To Optimize Supply Chains, Big Data Must Have The Need For Speed

Supply chain management strategies are top of mind for many organizations at a time when Brexit, trade disputes, tariffs and an overall sense of geopolitical volatility have businesses recognizing the need for resiliency through operations and business partners. In this environment, blockchain has surfaced as a technology heralded by many as the disruptive force that can address some of the modern threats to supply chains, from cyberattacks to vendor risks.

One of the biggest selling points of distributed ledger technology (DLT) is its ability to preserve the integrity of data. Blockchain currently remains a popular choice for experiments (and, in some cases, deployments) of supply chain technologies. However, while KPMG and JDA recently found that half of manufacturers plan to test blockchain within their supply chains in the next two years, Nishith Rastogi, co-founder and chief executive officer of supply chain optimization startup Locus, said blockchain isn’t the right fit for the most pressing concerns of supply chain management today.

“Blockchain gives you an immutable database — the data cannot be corrupted by any one agent,” he told PYMNTS in a recent interview. “But that is not the problem in supply chains. The problem in supply chains is that we don’t have enough information to begin with.”

While digitization has certainly elevated the volume of accessible data related to supply chain and logistics processes, it is clearly not in the best interest of any player within a supply chain to modify that data. A third-party player like FedEx manipulating supply chain data would never be able to move past the broken trust, said Rastogi.

As organizations work to develop supply chain technologies and solutions that address today’s most pressing industry challenges, they should be focusing on the need for more data, he argued. That includes the embrace of the Internet of Things (IoT), where fleet vehicle electronic logging devices (ELDs) and sensors are able to gather and transmit a greater level and quality of granular data, promoting capabilities like real-time product tracking or the monitoring of temperatures as products move.

Naturally, this information must be collected and analyzed, making space for technologies like machine learning and artificial intelligence to utilize that data. What is particularly valuable about these tools, Rastogi said, is that they become more valuable over time. As more information is collected, machine learning solutions become more accurate and effective at providing valuable, actionable insight.

He noted that this is key to areas like supply chain and logistics, which struggle with what he described as the concept of “tribal knowledge.” Information gathered by a warehouse manager will not necessarily be shared with fleet operators, shippers, customs officials or even other members of that warehouse. Machine learning technologies promote the documentation of this data, while also being able to adapt to the daily changes of an environment that impacts the supply chain — whether they be weather patterns and traffic, or an operational change at a warehouse that remains unknown to the rest of the supply chain.

Flexibility and adaptability of data analytics technologies like machine learning are key in today’s volatile climate, but Rastogi noted another key factor essential to effective supply chain optimization strategies.

“One of the biggest trends in supply chains that people are talking [about] today is not just about Big Data, but faster data,” he said. “How can I analyze data in real time, and make decisions faster?”

Only after these immediate concerns are addressed — the availability of data, intelligent analytics of that information and the immediacy of actionable insights — will technologies like blockchain come into play to protect the integrity of this information, Rastogi said.

Locus recently announced $22 million in funding, which will bolster the company’s pursuit of supply chain optimization technologies that Rastogi said will be most impactful in today’s market. The Series B funding — led by Falcon Edge Capital and Tiger Global, with existing backers Exfinity Venture Partners and Blume Ventures also participating — will be used to strengthen its team, and expand globally as the India-based firm sets its sights on North America.

However, while the application of technologies like machine learning, IoT and Big Data analytics is an important component of optimizing supply chains, Rastogi emphasized that it is not the only component.

“Fifty percent of it is technology, and 50 percent of it is change management,” he explained. “I would say the biggest challenge [to supply chain optimization] is mindset.”

Businesses must adjust their thinking of improving supply chain management, and consider the strategy as less of a cost center and more of a profit center. Regardless of the technologies a business implements, though, changing supply chain strategies will have a far-reaching effect within an organization, and leadership must be ready to take charge.

“There will be changes in sales, in finance, in technology — and the biggest hurdle with clients is the leadership of the company,” he added. “They’re often looking at this as a cost center.”