Supply-chain planning is undergoing a major transformation, as companies adopt digital strategies to replace manual processes, according to Shaun Phillips, global product manager with QAD DynaSys.

SCB: What are some new ideas that are driving advances in supply-chain planning?
Phillips: In planning, technology is going through a step change in its evolution. We're seeing the advent of transformational types of technologies, such as machine learning as part of artificial intelligence. We're seeing advanced analytics, as well as the coming of the Internet of Things and the connectivity of external devices to the supply chain.
SCB: Technology has always been an important part of the supply chain. It is even more so now?
Phillips: Ten years ago, we had a very inward way of looking at our supply chain. We would use data for developing statistical methods, and for in-house collaboration. These days it's very different. Most of the data we need to make decisions comes from outside our organization. We can connect to it through the Internet of Things and get real-time updates. With the advent of new technology, we can collaborate digitally with stakeholders, customers, suppliers, even consumers.
SCB: What’s driving the need for companies to pursue these innovations to supply-chain planning?
Phillips: It’s a question with many dimensions. We have a lot of geopolitical disruption happening at the moment. We've got the advent of digitization and the technology that comes with it. We have a new generation that’s grown up with mobile phones and access to any data they want. We have the ability to connect with people. It's a new way of thinking.
SCB: What are companies doing to meet these new demands?
Phillips: One of the key innovations is the embedding of smart analytical engines at the core of the supply chain. Supply chain is essentially about decision making. In the past, we had an idea of what the decision would be, and we used data to support what we already thought. Now, advanced analytics is generating actionable insights. Using advanced analytical methods, we can identify outliers and trends that we would not otherwise see.

An example would be marketing into a certain geography, where you’re having a lot of success with a product. The analytical engine can look at external factors such as demographics, average income, and educational levels in that area. It can identify a secondary area where the demographic is very similar, then suggest to you: "Why don't you also launch that product into this region as well?"
SCB: Is “suggesting” really what the technology is doing? Or are we getting to the point where it actually can make decisions?
Phillips: It's a fine line between automation and augmentation. Already today, there are a lot of things that are being automated, such as forecasting and the way we launch products. Things that require major infrastructural decisions are still augmented. Maybe in five to 10 years, they’ll be more automated.
SCB: Are we headed to a world where the system is making more decisions instead of humans?
Phillips: A lot of it comes down to individuals. Millennials have an unprecedented comfort level with adopting machine-generated decisions. We’ll see this become more automated, not just because the technology is getting smarter, but also because people are more willing to accept automated decisions.
SCB: To the extent we accept those decisions, do we understand how they were made by the machine?
Phillips: Very few people have that level of expertise, so there’s going to be a leap of faith. But no more than when you accept a Netflix movie suggestion. Of course, the ramifications of launching a product and picking the wrong movie are totally different.
SCB: Will automation enable planning systems to react instantly to what’s going on in the market?
Phillips: With the advent of cheap, high-capacity communication and many more devices connected to the Internet of Things, we're getting to the point where we're perpetually planning. We're not just creating a plan for a month or week. All that data coming in is telling us that a plan might no longer be optimal, and we have to react to that. It's not a matter of saying, "Here is a problem that's making that plan infeasible." It's saying, "Here is a problem, and by the way, here is the solution and the new plan that you're going to adopt with a minimum of a disruption."
SCB: Will all supply-chain partners be on the same system? Or will we still have organizational silos, and a hard time putting the pieces together?

Phillips: We’re moving to common platforms, especially in industries such as automotive. We talk about end-to-end data visibility and supply-chain control towers that can identify risks and resolve answers to questions across the supply chain. However, I believe that's only part of the solution. Having access to upstream and downstream data is one thing. You need to be able to coordinate upstream and downstream processes, and to do that in a coordinated manner, people need to work to the beat of the same drum. They need some level of workflow that's common among the different stakeholders.
SCB: What benefits are companies seeing now, and what might they see in the future?
Phillips: The benefit right now is better utilization of assets. We should be able to look ahead and predict with more accuracy what we need to do. It might be a transportation asset needing to backload on its return journey. You get better utilization of assets across the board because of digitalization. And with that comes lower stocks.
In the future, you're going to see a shortening of lead times. Consumers already have an expectation of not accepting any deliveries in one or two weeks – we want everything tomorrow or this afternoon. You’ll see a lot more supply chains that aren’t working to a forecast or plan; they're just working in response to a demand signal.