Consumer demand for smart technology is surging, driven by a range of factors that include growing interest in home automation and the dizzying pace of innovation that introduces new IoT products with irresistible features seemingly every day. As demand for digital assistants, wearables, and connected appliances grows, so does the need for the components that give them life. Semiconductors, motors, batteries, and other enabling technologies are necessary to keep the digital economy firing.
However, a lot of electronics manufacturing relies on a variety of raw materials, some of which are quite exotic. These materials are often sourced from specific regions around the world, and their extraction can have significant environmental and geopolitical implications. Cobalt, for example, is needed for lithium-ion battery production, and more than 60% of the world’s cobalt supply comes from the Democratic Republic of the Congo (DRC). Similarly, most of the world’s gallium, which is used in semiconductors and LEDs, is produced in China. This regional concentration leaves the global supply vulnerable to disruptions, as demonstrated last year when China's Ministry of Commerce announced export controls on gallium.
Scarcity and Its Potential for Disruption
In addition to these sourcing headwinds, the skyrocketing demand for resource-intensive products like EV batteries and ubiquitous smartphones and tablets is forcing manufacturers to come up with strategies to address mounting supply chain challenges. The ripple effects set off by these disruptions cause delays in receiving these raw materials, resulting in late production orders and, ultimately, delivery delays.
On-time delivery (OTD) is our industry's North Star metric, and artificial intelligence (AI) can help manufacturers mitigate these supply chain risks.
Using AI to Close the Blind Spots
The global race for technological superiority is reaching a fever pitch, with intense competition among a few key countries vying for economic growth and influence. If U.S. manufacturing is going to thrive in this new era of supply chain uncertainty, it’s going to be because of AI. Integrating tools with AI capabilities will help manufacturers bridge the gap between their ERP systems and supplier networks and give full visibility into the things that are in their control. Closing these blind spots will eliminate much of the risk that causes up to 70% of supply chain issues before products even ship.
At SourceDay, our core platform is designed to manage risk, and we understand that risk is everywhere in the PO lifecycle management process. Spreadsheets, emails, and outdated processes cause headaches and unnecessary delays even when supply chains are working as needed. But, the complexity and volume that accompany today’s procurement velocity make this approach unsustainable. Even a digital solution that simply surfaces things to be more efficient isn’t enough. With effective, solutions-oriented AI as part of your system, you can predict risks, recommend resolutions, and turn manual processes into precision workflows. But more importantly, it surfaces the things you would never see on your own. Things like an email that failed to deliver, which you might not ever find out about until the delivery date comes and goes. For instance, we know from our experience managing 100 million PO changes every year that when you can get a supplier to acknowledge a PO within a certain time frame, the likelihood of on-time delivery increases by 24%. Being on time is not an accident, and AI can help buyers put the formula in place to improve OTD with a deliberate set of criteria to ensure POs are acknowledged.
Procurement teams can be technology laggards, so introducing AI and the promise it holds can feel like science fiction, especially with the hyperbole surrounding its potential. But this is another area where our experience brings insight. SourceDay has the benefit of having the most comprehensive data set, supported by a decade of managing more than $59B in direct materials spend. We’re also leveraging AI to understand and collate item and supplier data, i.e., analyze disparate data labels to find identical items and suppliers despite the differences in the data. This allows us to continually clean and enrich our existing dataset to build data-driven machine learning models to detect, predict, and prevent risks to on-time delivery.
Human-Assisted AI
It’s important to frame any discussion of AI in terms of autonomy. Our platform is a complement to existing workflows and puts the power of our comprehensive AI models into the hands of our users to gain actionable insights and solve real user problems. We want supply chain professionals to embrace AI not because it’s going to do someone’s job for them or because they’re afraid of being left behind. We want manufacturers to understand that this technology can give them greater control of the customer orders and inform downstream suppliers of issues.
By showing users what happens when you adopt a more intelligent workflow, you give them visibility into the outcomes. So when an action is recommended or when something is automated, you can see the results of that action. Nothing happens in a black box, and this visibility is key to adoption.
Configurability is another key element to integrating AI because procurement teams don’t all operate the same way. Implementing an out-of-the-box AI solution is not likely to be successful. Users want control, so all of our automation has built-in reconfigurability to give them ultimate control.
In today’s frenetic supply chain reality, some things are always going to be outside of our control. However, AI can help address surface issues that need attention so we can eliminate risk and navigate the inevitable disruptions that come with material shortages and other external challenges.
About Tom Kieley and SourceDay
Tom Kieley is CEO and co-founder of SourceDay where he leads with a passion for changing lives by meeting customer needs. As a veteran business owner, Tom knows how to recruit top talent and build a lean team to manage growth. He is also good at conveying company vision and goals to employees, partners, prospects, customers, and industry leaders. But it’s the execution of that vision that makes him such an asset for SourceDay.
SourceDay is a direct materials procurement platform focused on increasing supplier reliability and de-risking Purchase Order Lifecycle Management. Powered by patent-pending AI and Machine Learning, SourceDay delivers enhanced visibility, predictability, management, and accuracy to manufacturers and distributors. SourceDay integrates with any ERP system transforming costly, manual, and often error-prone tasks into precision workflows.
