Supply Chain Planning Blog

Run Your Supply Chain without a Bullwhip!

Posted by Cyrus Hadavi on Thu, Feb 26, 2015
bullwhip

Bullwhip or Forrester effect is result of uncertainty and changes in demand that magnify as we move upstream in the supply chain. The farther upstream the supplier is, in the supply chain, the more variations in inventory levels.  Unfortunately this behavior is taken for granted for most industries. Some advocates of Kanban and JIT believe that using these techniques would eliminate such behavior and makes the supply chain more predictable to the extent that large variations are avoided. This is not a true assumption for the following reason. Kanban and JIT are not planning tools, they are execution methods. Hence they cannot be used to dynamically plan ahead of time when there are inevitable variations in demand. When you design your supply chains with a certain demand in mind, then as the demand goes down, Kanban would react accordingly unless your buffers are too large such that much of the inventory will remain unused between stages resulting in excess inventory. If the buffers are NOT big enough to avoid the excess inventory problem, then it is likely that shortages will occur when there is a surge in demand? The buffers are all used up and the pipeline will sit empty resulting in shortages and loss in revenue etc.

Here are some observations and reasons why we no longer have to run our supply chain under the assumption of bullwhip phenomena. We all know that plans are not perfect however re-planning is the key and doing it fast and in parallel is the reason why we can avoid BW effect. This is explained in more detail below. 

From Serial to Parallel

Bullwhip happens because of the serial behavior of the supply chains. In other words each downstream stage tells the stage before it until it gets to the first stage. This delay is one of the reasons for the rise in the amplitude of the inventory. However this behavior can be changed by providing multiple levels of visibility upstream using collaboration tools. Such tools can be set up to send signals to suppliers as far back as needed in order to share with them the trends in demand that are observed in the consumer behavior. Using point of sale information as well as demand signaling and demand planning technologies, the information shared can save suppliers much cost as well as make them a better and more reliable supplier.

Whole vs Segments

Another notion related to parallel analysis of the supply chain has to do with how the buffers are set up at various stages of the supply chain. In contrast to the traditional techniques of each stage deciding on their own inventory levels before, during and after that stage, Multi Echelon Inventory Optimization (MEIO) technology looks at the entire supply chain and each layer thereof in parallel, not in an isolated and serial manner. Using probability and queuing theory it can make fairly accurate predictions as to how much inventory of each item should be at every stage of the supply chain to avoid shortages and/or excesses yielding unprecedented delivery performance while minimizing cost. Such a parallel treatment of the supply chain would eliminate the BW effect and change it to a “stick effect.” MEIO takes into account both the cost and service levels at every stage given the lead-times and interactions between stages to produce a holistic solution not an isolated serial solution. 

Responsive vs Predictive

The more responsive we are the less predictive we need to be. Widespread use of cell phones have made all of us a lot more responsive. As a result we do a lot less planning. How many times have you heard someone saying “I will call you when I get there.”  In the past you had to specify exact time and location to meet up with someone! Today’s S&OP technology allows real-time planning to be more responsive. In other words within hours a new plan can be generated if and when there is a change in demand or supply. Obviously faster planning does not eliminate the time it take to physically build and transfer goods, however it does significantly shorten the cycle time to delivery. Hence it can reduce the potential amount of inventory quite considerably resulting in a more stable supply chain rather than a BW supply chain. This is more of a responsive planning in contrast to predictive planning. 

Risk Factor

The value of an item at the most downstream point in the supply chain is several times higher than the cost of an item at the most upstream location! So if you look at the weighted variation of inventory taking into account cost factors, then the variation in value is fairly constant and not as variable as the quantity depicted in the BW. This is a key issue in balancing the supply chain and risk management. In order to ensure the availability of parts, the upstream locations can take higher risks than the downstream locations. However, the way the supply chains are set up today, the reward/risk ratio is a lot higher for the downstream companies than the upstream suppliers. By making this ratio more equitable, much better and more efficient supply chains can result in terms of adaptability and responsiveness. One way to do this is a commitment to buy a minimum amount within a defined window of time. With this level of confidence, suppliers can assess their own risk and not only ensure delivery of what is needed but take additional risk knowing that they have some level of downside protection.

Although BW effect may not be completely eliminated however the size of the waves can be significantly reduced resulting in a much more stable and predictable supply chain.

Topics: Multi Echelon Inventory Optimization, Supply Chain, Supply Chain Planning, Supply Chain Performance Management, MEIO, Inventory Management Software, Inventory Management, Sales & Operations Planning, S&OP

Not Your Father’s Inventory Management System

Posted by Cyrus Hadavi on Fri, Apr 30, 2010

Inventory Management SoftwareWhen it comes to an Inventory Management system, we have moved to a whole new level of solutions called Multi-Echelon Inventory Optimization systems (see previous posting on Supply Chain Planning Blog).  This technology brought about a big change to the all-critical inventory planning function.  To that end, it has evolved quickly like anything else in technology today. So in this posting, I want to touch on some of the major differences between the MEIO solutions that were initially introduced into the market, and the ones that are available today.
 
Operations research and mathematical programming techniques are great at finding answers but fail to explain why.  This is like your boss telling you what to do without telling you why you are doing it, what the consequences are, and how the decision was arrived at.  As wise as your boss might be, he may fail to see all the different angles, and his "good" decisions are only relative to what he is trying to optimize.  For example, your boss may ask you to increase production of XYZ Widgets since the demand is high.  In his mind he is meeting the customer service goals, increasing revenue, and keeping the production line fully utilized.  So what's wrong with that?  He is optimizing for all of the above criteria, except that XYZ is not a high-margin product.  In fact based on competitive pricing, it is losing money in certain regions, meaning that the more you produce the more you lose!  So by doing this, not only he's hurting the profit levels, but also taking away opportunity to make and sell other high-margin products.  Another simple example, a new line of product is launched and you are wondering how many should be made based on current market demand?  The strategy is to make as many as possible based on supply capacity, in order to capture market share. However, by selling the new line you are cannibalizing the sales of the old inventory-- wrong timing and inventory policy, costing you millions!
 
This process has some deficiencies:
 
1- How do we know that the boss has looked at every criterion that is relevant?
2- What are the alternatives and consequences that may lead to better results for all, rather than a few.
3- Unless you know why a decision is made how can you justify it, and not put the company at risk?
 
First generation MEIO systems were kind of like your boss. They would just say what to do without telling you why you are doing it and what the repercussions are.  Many of Today's MEIO systems have the capability to go much further to explain the results, allow "what-if" analysis, show you alternatives, and most importantly tradeoffs-all at your finger tips, in real-time!
 
When designing an inventory strategy, transparency is needed to evaluate the different alternatives and to examine the impact of the decisions on your enterprise, as a whole.  For every gain that is expected, there might be a sacrifice of other products, as well as customer delivery performance tradeoffs.  The new MEIO systems are no longer that "black-box" that tells you here are your two choices-take it or leave it.  Just like a brilliant analyst, your MEIO system should tell you what happens when you increase production of one line vs. another, show why you need to make more of this and less of that, and explain how you can set your inventory targets to make the best of both customer service levels and reduce cost, at the same time.  But more importantly, it should walk you through your decision scenarios and its financial consequences.  Now this does not sound like an inventory planning system that our father's used...does it?  Don't even get me started on spreadsheet-based systems.    
 
By the way, I am very interested to get some feedback on what you are using in your enterprise for Inventory Planning, today?  And how it's working for you?  So feel free to comment on this posting and I am sure others will share too.
 
If you are interested to follow up on in this topic, there is an informative ePaper called Demystifying MEIO that I highly recommend, at: http://web.adexa.com/multi-echelon-inventory-planning-epaper/ .  Feel free to click and read it at anytime.

 

Cyrus HadaviDr. K. Cyrus Hadavi is the president and CEO of Adexa, for more information about the author please click here.  

 

 

For more information about different types of Supply Chain Planning systems visit: Demand Planning, Inventory Planning, or Sales and Operations Planning.

Topics: Multi Echelon Inventory Optimization, Inventory Planning, MEIO, Inventory Management Software