The Stream by River Logic

Supply Chain Optimization and Complex Trade-Offs: Expert Interview

January 28, 2019 | By Aaron J. Berg

Supply chain optimization and modeling isn't what it used to be. Optimization technology is getting more flexible, faster and more robust, enabling it to be used for an ever-increasing number of planning and decision-making challenges. In this expert interview with Aaron J. Berg, Vice President Professional Services at River Logic and long-time analytics planning and strategy consultant, we reveal how end-to-end optimization is the single best way to balance complex supply chain planning trade-offs. No other form of decision-making is able to show the unmatched value of supply chain optimization. Learn from real-world customer success stories and better understand if this approach is right for you.(Please note that the video has also been transcribed below.)

 

 

Jeff (Interviewer):      Hello, I'm Jeff Mix with executive platforms; I'm here with Aaron Berg of River logic at the North American supply chain executive summit, welcome Aaron.

Aaron (Respondent):   Hi Jeff, good to be here.

Jeff:      A lot of organizations are having trouble quantifying their trade-offs, how is that impacting their supply chain organizations?

Aaron:     I have the best job in the world, I get to work every day with companies and supply chains that have complexity to them, where there are potential trade-offs of doing A versus B and there are millions of dollars of value that you can unlock in helping companies make proper decisions on trade-offs.

Jeff:     Can you give us an example of a trade-off?

Aaron:     Sure, I'll start real simply, let's say for example you have decided that your customers should be served or your DC should be served by particular production facilities, and you've said I'm going to make sure that I've allocated my demand to the right production facilities. Well if that demand exceeds the amount of capacity for example of a production plant or it causes a plant to have to go into overtime production, that decision of having to source that from that DC to that plant might actually be different.

So how do you decide whether I'd rather pay overtime let's say, between the other plants or spend a little bit more on transportation to source your product from a plant that isn't in overtime. So that's an example of a simple trade-off, it's actually kind of hard to make because supply chain decisions might be made just with respect to logistics without respect to what's going to happen in the production facility. So when we talk about end-to-end supply chain the trade-offs between production and sourcing and distribution of customers can get pretty tricky and that's why it's hard to do.

Jeff:      How do you measure the benefit of trade-offs? 

Aaron:     So as an example in an ice cream company has a lot of demand seasonally, they've got two options on how to satisfy that demand let's say, classically. One would be to start making ice cream in January when it's still cold and put that ice cream into inventory, the other would be not to build up that inventory but then to bring it in a lot of seasonal help, a lot of overtime labor and wages that are probably more expensive than their normal wages and manufacture that stuff as its needed and keep inventory as well, that's a tradeoff across time. The metric, how you would measure the value of that trade off gets a little bit complicated.  

Jeff:      Why? 

Aaron:    Well because you're not just talking about putting material in inventory, having a cost associated with putting it in, keeping the ice cream frozen and then bring it back out you're also tying up cash on the balance sheet, so the value of tying up cash on a balance sheet and comparing that with let's say extra labor costs, overtime costs with labor is a little bit tricky. So now you're talking about the weighted average cost of capital or the opportunity cost of being able to use that capital for something else. So the metric at the end of the day can be a very sophisticated financial one to get to the best answer.

Jeff:      Could you give me an example of a counterintuitive result? 

Aaron:     Sure, a counterintuitive result is really one where the complexity of the trade-off is such that you wouldn't naturally have made that decision; it might have not been the first thing that you thought of. So an example might be in production, if you have two machines and one machine runs faster than the other that's your better machine, so your tendency will be perhaps to put your best production products on that fast machine, it's a fast machine, it's easy to get to the customer, we know it's profitable.

Well a counterintuitive result might be one where you look at the problem and realize that by taking your best product and putting it on your slower machine, that you actually free up enough capacity on a faster machine to sell more of a second most profitable product or another product that could increase your profit even more. So this is one where you wouldn't get the answer the first time around, but by looking deeply into the trade-off you get a counterintuitive answer. 

Jeff:      What does it take to be able to do this? 

Aaron:     Well really two things, so in our experience you need to number one understand your business not understand what's possible within your business, so this means where can I manufacture things, what does it cost to do things, now people have that information. The second most important thing to have in order to accomplish this is to have the analytical power to look through all of the possible trade-offs that exist, so if you can imagine a single business with a few different production plants, a few hundred products, a few hundred supply lines knowing which combination of which is going to give you the best result can be a huge complex problem, so that analytical power you need some real computational power to answer the question.  

Jeff:      And where does River logic fit into this conversation? 

Aaron:    River logic has an extremely powerful platform for this sort of analytics, we are prescriptive analytics vendor that has been in this space for about 20 years and we're now leveraging the power of the Azure platform to provide all the analytical horsepower needed to use this kind of a capability every single day. 

Jeff:      Now I know you've been having a lot of conversations with supply chain executives about these issues, what are some of the key takeaways that you want them to have after they've spoken with you? 

Aaron:    Well there are a couple of points that I think we've been discussing an awful lot and one is this idea of end-to-end supply chain, I'll call it supply chain optimization because that's the business we're in. But end-to-end supply chain to us really means all the way from procurement through production through logistics and through distribution and even sales and marketing in the demand side of the business. Because I think the theme that we're getting from people that we talk to is it’s not just about individual tools to solve individual problems, it's about seeing the bigger picture and making bigger changes, making a bigger impact on the business with the supply chain. 

Jeff:      Could you give me a single takeaway that people should have, having had conversations with you and having watched this interview?

Aaron:    I think it's a no-brainer, I mean this is the wave of the future and the technology is ready to go and this is the time to use it.

Jeff:      I've been here with Aaron Berg of River logic at the North American supply chain executive summit, thank you for watching.

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