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Supply Chain Expert Video Series

GAINS ON

GAINS ON is a video series featuring GAINS Co-Founder Bill Benton sharing his supply chain insights based on decades of industry leadership in supply chain planning. GAINS ON allows viewers to learn about the latest advances, processes, and insights that can make your supply chain planning function more impactful and effective. It’s a masterclass for anyone wanting to learn about supply chain planning. 

The on-demand video series includes insights on topics including: 

  • Demand Driven Materials Resource Planning (DDMRP)
  • Inventory Optimization
  • And more

Check back often for new videos to help you master the art of supply chain planning, or follow GAINS on LinkedIn to see the latest GAINS ON videos. 

About Bill Benton: 

Bill Benton, widely recognized as a visionary in the supply chain industry, is known for rolling up his sleeves and solving complex supply chain challenges. He is passionate about bringing practical innovation to supply chain planning using ML and AI. Bill has received several awards for his professional achievements and is a frequent speaker at the Gartner Supply Chain Symposium and other industry events.  

DDMRP

In this Episode of GAINS On, join GAINS Co-founder Bill Benton as he guides supply chain professionals through the shortcomings and pitfalls of Demand Driven Materials Resource Planning (DDMRP).

Part 1

Part 2

Transcript:
(00:00): Hello, my name's Bill Benton. I'm a co-founder here at GAINSystems. Thanks for taking time to join us today. We'll be talking about DDMRP, that's an acronym denoting Demand Driven Materials Requirements Planning.

(00:32): So we're here to talk about a principle that some organizations, including APICS, are promoting for simplified means of improving planning. One is called DDMRP. Some advantages of things like DDMRP as they relate to improving over baseline MRP, which includes usually a fairly simplistic finished goods forecasting process. So sometimes forecasts are a bit optimistic. As well as you know, they often encapsulate simplistic inventory policy measures like certain weeks of supply for certain inventory classes. There are problems that are inherently complex and failing to embrace that complexity and manage it leads to inferior results in terms of lower than feasible inventory terms, more expediting charges, lower service level to your end customers, less accurate predictions for revenue and budgeting. And because of all this, we think that the slight increase in complexity of an advanced system like GAINS is well worth the investment.

(01:44): So the first point worth mentioning here is this idea of multi-horizon planning. So we have the concept of, for example, of frozen slushy and then highly variable liquid period. So in order to solidify transportation plans or solidify sequencing on the floor and manufacturing execution, you might want to freeze your supply plan over a one or two week horizon. Secondly, you might have a slushy period where it varies, plus or minus some amount. And then lastly, you're gonna have completely liquid. And within DDMRP, it's presuming that that these things are, are equally variable across time. So we think this is one area where advanced planning can be very helpful. Secondly, there's the concept of supply sensing. So there is lead time variability and it's important to account for that.

(02:46): DDMRP doesn't always do that. Base level core supply variability management, it's more based on demand variability. But even if that is included, supply variability can be parsed in the segments across time. So, for example GAINS has AI algorithms for supply sensing, and those algorithms can actually reduce variability over the short run and thereby reduce your need for working capital and therefore increase service or reduce inventory of both. So this is quite important element as well that DDMRP doesn't manage. Third, we have the concept of looking across different available inventory before executing more production or purchasing of the given item that appears to be below what's needed.

This can include things like redistribution of excess from other locations, where handling and transporting that excess costs less than holding it, or less than expediting into this particular site could look, look at alternate products where they might be slightly higher cost, but available and much lower cost in acquiring new material, rather than using what's available. These things are very important. And they're related to the fourth element here, which is potentially looking into alternative supply sources. So you might have other production lines that could produce something, you might have different suppliers. It might be higher cost, but shorter lead times, it could provide fill and demand for purchasing. All of this nuance and opportunity really is not typically available in any kind of DDMRP model at all is to be done supplemental, usually in Excel.

Transcript:
(00:00): Hello, my name's Bill Benton. I'm a co-founder here at GAINSystems. Thanks for taking time to join us today. We'll be talking about DDMRP, that's an acronym denoting Demand Driven Materials Requirements Planning

(00:33): Particularly in seasonal environments, but even just with general variability across time. There's gonna be times where you need to pre-build to avoid having less than needed to capacity in the future. One of GAINS' practitioners, for example, has over 50% of their demand in 10% of the year between Thanksgiving and Christmas, they’re a jewelry manufacturer. This type of pre-building, pre-buying, etc., really isn't feasible in the DDMRP construct. Some demands are large project based demands. These are things that are known in advance, are large increments, which will increase variability unless they're recognized and filtered as one-off events that are scheduled in advance. And secondly, there are things like outliers, one-time exports selling off excess, you know, at a low price. These are things where you don't want to plan more inventory just because you have these one-off events that you can see as outliers and/or filter as incremental scheduled demands. So that's the first.

(01:39): Secondly there are simple things that cause variance that can be managed like seasonality. So in a DDMRP environment, fluctuations across the year are seen as variability, no different from gaining and losing customers in many cases, new product launches, right? So that can be seen as not a step function upward because you've now adding a new way of new products that might use the same componentry as existing products, but seen as another false source of variability. And then of course, things like promotions. All of these things can be managed, recognized, and filtered out so that you understand that these aren't random variability that require costly management methods or working capital investments, but things that can be dissected and managed. Now, that said, you do need to manage around that core variability that can't be managed and discerning between the two is essential.

(02:37): Prioritizing given scarcity. So if you're trying to fulfill as much demand is feasible where you can't fulfill all the demands and you have to make decisions about which components cure or produce or which items to expedite for distribution or sales order. Understanding the interdependencies between items that go into a same bill material or interdependencies between items on the same sort of perspective sales order isn't at all managed by DDMRP. So again, that's, that would be a large manual effort to say, I have these shortages. How do I combine shortages of these items across other items in a BOM or bill of distribution or bill of sale into a complete perfect order. I want to thank you for your time today and would love to chat further about all of these topics. Thank you.