I’m excited about Amazon’s announcement of AWS Supply Chain, a cloud-based, machine learning (ML) powered supply chain management application. What a great opportunity for businesses of all sizes to take advantage of what Amazon has learned from using ML insights to optimize its own supply chain.
According to AWS, AWS Supply Chain will enable users to:
- “Quickly gain visibility across [the] entire supply chain without re-platforming, upfront licensing fees, or long-term commitments.”
- “Make more informed supply chain decisions with machine learning (ML)-powered actionable insights.”
- “Reduce errors by using contextual chat and messaging to collaborate across teams and quickly resolve issues.”
- “Mitigate overstock and stock-out risks to improve customer experiences while lowering excess inventory costs.”
It’s always good to build on a strength, and supply chain is one of Amazon’s greatest strengths (no surprise given its e-commerce DNA). The company’s investment in demand planning, distribution, and logistics is an important component of its customer-centric focus. That’s how it has steadily improved delivery from three days to “next day” delivery, a feat that other online retailers can’t match without charging customers significant express shipping fees.
Here are three reasons I’m looking forward to the release of AWS’s new application, and why it could be an important opportunity for many businesses:
AWS Supply Chain Is ML-Based
What does a machine language-generated recommendation need to be effective? Lots of data. Who has lots of data and knows how to put it to work? Amazon, the company currently responsible for 22% of the world’s shipping value (more than 4.2 billion packages annually).
Investing over time in building containers, leasing aircraft, and acquiring cargo ships, Amazon recognized that to meet its customer service goals, it needed to understand and control logistics and distribution. When congestion plagued the Port of Los Angeles in 2020 and private cargo vessels were delayed up to 45 days, Amazon was the first to use lesser-known ports of entry and truck its product where it needed to go — a great example of how it took logistics data and developed actionable insights from it.
That same kind of creative thinking is in place with AWS Supply Chain, which uses the same ML technology that Amazon leverages internally to extract data from customer’s cloud and on-premise legacy systems, including enterprise resource planning (ERP) systems, existing supply chain management systems, and EDI (electronic data interchange) feeds. It then aggregates that data and identifies risks in the supply chain or in vendor lead times. In a typical business, these systems are rarely all integrated, let alone analyzed in a way that to clearly identify actions for improvement. Someone using AWS Supply Chain will have a more complete set of information from which to make business decisions than if they were using conventional technology.
AWS Supply Chain’s use of ML to continually adjust insights gives the opportunity to create robust forecasts that can be continually tweaked as additional input is received. Robust demand planning is always a challenge because there are many factors that contribute to customer demand. Businesses using the tool will have the opportunity to identify bottlenecks and pain points and take action to adjust their supply chains more rapidly than businesses that rely on fewer, conventional sources of input.
Amazon Software Is Intuitive
Across organizations, people get frustrated and struggle to use the software that powers their business because old legacy systems can be complex to operate by today’s standards. The same people who struggle at work likely are able to easily wire money, book reservations, make purchases online, and easily manage their personal lives. Why? Because a provider like Amazon, which has decades of experience catering to all types of consumers via amazon.com, has created processes that are intuitive and easy to follow. No power users or subject matter experts required.
One expects Amazon to apply this same approach to user experience in creating the supply chain software. Teams within a business won’t have to rely on a handful of power users, which means more information, faster, in the hands of the people who need it.
An Enticing Pay-as-You-Go Model
With no long-term contracts or licensing fees, AWS Supply Chain offers a perfect opportunity for the small- to mid-sized business community to take advantage of ML-generated insights. These companies have often been precluded from using enterprise solutions, because of transition cost, price, complexity, or lack of resources. Amazon’s offer of a 60-day trial will allow businesses to “try before they buy” and create confidence that it is the right solution for them.
I am, however, concerned about the ability for companies to predict the ultimate price of AWS Supply Chain. First of all, AWS Supply Chain runs through Amazon Web Services and charges separately for data storage, supply chain insights data usage, and demand planning data usage. With all these variables affecting price, it can be challenging for a business to predict what its ongoing costs will be.
Nearly 60% of the companies that move to the cloud see higher costs than they expected. The same is likely to happen here. That doesn’t mean there aren’t big benefits that offset those costs, but businesses should understand there are some variables affecting price that may be hard to nail down in advance.
On the flip side, if it doesn’t work out, pay-as-you-go pricing means that companies won’t be stuck with multi-year agreements from which they must extricate themselves.
When I reviewed the AWS Supply Chain announcement and looked at the details as far as they have been provided, I got excited, so I registered to get a preview copy of AWS Supply Chain. Amazon laughed . . . AWS Supply Chain may be enticing to many businesses, but mine is a bit too small to make the preview cut. But I remain hopeful that when it’s widely available, it’s going to be an awesome tool for decision-makers in businesses that haven’t been able to afford, or have been dissatisfied with, supply chain software solutions targeting the largest enterprises.
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