A.I. Powered Suggestions - A Smarter Way to Execute Your Supply Chain Workflow
Ravacan Product Manager
If you work in supply chain management and operations, you are no stranger to complexity and time-intensive processes. If you use Ravacan, you are already ahead of the curve in that you reduce your need to manage spreadsheets and various types of overhead associated with sourcing and tooling management.
At Ravacan, however, we constantly ask ourselves: can we do more and go the extra mile by delivering more than any other solution? The answer is a resounding YES.
We are excited to introduce AI-Powered Smart Suggestions, the first of several enhancements to our platform that unleash the power of artificial intelligence on your sourcing and tooling management workflows. These Smart Suggestions offer a new way to quickly assign and efficiently classify parts in your system by leveraging state-of-the-art machine learning algorithms.
With AI-Powered Smart Suggestions, part attribute assignments and classification take place automatically as your part data is ingested into the Ravacan platform, whether that’s via the user import or the Arena Integration.
What’s more, in this initial phase of AI-powered capabilities at Ravacan, we’ve decided to tackle one of the most strategic aspects of sourcing and purchasing: Commodity Management, along with its relationship to part ownership in the buyer context.
Commodity Management and Ownership
Strategic supply chain operations teams tend to organize by “commodity,” whether that means plastics, semiconductors, cables, or any other commodity that is relevant to the product in question. Oftentimes, however, engineering organizations will incorporate a part categorization scheme into the part number designation. Because this categorization does not always correspond to the commodities for purchasing, a significant amount of time can understandably go towards appropriately defining and labeling the commodity classification for these new parts, adding to the overall workload for the buyers. This classification process lays the foundation for all downstream workflow operations and is often considered essential.
Furthermore, time is spent on assigning the appropriate ownership of the part. The part owner is synonymous with being the lead buyer, who, among other tasks, takes on the responsibility of sourcing, negotiations with the supplier, and overall supplier collaboration and relationship management. However, specific part ownership on the team can vary and may or may not correspond to commodity ownership. Therefore, part ownership assignment is not a trivial task, and therein lies the opportunity to more efficiently handle these assignments using an approach that saves users time and expedites the realization of value downstream in the supply chain.
Now, with the AI-Powered Smart Suggestions, commodity assignments for new parts in Ravacan are automatically recommended based on a proprietary set of machine learning methods. No action by the user is required to kickstart the automatic AI-powered process. All of the heavy-lifting is conducted under the hood so that the user is shielded from the complexity of the algorithmic classification process.
What’s more, if a part is appropriately designated as “sourced” upon import, the Ravacan AI system goes one step further and automatically recommends the responsible buyer for that part, by name. In addition, the supplier for that part is also automatically suggested based on all current and prior context at the time of data ingestion.
Once assigned, the owner can then carry out the requisite duties ranging from negotiation and price management to demand planning and monitoring, to name a few (all of which are already possible on the Ravacan platform today).
For added flexibility, users will retain the ability to manually input these parameters as well, and in doing so, will allow the Ravacan AI system to learn and more accurately perform these operations over time.
Just the Beginning
With this new capability, no longer will countless hours of highly qualified buyers’ time be spent on data entry that could be avoided. Instead, these users can focus on the downstream work that matters and drives a real impact on your organization’s bottom line.
But this is just the start.
The Ravacan team is listening carefully as our users continue to keep us informed about their biggest challenges throughout the supply chain workflows that they execute every day. With the power of artificial intelligence, Ravacan is committed to unleashing a wave of smart capabilities that will further optimize each step in these workflows, making strides not just in operational excellence for buyers, but also for suppliers and contract manufacturers alike.
Have an idea for how this might apply to your supply chain needs? Don’t hesitate to reach out! Drop us a note at email@example.com.