This interview is part of our new AI in Supply Chain Management series, where we interview the world's top thought leaders on the front lines of the intersections between AI and supply chain management.
In this interview, we speak with Evan Goldenberg, Co-Founder and CTO of Alloy, to understand how his company is using AI to transform supply chains, and what the future of supply chains holds.
1. What’s the story behind Alloy Technologies? Why and how did you begin?
EG: My co-founders and I started Alloy because, for all their complexity,
supply chains lack a modern technology platform to connect and
optimize them end-to-end. It’s a huge problem, so we knew that we
needed to tackle one area at a time. We started with consumer demand.
Why? Because the entire purpose of a supply chain is to serve the end
customer, and yet this “demand signal” is often poorly and
We spent the first 18 months or so focused on building a robust
platform and scalable data model for future development. We had a few early adopters who helped guide our product. They were excited about how Alloy’s purpose-built solution seamlessly brought together data and analytics, which was something they had always wanted but never found.
2. Please describe your use case and how Alloy Technologies uses artificial intelligence:
EG: Supply chain teams at consumer goods manufacturers use Alloy to
evaluate, predict, and respond to true demand.
Use cases include:
* Multi-tier supply chain visibility. Track inventory levels and
movements from your distribution centers to your distributors’ and/or
retailers’ distribution centers and stores.
* Demand-driven replenishment through a variety of models, including
VMI, CPFR, and informal processes for working with retailers to
influence and improve replenishment. Identify daily order/replenishment needs to meet consumer demand and Weeks of Supply targets.
* Demand forecasting and planning. Scale forecasting and planning to
every SKU, at every location and e-commerce channel, and enable
effective planning collaboration.
Alloy uses AI in a couple of ways. The first is in our data platform: the
data that we get from different retailers is inconsistent and messy.
We use AI to harmonize and translate the data, including mapping
products to the product master, case/unit of measure (UOM) conversions, and logically filling in “gaps” in the data.
The second application is in demand forecasting. We generate forecasts
using dozens of different models and methodologies, including machine
learning/Artificial Intelligence. We then backtest all the models and
identify the best one for each SKU-store combination.
3. Could you share a specific customer/user that benefits from what you offer? What has your service done for them?
EG: Eero, a home Wi-Fi system that was recently acquired by Amazon, has
used Alloy to increase sales and service levels. Prior to Alloy, eero
was using a general-purpose business intelligence (BI) tool that required significant investment from their team to maintain and was only updated weekly. With Alloy, they have increased sales by reducing out-of-stocks in
Alloy takes the burden of gathering and analyzing data off eero’s
Sales Operations team, and lets them instead focus on making timely,
data-driven decisions. Since implementing Alloy, eero has increased
their fill rate at their top retailer to 97% or higher, and
strengthened relationships with all their buyers.
According to the Head of Business Operations at eero: “To succeed
today, businesses need to be able to make data-informed decisions at
every level—that’s exactly what Alloy allows eero to do. Alloy allows
us to proactively manage our supply chain, increase sales by reducing
low-inventory retail locations, and build more rapport with our retail
partners. The support is also world-class.”