If you've got supply chain challenges, artificial intelligence (AI) could offer a solution. Small businesses notoriously suffer from supply chain inefficiencies. The high cost of shipping and buying small quantities of goods, unreliable delivery times, supply disruption and lack of clarity into stock are a few of the issues that eat at their margins and affect customer satisfaction.
“Small businesses get penalized all the time on on-time deliveries because demand signals aren't accurate," says Joe Bellini, COO of One Network Enterprises, a supply chain network technology vendor in Dallas, Texas. Information latency delays their ability to respond to customer demand, and drives cost and quality issues throughout their product development process, he says. “It makes it hard to be efficient."
AI can help address these risks by providing transparency at every step of the supply chain, so businesses know where to focus their resources.
How It Works
AI platforms use machine learning algorithms, which are tiny pieces of software designed to find patterns or red flags in large relevant datasets. For example, an algorithm built for supply chain management could determine whether an impending storm system will delay shipments, if suppliers are falling behind in production of a critical component, or if commodity shortages are going to drive up costs on a vital ingredient or material.
In other cases such algorithms can provide visibility into an organization's own operations, says Jeannette Barlow, VP of strategy and offering management, supply chain solutions for IBM in Boston. “It gives you access to insights you can't get from spreadsheets," she says.
She recalls working with a mid-size maker of electronic kits that had recently acquired a new business and was suddenly missing its production goals. It forced them to pay for expedited shipping costs and to hire additional customer service reps to field growing customer complaints. “It all occurred because they had no visibility into when a specific part would arrive to assemble the kits," she says. Using IBM Watson's AI solution, they were able to link their disparate ordering systems, with external data on weather trends and shipping schedules to predict when parts would arrive and to proactively alert customers if there were going to be delays. “It changed the entire customer conversation," she says.
Whether you are a small business or a big corporation, these solutions have to be grounded in business problems that you are trying to solve.
—Jeannette Barlow, VP of strategy and offering management, supply chain solutions, IBM
More advanced AI tools can even suggest “the next best action," Barlow adds. For example, they could suggest how to reprioritize orders if a delivery is delayed, whether to lock in commodity prices when markets shift, or whether to reroute shipments to avoid gridlock. “The real pay-off of AI is that you finally can use that data to achieve 'on time in full' delivery."
Not Enough Data? No Problem
The challenge in deploying AI for any application is that you need enough data to train the algorithms and identify trends. For big companies this isn't a problem, but smaller companies may not have enough quantities of data about clients and suppliers to make meaningful predictions.
Or at least that's the theory.
In reality, there are lots of datasets and data providers that small companies can use to leverage AI in their own supply chain workflow. Many supply chain management vendors provide access to industry data, and now offer AI tools that customers can use for their own analysis, notes Bellini. For example, One Network uses machine learning algorithms to monitor real-time industry data and share it with all of its members so no one suffers from data latency. Instead of planning based on past experience, they can predict customer demand and respond accordingly, he says.
Other vendors leverage AI internally to offer more agile and cost-effective solutions. For example, Oren Zaslansky, CEO of Flock Freight in San Diego, is recreating the 'less than a truckload' (LTL) freight environment for small customers. “If you need to move four pallets of product across the country it's expensive and slow," he says. Small customers are at the mercy of traditional hub-and-spoke models, where their product is shipped from terminal to terminal and faces constant delays as it waits to be loaded into partially-full shipments.
Flock Freight replaced that model with a platform that uses AI to figure out which customers need product shipped on which routes so they can ship it all in a single trip. Zaslansky's team built algorithms to predict when customers will need shipments picked up in the future, and to calculate the benefits of lowering rates on certain trips to encourage more customers to take advantage of it. “We are using AI and machine learning to address a specific use case for small businesses," he says. “Their shipping rates go down, and their on time delivery goes up."
Finding vendors who solve these kinds of clearly defined supply chain problems is the key to generating value from AI and machine learning, Barlow says. “Whether you are a small business or a big corporation, these solutions have to be grounded in business problems that you are trying to solve."
A Problem-Based Approach
Before choosing any vendor or AI-based platform, these experts suggest going through the following steps to be sure the technology will add value to your workflow:
- Educate yourself. Before vetting any vendor, Barlow suggests checking out university educational resources and supply chain conferences to learn what AI can do for supply chain management and whether it's a good fit for your organization.
- Identify obstacles in your own supply chain. Once you know what AI can do, look at where inefficiencies pop up in your own operations, based on decisions you are forced to make based on bad data, suggests Bellini. These insights will define the business case for AI and help you vet potential vendors.
- Look for solutions, not bells and whistles. Vendors should be able to walk you through their offering and show you exactly how it will address your needs, Zaslansky says. “If they only explain the features and not the benefits to your business, that's a red flag."
The big message, says Barlow, is that AI is not going away. “It is already in practice, and it will soon become absolutely essential to any organization that wants better insights into what's going on in their supply chain," she says. Starting early can give small businesses the edge they need to level the playing field.
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