Taking a Big Picture View of Supply Chain Networks

This post was originally featured on Logistics Viewpoints.

I recently read a thought-provoking report with several predictions about the future of supply chain technology. As I read through it, I was struck by a glaring dichotomy: Supply chain organizations are expected to double down on artificial intelligence, advanced analytics and various digital supply chain technologies — and yet the report predicts that “through 2023, less than 5% [emphasis mine] of control-tower-like deployments will fulfill their end-to-end potential.”

Let me underscore the obvious here: 5% is a woeful “success rate”. How can it be that so many companies will continue to invest so much in state-of-the art technologies, and yet fewer than one in 20 control tower deployments are expected to deliver on their potential?

My view? Much of the industry at large simply isn’t seeing the forest for the trees. To actually realize the promise of end-to-end visibility and control over our incredibly complex supply chain networks, we need really big picture thinking — particularly when it comes to the supply chain data networks that serve as the foundation for true digital transformation. Here’s what I mean.

Supply chain networks: A big-picture view

At its core, the control tower concept is about “stitching together complex and siloed supply chains” so organizations have greater visibility and better insights to help them run more efficient operations. Real-time visibility platforms are an indispensable piece of the puzzle, and the report predicts that 50% of global product-centric enterprises will have invested in real-time visibility platforms by 2023. But advising that visibility vendors should be evaluated based on “how well they align to the company’s existing carrier network” overlooks several other critical factors that should be part of the calculus.

Without a doubt, real-time visibility into carrier networks is a must-have. But carriers are only one component of a complete supply chain network. Taking a bigger-picture view, there are also other critical elements to focus on when building out a robust supply chain data network:

  • Quantity. Numbers matter when it comes to supply chain data networks. When we launched FourKites more than seven years ago, we were maniacally focused on signing up as many of the world’s largest shippers as we possibly could. Our strategy was to lead with shippers, then onboard their vast networks of carrier, broker and 3PL partners. The more users and the greater the usage, the richer the data set for benchmarking, analysis and, ultimately, insights to help organizations improve their KPIs. More users = more data = more potential value. (Our efforts paid off; today the FourKites network includes more than 500 of the world’s largest shippers and thousands of their partners, generating 1.5 trillion terabytes of new data every day.)
  • Diversity of sources (carriers + vendors + customers). Elaborating on my earlier point, viewing a supply chain network solely through the lens of the carrier component is severely limiting. For starters, I’ve yet to work with a supply chain organization that didn’t prioritize two other key constituents — namely, customers and vendors! A supply chain data network needs to aggregate and share data from and with customers and vendors, too. And it must integrate with a myriad of internal and external systems such as transportation management, warehouse management, order management, ERP, weather and traffic systems and many more.
  • Data integrity. In 2006, British mathematician Clive Humby coined the phrase “data is the new oil” to help make his point that corporate data has the potential to be an incredibly valuable resource. But he also rightly noted that data, as with oil, is just raw crude if it’s not refined. The same is true of supply chain network data, which require the latest data tools and services for ingestion, processing, automation, security and virtualization, governance and the like. Supply chain network data must be complete, accurate, fast and secure.
  • Consumability. Supply chain data is of little value if it isn’t packaged for efficient access and consumption. Role-specific interfaces, advanced analytics, robust search and filter capabilities and exception management are a few of the ways data can be packaged and presented so that busy supply chain professionals can quickly move from data to information to insights and action.

To be clear, achieving the “end-to-end promise” of supply chain control tower capabilities is hard work. But organizations will never achieve anything like robust control tower functionality without first taking a big-picture view that comes from a data network bringing together the right stakeholders. That means unifying quality data from disparate systems, layered on top of artificial intelligence, advanced analytics and other state-of-the-art technologies — all in one modern platform.

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