Talking with supply chain leaders across the industry, it’s clear that supply chain control towers are being tasked with more and more functionality. It’s a natural evolution. After all, control towers collect and leverage large data sets from across the end-to-end supply chain. If data really is the new currency, there must be gold in those hills, right?
As it turns out, not necessarily.
As supply chain networks become more complex, siloed and disconnected systems can lead to troublesome visibility gaps across internal and external supply chains. Lacking insight across all nodes makes it increasingly difficult to interpret the impact of disruptions or opportunities across the network. For many control towers, that lack of true real time end-to-end visibility is an Achilles’ heel.
For other control tower implementations, it’s the inability to understand and leverage signals from across the digital ecosystem. For some others, a lack of effective exception management can cause value erosion. But for most control towers, the greatest lost value is the lack of a cognitive response framework with the ability to continuously learn, sense, predict, and respond to potential disruptions. That functionality is critical to enabling the user to solve potential problems before they impact the business.
How can you optimize the business value of your supply chain control tower?
Fortunately, the cognitive capabilities of machine learning are coming to the rescue. It’s an important evolution, as machine learning can leverage the deep data sets generated across the end-to-end supply chain to find valuable new insights from the noise generated in a typical supply chain network. A cognitive control tower can ingest hundreds of data signals from diverse sources like the Internet of Things (IoT), news, weather, and more, helping users to see possible disruptions before they happen, better sense demand and intelligently adjust supply in real time.
What does all of this mean in terms of value to your business? Visibility to goods in transit and track and trace capability can improve revenue through improved on-time deliveries and speed to market. Having accurate shipment ETAs can improve sustainability, reduce waste, and reduce expedited fees and fines from delays. Having cognitive, prescriptive recommendations based on achieving your key performance indicators can improve overall supply chain performance and efficiency, improve customer service, increase inventory turns, employee productivity and revenue per employee.
In a new report published by Nucleus Research, JDA was positioned as a Leader in the Control Tower Technology Value Matrix 2019. The report “provides a snapshot of the market based on how vendors are delivering value to customers through the usability and functionality of their software.” This Nucleus Research report is particularly insightful as it helps users to both understand what a vendor is bringing to market today and also the vector of what to expect from the vendor in the near future.
In fact, according to the report, “Leading vendors are leveraging machine learning (ML) and artificial intelligence (AI) algorithms that can review historical performance data and the larger contextual picture when exceptions arise.”
Ready to take the next step in supply chain visibility? Discover our Luminate Control Tower.
