AI enables smarter sourcing

AI enables smarter sourcing

The company has been built through the acquisition of 17 companies over a period of approximately 4 years, has seen continuous strong organic growth from its customers in their target markets of healthcare and consumer packaged goods and continues on the journey of new customer acquisition. Westfall’s corporate methodologies backed by their “stack integration model” certainly advance as it relates to their value proposition but they have also increased the need for continuous improvement in key areas due to their growth. This has resulted in an organizational structure that poses unique and nuanced challenges to the supply chain. The company provides comprehensive manufacturing capabilities, including product design, mold making, injection molding, assembly and more to a wide range of customers, and as David Schultz, executive vice president of supply chain, said, Westfall Technik counts “all the biggest logos” among its customers.

Schultz, whose previous experience includes several senior operational positions and, more specifically, Chief Procurement Officer/Chief Supply Chain Officer for both private companies and publicly traded companies. He has held key operational positions with GE Plastics, Boston Scientific, and ConMed. He was also the president and founder of a packaging company in partnership with Nypro which was later sold after Jabil’s acquisition of Nypro. He began his work with Westfall in February 2022 specifically to help the company steer countless businesses in the same direction from an overall supply chain point of view. After quickly assessing value-enhancing opportunities, he reached out to Edmund Zagorin, CEO of Arkestro (San Francisco), whom he has known over the years at various supply chain events and conferences. During that time, Schultz received regular updates from Zagorin about his company’s new capabilities in applying AI/ML to strategic sourcing. Westfall adopted the company’s predictive procurement program in April, initially easing the platform in the company’s sourcing activities. .

“We started with the strategy of crawling, walking, and running,” Schultz says. Initially, Westfall tasked the predictive platform with sourcing so-called indirect materials — things like laptops and security cameras. After these early successes, Westfall and Arkestro moved into areas of significantly greater complexity.

“Despos de [indirect materials]We said, “Let’s really test this out—working with us on resins, our biggest purchases, and very complex direct materials with a lot of moving parts,” says Schultz. Westfall and Arkestro have teamed up to push the platform where they need it, helping to not only secure lower total costs but ensure continuity of supply.

“It wasn’t just prices,” Schultz says. “It was capturing total value across the supply chain. If you look at historical surveys of senior purchasing officials, price has always been the biggest concern. Last year was the first time it wasn’t priced — it’s operational efficiency as emphasized in a Deloitte Global survey. 2021 CPO. If you get a great price that’s great, but if it doesn’t show, does that really matter?”

Eliminate the time people spend correcting the inevitable mistakes

In the non-AI-powered procurement process, the heavy burden of data collection and comparison falls on people, invoking the inherent potential for human error and arduous corrective measures. “The traditional way that procurement teams interact with suppliers is to ask them for lots of data that is copied and pasted from multiple systems in one submission,” Arkestro’s Zagorin explains. “Then on the procurement side of the cycle, you can create another spreadsheet and look at each row and each view, side by side, using a pivot table. If there is an error; if the supplier misses a value in the price; it is often caught late So out of the process that it is difficult to detect or update it. After all, the error can form part of what is legally agreed upon”

Arkestro works within the systems and processes customers already use by including price and personalization recommendations in the company’s purchasing and workflows. It does this by recommending predictive pricing suggestions to buyers at the item level for any market basket, purchase order, or bill of materials, which can then be communicated directly to suppliers. Arkestro can also direct purchases to preferred suppliers and automate buyer and supplier email correspondence, saving time, attention and resources. The company is committed to standardizing business sourcing, purchasing, contracting and supplier management activities with real-time data standards and “manage by exception” anomaly detection.

“Arkestro actually recommends the price and terms in the supplier’s offer,” explains Zagorin. “Instead of the supplier having to take the time to come up with an offer just to get an opposition, not to mention the procurement team having to check and grade it all, Arkestro proposes an offer that it thinks is competitive, and the supplier can adjust it and submit. By proposing a mutually beneficial price, it reduces of cycle time which gives the supplier greater predictability and gives the procurement team better economics.”

Schultz says Westfall has benefited from using the software from a buyer’s point of view, but he’s also seen how quickly suppliers are drawn to it, too. “Arkestro initially started building this platform with suppliers in mind, which is critical to long-term success,” Schultz says. “If you don’t have a supplier base that believes in the integrity and simplicity of the system, you get nothing.”

Founded in 2017, Arkestro’s first customer was BASF, and Zagorin noted that they have “worked on enterprise-class technology since day one,” including the ability to handle data security, global currencies, and more. While these requirements have remained the same, other aspects of its business have changed.

“Our initial vision was really focused on helping manufacturers and industrial companies improve the RFQ process, as they need to collect and compare quotes for a new product launch, sourcing event, or approval of a large and complex purchase,” says Zagorin.

Early on, the company picked up on the issue of manual entry of error-prone data. “Web forms with manual text fields alone won’t help much,” says Zagorin. “We realized that from a paper-clean standpoint, you need to apply machine learning, behavioral science and game theory to make sure stimuli match. This is why predictive learning is key.”

In the same way that Netflix or Amazon recommends users what to watch or buy based on past behavior, Arkesto works to learn and understand the companies that are publishing it. Where normally, sources can be isolated into different groups within a company, Arkestro hopes to open them up. “Traditionally, companies struggle to learn from their own buying and selling transaction history,” says Zagorin. “You buy a replacement part for a machine in one factory, and when you go to buy the same part, you basically start from scratch. We wanted a recommendation system that learns from buyer and supplier behavior and makes timely, relevant recommendations to suppliers and purchasing teams. The fact that recommendations learn and improve over time is a huge benefit. to our clients.”

Can AI help you better manage the sourcing process?
Image source: Getty

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