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As the COVID-19 pandemic creates record-breaking bottlenecks in companies’ supply chain logistics networks, while simultaneously forcing them to adapt to changing customer expectations and demand patterns, San Francisco-based Alloy is helping customers weather the evolving environment.
I spoke with Cindy Chow, Alloy’s marketing director, to gain a better sense of how the startup is helping its customers.
The problem Alloy solves for customers
Chow explained that “Alloy’s customers are consumer goods manufacturers that sell through multiple channels, including traditional retailers, online retailers, owned stores and direct-to-consumer (DTC). They range from enterprises, like Ferrero and Valvoline, to midmarket companies, like quip and eero.”
“We solve a ‘simple’ problem that every company has: Reality is going to differ from whatever you plan for. For our customers, who have a complex supply chain with retailers, distributors, logistics providers, manufacturing and material sourcing, solving this problem is more complex. Each time things don’t go according to plan, it takes them too long to respond and the costs pile up,” she said.
“What’s more, reality is deviating from plan more and more often. Both constantly shifting consumer demand and supply shocks that are felt worldwide regularly throw supply chains out of balance,” she added.
What this means is that it is getting harder than ever to ensure products are available where and when consumers want them.
Chow says, “Retailers have responded by putting the pressure on suppliers to do so. Brands have been trying to keep up and align supply with increasingly unpredictable demand, but largely by using status quo techniques such as: Operating in functional silos, relying on retail orders rather than sell-through point-of-sale (POS) data, and relying only on slow sales and operations planning (S&OP) processes.”
According to Chow, what this means is that companies are not solving the underlying issue: the disconnect among all the players in a supply chain network. Each company has its own datasets and processes that are siloed from its partners. Even within a company, different teams — sales, supply chain planning — are often disconnected from one another.
“As a result,” she explains, “it takes too long for deviations from the plan to reach the manufacturer’s supply chain team, if they see it at all. And once detected, they struggle to get the data they need to identify a solution and drive collaboration to respond quickly.”
This is the dreaded bullwhip effect discussed in this column in the context of the 2019 chicken sandwich wars.
Alloy solves this problem by acting as a central nervous system for the supply chain. It automatically collects and makes sense of real-time signals, from consumer demand through your supply chain, to alert you to important insights.
In Chow’s words, “Ultimately, Alloy helps customers close the gap between plans and reality through better planning, better execution against that plan, and a better feedback loop between the two.”
Alloy’s secret sauce
Chow said, “A big part of Alloy’s ‘secret sauce’ is the way we directly handle the problem of the lack of high-quality data for AI and machine learning. Machine learning models are only as good as the data that they are trained on. Thus, any company serious about applying artificial intelligence or machine learning must have a robust dataset as a starting point. Instead of leaving our customers with that problem, we take care of it for them to help ensure our machine learning can produce valuable results.”
According to Chow, the Alloy Data Platform automatically integrates and harmonizes data so it’s ready for use for machine learning and other applications. The platform is depicted in the following diagram.
Describing Alloy’s technology in more detail, Chow said, “We have pre-built connectors to collect demand and supply data at the most granular levels, in real time for our customers. We can extract data directly from traditional retailers, e-commerce, distributors, 3PLs and a company’s own enterprise resource planning systems, and validate it as it’s loaded into Alloy. In particular, retailer POS data is a critical input for consumer goods manufacturers. It is the best demand signal to understand current and future demand, and thus to feed into machine learning models.”
Chow explained that retailers provide POS data in different formats and levels of granularity, using retailer-specific terminology, and many brands struggle to aggregate and harmonize it for use.
She explained that, “The modeling layer of our platform processes these volumes of inconsistent data and transforms it into information that can actually be understood and used by business teams.”
Chow emphasized, “Overall, Alloy strives to help our users focus on what matters, provide intelligent recommendations, and drive better execution. Learning and problem solving are critical at each step of this process, and we believe ML is an important way of driving value, but not the only way!”
What customers are saying
I asked if there are customer success stories Alloy could share.
Alloy has been selected by Ferrero, the world’s third-largest confectionery, after demonstrating that its software could yield a 5% or greater bottom line improvement for Ferrero.
Alloy has also been selected by Valvoline, the supplier of premium branded lubricants and automotive services, to connect daily demand data with other data from Valvoline’s supply chain, prevent ongoing lost sales, and enhance Valvoline’s ability to perform granular market analysis for each of the stores in its retail network.
If you are a team working on innovations that you believe have the potential to significantly refashion global supply chains, we’d love to tell your story in FreightWaves. I am easy to reach on LinkedIn and Twitter. Alternatively, you can reach out to any member of the editorial team at FreightWaves at media@freightwaves.com.
Author’s disclosure: I am not an investor in any early-stage startups mentioned in this article, either personally or through REFASHIOND Ventures. I have no other financial relationship with any entities mentioned in this article.
