacy software, ClearMetal – whose other founders are head of engineering Diego Canales and head of technology Will Harvey – wishes to replace those outdated tools with its SaaS platform, which adopts artificial intelligence to canonicalize freight data, or convert it into one standard format, and create more visibility for the entire supply chain.

Furthermore, ClearMetal’s technology makes good use of freight data to forecast the future with certainty. Developed by top software engineers from Stanford University and Silicon Valley, ClearMetal’s Intelligence Platform predicts nearly all events in freight booking and transport – enabling asset allocation and trade management decisions that deliver unparalleled profitability gains for carriers, forwarder / 3PLs, terminal operators, and shippers.

To take an example of how such platform can potentially benefit users, Compain describes a large retailer that is in bad need of getting shirts from a factory in China to its distribution center in Chicago in time for Black Friday. Usually, this means it shall have to make an order 60 days in advance to account for shipment delays. Even then, the retailer still has to budget for emergency air shipping because it doesn’t have a lot of visibility into the status of its freight.

ClearMetal’s platform, on the other hand, not only tells the retailer where its shipment currently is and predict transit delays but also selects which ocean carriers to use by analyzing their service reliability. As a result, such retailer is able to save money on shipment costs, nail down an arrival time for its shirts as well as avoid ordering backup stock. Whilst the amount varies by company, Compain says ClearMetal’s customers have “cited tens of millions of dollars of value potential” up to 2017 when employing its technology.

“Often we draw the analogy to the early days of mobile technology,” Compain says. “We’re helping equip supply chain operators with a smartphone when traditionally all they’ve been given is a flip phone.”

In May 2018, ClearMetal has been named in “Cool Vendors in Artificial Intelligence Across the Supply Chain” report by Gartner, Inc. “We believe our inclusion in Gartner’s Cool Vendor report validates our efforts to deliver data intelligence and our Predictive Transport Visibility solution to the retailers and manufacturers we serve,” said Compain “As challenges have increased for our customers, it’s become increasingly important for them to gain differentiated capabilities from what has existed before. Our data-first approach to supply chain transformation delivers a unique competitive advantage in the form of reliable data, which is becoming increasingly recognized as a prerequisite to successful supply chain transformation strategies.”

The report highlighted that, “Traditional applied analytics and visibility software platforms were compromised by not being able to streamline or home in high-quality, grouped source datasets (which in turn provided optimal pathways for accelerated machine learning and broader applications of AI techniques).”

The ClearMetal’s CEO also added, “Supply chain data has historically been unreliable and inaccurate, which inhibits visibility and transformation. Traditional solutions have aggregated and presented deficient supply chain data – resulting in inadequate visibility and sub-optimal inventory decisions. ClearMetal directly addresses this by solving the underlying data problem. We apply machine learning and AI to clean and make sense of underlying supply chain data to ensure accuracy and reliability. This becomes the foundation of the visibility solution we deliver and the strategic transformation we help usher in.”

Such an innovative start-up to watch out, right? Now it’s time to move on the most critical part – to take a deeper look over the industry data challenges and the approach ClearMetal has adopted them to be “riding on the crest of a wave”.

Data: The Challenge to Change

First of all, let’s hit the ground running with the big picture of the logistics and supply chain world!

1. Industry Overview: Some Highlights

Supply Chain Transformation

Over the past few decades, supply chains have evolved from a just “sub-function” of manufacturing and sales into a business process that generates real sources of value for customers.

Such evolution seems to be most evident in e-commerce, particularly…

● Nearly 80% of Americans now shop online

● Approximately 38% of Americans expect free two-day delivery

● Around 24% expect same-day delivery

● And up to 44% of all U.S. online sales in 2017 came from Amazon

The businesses that timely optimized their supply chain operations to deliver on these demands have reaped tremendous dividends. The key to this agile supply chain is data – a data-driven supply chain is efficient and proactive, driving better performance as well as greater customer satisfaction.

There is no denying that supply chain remains the epitome of Big Data; yet, the most challenging problem companies face these days is access to good, quality data – that’s exactly what they need to optimize their supply chain processes.

“One of the biggest challenges is having many companies around the world specializing in one thing – but they’re faced with a new set of challenges regarding data and dynamic environments that are best handled with software. These companies don’t know how to use that. There’s just a natural ‘innovator’s challenge’ some of the biggest companies in the world have.” – Adam Compain shared at the Connected Enterprise podcast.

Supply Chain Visibility Trends

The recent shift in consumer demand and expectations challenges every stage within the supply chain landscape. To handle these challenges, mastering “industry visibility” is a “must”!

Supply chain visibility does offer companies a clear view of inventory as well as the activities involved in the transport of that inventory. Those that lack visibility across their supply chain are likely to be consistently reactive to adverse events because they are either working from incomplete data or unable to leverage what data they do have to their advantage.

As it provides the ability to assess problems ahead of time, true visibility empowers logistics planners to manage risk and map out contingency plans. This is near impossible without complete, accurate, and timely data and a visibility software to leverage it. The power and impact of these technologies are unquestionable but even the smartest, most powerful supply chain management solutions are meaningless if they rely on low-quality data.

After all, it is data that matters!

2. The Data Challenges

As previously mentioned, supply chain intelligence should enable smarter decisions that impact business profitability and customer service, but when those decisions are based on faulty data, the end-to-end supply chain is affected. How can you trust your supply chain intelligence if you can’t trust the data behind it?

Let’s take a closer look over the typical data issues which have been plaguing the whole industry.   

Data Access

The first challenge all shippers, including retailers, manufacturers, and 3PLs alike, meet is to “mine” for raw data. In fact, supply chain and logistics personnel spend thousands of hours calling different trade partners, emailing, and searching for data on their shipments.

There is a common misconception that there is no data available, which isn’t true. Actually, there are several sources of data available, the matter is that the critical data required to make decisions is often hidden in siloed systems – or simply not made available because it is solely owned by third-party providers who have traditionally withheld that information.

Without a centralized data source, industry insights are difficult to gather and hidden value within the supply chain also cannot be uncovered.

Data Quality

Once data has been made accessible, the quality of that data must be determined!

The majority of the data pulled from the vast network of disparate supply chain systems is riddled with holes, duplicates, errors, out-of-date information, and latencies that easily result in complications and process disruptions when leveraged by existing visibility solutions. To ensure its integrity, the data must go through an adequate enrichment process. Cleansing, standardization, normalization, harmonization, and mapping is key to generating trustworthy insights.

Next Steps…

If you have already resolved all the data issues and gain access to clean and accurate data, what should you do next? Bear in mind that it’s not just data but also what you do with it that matters!

Once essential data has been collected, the powerful supply chain platforms available can be utilized to deduce insights and make proactive decisions. The questions are: What are the right metrics for you to focus on? Which specific technologies will help get those metrics?

The supply chain technology landscape is vast and it is more than vital to figure out a solution that is best-suited to the needs of your business as well as the customers. The capabilities and costs are varied so due diligence is required in selection. Given that, the best place to start is making sure that the key metrics that drive your business are addressed by whatever solutions you select!

Should you be still vague about this, ClearMetal shall be your perfect example.

3. ClearMetal: The Data-First Approach

Whereas approximately 35 to 40% of all global transportation data is inaccurate, ClearMetal has managed to maintain its data quality and hence establish strong customers’ trust. In 2018, they conducted a survey with all of our customers, asking every user of the ClearMetal application, “Do you trust the data in ClearMetal?”- and amazingly, 100% said yes.

Again, ClearMetal is not just about collecting, aggregating, and showing information – they’ve made huge efforts to offer a supply chain solution that has addressed the data problem, delivering data everyone can trust so that true visibility can finally be achieved. Let’s go through some examples of how they uniquely cleanse and correct the global transportation data! 

Automatic Rejection of Inaccurate Data

 So often, inaccurate transportation data does occur because of hard-coded rules and/or the system architecture of technology stacks. These systems cannot make sense of the data. Also, logistics service providers will likely write in hard-coded rules to meet customer service-level agreements or SLAs. 

While many supply chain vendors claim to have “AI capabilities”, only ClearMetal can actually offer a solution automatically filtering out incorrect statuses and standardizing these statuses across all carriers. This technology is patent pending.

To be more specific, ClearMetal purges more or less 26% of incoming transportation data as their platform identifies them as incorrect. Such accuracy can be proven across global transit lanes, from millions of data points, across all their customers.

Improvement in Complete Data

Incomplete transportation data is a consequence of the constricted flow of data through brittle, outdated integrations between carriers and shippers – data gets corrupted or lost. To get over such an obstacle, ClearMetal has employed machine learning algorithms to cross-reference IoT data, allowing them to accurately determine the right milestone events.

For instance, ClearMetal realized that up to 18% of the time, shippers never received key vessel events. The predictive logistics company filled in these gaps automatically and in real-time, with all global shipments, improving completeness by whoppingly 66%. 

Improvement in Earlier Data

Last but not least, latency stands amongst the most common issues that supply chain businesses usually come up against. Latency occurs because of delayed event logging, the time taken to manually cleanse the data, or the complexities involved in data transfer between multiple legacy systems. So, how to completely solve it?

ClearMetal has established direct integrations with the top carriers and applies purpose-built machine learning to ingest, correct and enrich shipment data in real-time, without humans or brittle maps. For example, analysis has shown that ships are at port for 1.5 days on average before anyone knows that they have arrived – ClearMetal has reduced this by 88%, up to only 4 hours.

The Bottom Lines

“The logistics industry has been in need of support from a true digital perspective and ClearMetal’s data intelligence platform successfully provides it,” said Frost & Sullivan Research Analyst Sankara Narayanan. “This platform, by leveraging advanced AI, machine learning technologies and massive volumes of data, simplifies the overall supply chain complexity, enables a highly accurate and granular prediction of global trade events, improves supply chain management and efficiency, and drives profitability.”

ClearMetal was initially found with a view to overcoming the pressing industry challenges of overwhelming complexity and uncertainty through AI and machine learning – up to now, undoubtedly, they have well accomplished such missions. Should you be an enthusiast within the shipping community and look for a role model to learn from, ClearMetal can end up your seamless match!