14 January, 2019 | Written by: Roger Needham
Categorized: Artificial Intelligence
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At this point, supply chain professionals might be getting a bit impatient with AI. You’ve likely heard how this technology is poised to revolutionise the supply chain. But as a supply chain professional, you’re not working in R&D; you’re responsible for P&L. The obvious question is: what’s in it for me and my bottom-line performance? Supply chain professionals need to understand how AI will reduce costs and/or increase revenues.
To answer this question, we need to back up a bit. While various sectors have very different concerns, there are some challenges that affect nearly all supply chains. I’ve worked as a supply chain practitioner, myself, with a large industrial manufacturer and with one of the world’s largest transportation services companies. To my mind, there are four challenges all of us understand very well, whether we are moving consumer goods, food and beverages, or cars.
- Visibility. Where are all of the moving pieces at any point in time, from our suppliers to our warehouses to our carriers and finally to our customers? How could improved visibility impact core cost and revenue components across the business?
- Sales. Could improved visibility of the total supply chain help us to get the right products in the right place at the right time, based on our specific demand profile? Could we then hit product launch deadlines with more certainty?
- Inventory. A lack of inventory visibility can lead to increases in working capital – the lifeblood of any business. If there is an issue with inventory, how do we fix it? And if we can’t fix it right away, how do we interact with our customers and suppliers in a way that protects these critical relationships?
- Change. Keeping up with the pace of change is a constant issue. The acquisition trend in our industry means we are frequently incorporating new supply chains and systems, and building bridges between platforms, all the while ensuring on-time delivery and minimising costs.
Right now, solving these challenges involves a combination of dashboards and ad hoc decision-making. The dashboard alerts you to a problem. You reach out to subject matter experts and come up with the most efficient resolution. (Much of this happens via email.)
There are two problems with this mode of problem solving. One: you’re limited to the internal data your dashboard is tracking. Two: once that problem is solved, the knowledge and insight that helped fix it disappear. If the same problem happens a year later, you’re starting from scratch, especially if people have changed roles or left the company altogether.
AI addresses both of these problems, helping supply chain professionals do what they do best – but more efficiently and with better data.
Specifically, IBM Watson Supply Chain brings in a broader range of data to help you quantify the impacts of any incident. For example, if the two cities most critical to your supply chain are Shanghai and Rotterdam, Watson can track world events – weather, geopolitics, finance and more – that could disrupt this specific trade lane flow. It’s not looking at everything for everyone; it focuses on the parts of the chain that matter most to you. Ultimately, you improve your awareness of potential issues while sharpening your calculations of the impact on your business.
Next, Watson captures all of the conversations, inputs and outputs used to solve the problem. This institutional knowledge becomes permanent and searchable, so you can reach an even faster resolution if the same problem happens again. In fact, Watson will learn from this data to recommend better alternatives.
IBM is already taking advantage of AI in this way. After a Japanese tsunami disrupted our supply lanes in 2011, we asked ourselves how to get better insights. IBM Watson Supply Chain is the result. We created a transparent supply chain app that alerts key decision-makers when disruptions occur. Then we collaborate in a virtual “resolution room” to share expertise, get real-time updates and make quick decisions. All of this detail gets fed into Watson for future decisions. To date, we’ve reduced our data retrieval times by 75 percent and saved $40 million in freight and inventory costs.
Other customers are benefiting from AI too, like Lenovo, which is using IBM Watson Supply Chain Insights to rapidly predict, assess and mitigate the risk of disruptions to its supply chain. With AI, Lenovo can shrink average response time to supply chain disruptions from days to minutes – up to 90 percent faster than before.
To bring it all home: AI can help supply chain professionals make better decisions more efficiently in a more repeatable way over time. It doesn’t replace people; human expertise is too vital to the process. What it does instead is augment your team’s capacity and capability, so you can spend more time resolving issues and less time gathering data and responding to emails.
AI may seem a bit futuristic, but it’s certainly not an abstract concept – it’s here and now. And it can provide a demonstrable bottom–line impact across all supply chains structures.
To make AI relevant to your supply chains, download IDC Technology Spotlight: The Path to a Thinking Supply Chain.