Supply Chain Planning Blog

Planning is Important, Re-planning is Even More Important

Posted by Bill Green on Wed, Feb 08, 2017

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Planning is the world’s second oldest profession! Why? Because no matter what you want to do, you need to plan for it. You may argue that there are things that you do not plan for: accidents, Acts of God, inventions. However even these are somewhat planned for in case they happen. Buying insurance is a good example of such planning. Perhaps emotions and feelings are exceptions! But even these were planned by nature for our survival. In the world of manufacturing and supply chain, planning is probably the most important aspect of the business since it has to do with getting the right product in the hands of the consumer on time in the right place. In the absence of proper planning the cost can be very high leading to the demise of the business. Despite, the importance of planning, it is not enough to ensure on-time delivery of goods at the lowest cost. This is due to the stochastic nature of events that can change the demand or supply. Examples are a breakdown of an equipment or plant due to earthquake. Or, sudden increase in demand or shortage of supply from a supplier can lend the original plan somewhat under-optimized. Hence the title of this piece which is a quote from General Eisenhower.

We conclude that S&OP is good for aggregate level decisions for things like expected total production required in a month, but not good enough to figure out how much to produce of each individual product along with the capacity needed of each machine type. You need to have accurate plans that can be executed; and while they are being executed the plan is constantly adjusted to account for the changes that were not foreseen by the plan. To be able to do this, one needs S&OE (Sales & Operation Execution) system that can translate the original plan into more and more detail. A typical S&OP plan can only be as accurate as 40-65%. When combined with S&OE, the accuracy can be as high as 98% or better. We have actually performed simulation studies that confirm the above results.

What S&OE does is simply take the constraints defined by S&OP and apply additional detailed constraints in order to make the plan work and more accurate. In this process, it enables the users to see the details of what will be delivered and where and what potential issues need to be addressed, if any. For example, the S&OP Plan may say the forecast for the month of Product group A is 100, while S&OE says how much for A1 and A2 per day.  S&OP says 80 hours of drilling is required, while S&OE says how much of each type of drill is required each week.

Topics: Supply Chain Planning, Planning, Sales & Operations Planning, S&OP, S&OE

Attribute-Based Planning for a Green Supply Chain

Posted by Cyrus Hadavi on Wed, Dec 07, 2016

d0863753-41c8-405a-884f-eef4cc8755d8.jpgAdexa solutions deploy attributes to define the characteristics of machines, processes customers and suppliers, in order to mold the solution to a particular environment. Furthermore, as the supply chain changes and business or business priorities change then attributes are used to adjust to the new conditions. This has been extensively covered in a number of white papers that can be referenced by clicking HERE.  In this paper, we discuss the use of attributes for a greener supply chain and how they may be deployed to improve on the carbon footprint and use of hazardous materials.

Consider a process or an equipment that has more CO2 emission than other alternatives. The value, or relative value of the CO2 emission becomes one of the attributes of that process. On the other hand, cost might be another attribute of the process in a way that the lower cost process may contribute more to CO2 emission. Attributes, once defined, form dynamic constraints that are used by the system’s search strategy to find the optimal solution. The optimal solution can vary depending on the region, government regulations, carbon use quotas and even customer. Within the framework of such restrictions as defined for the attributes, the system can recommend the highest use of lower cost process without going over the CO2 emission limits as decided by the company policy. As alternatives, the system may recommend higher cost processes, use of substitute materials or manufacturing in a different region.

Another example, is the use of different transportation means in order to deliver gas or oil to different regions in Europe. The choices are by sea or land as well as pipelines. Each has attributes of cost, carbon footprint (depending on the distance travelled) and of course time to destination as well as associated risks. For example, it is imperative that oil gets from A to B if it is to be used for heating in the middle of North European winter. Land delivery has a much higher risk of road closures in certain regions.

As a final example, some customers or retailers may have a preference to sourcing products that are eco-friendlier. This kind of requirement is sent to the suppliers as an attribute that is then built into the BOM of the product. On the manufacturing side, the use of such embedded materials in the product is treated as an attribute of the material as well as the product. This attribute is then taken into account and honored as a constraint when plans are made by the system for making and delivery into those customers.

As it can be seen, attributes can be used in order to define local and global constraints on the operations of the entire supply chain including tariffs, carbon usage, supplier types, transportation means and material properties depending on the regions, government/international regulations, and company policy. For instance, a company can reduce the global value of an attribute (say, CO2 emission) by 10% per year by region and product. The system would then plan production of the entire supply chain by making sure that the local attributes used in every region does not exceed the maximum defined by the management of the company. We welcome your feedback and sharing innovative uses of attributes in your supply chain operations.

Topics: Supply Chain Planning, Attribute Based Planning, Attributes, Green Supply Chains

Supply Chain Risk Resiliency

Posted by Cyrus Hadavi on Tue, Oct 04, 2016

risk-dice.pngThere is risk in almost everything we do. It is unavoidable. Supply chains are no exception facing all kinds of unexpected but inevitable surprises. Some can be very costly to the company. It is imperative that the management are prepared to deal with unfavorable issues when they occur without building too much redundancy increasing the cost of operations. In a typical supply chain, having thousands of SKU’s and suppliers as well as other factors such as geopolitical issues, labor related issues and demand volatility, makes the supply chain operation very complex and in the absence of appropriate tools almost impossible to manage in an efficient manner. The key is to identify the potential risks before they happen so that adequate measures can be put in place.

There are many ways to assess risk vs cost and reward. As an example, one can use Multi Echelon Inventory Optimization (MEIO) to assess risk of on-time delivery vs cost. This can be done by SKU and customer. For certain customers, the desired delivery performance must remain at 98% or higher. Obviously this can be accomplished at a higher cost of inventory at different stages of the supply chains. On the other hand, for many other customers, a delivery performance of 90% might be acceptable at much lower cost of operations. As the demand patterns change, MEIO behaves as an almost perfect postponement strategy, to show where and when inventory is needed for a desired delivery performance and cost by customer and SKU. This algorithmic approach, based on probability distribution and queuing theory, is by far superior to the traditional methods of historical data such as moving averages and/or min-max types of approach.

Having visibility into meeting the financial goals of the company is critical. Any risks associated with that must be detected as early as possible and addressed. Likewise, meeting delivery performance for certain key customers, making sure that the right mix of inventory is available to keep the production running, knowing what options are available in case of capacity shortage, or material running out (or not delivered in time) are all factors that may increase delivery risks, increase cost and even cause loss of market share. Optimization models of systems designed to assess the impact of risks can act as a crystal ball to provide visibility to the end users and furthermore provide guidelines and advise end users as to what the best course of action would be. It is a proactive way of responding to potential risks than reactive.

One other critical use of systems is to perform what-if stress tests on the entire supply chain. By either overloading the supply chain model or trying to break certain links in the chain, one can observe the consequences of such events and what can go wrong, what the financial impact would be and what can be done from the convenience of your desk, before it happens! Preventing such potential disasters are how modern heroes are made of in the world of leading companies!  Learn more about Supply Chain Risk Resiliency by clicking this link.

Topics: Supply Chain, Risk Management, MEIO, Enterprise Risk Management, Risk Planning

Where is the E in S&OP?

Posted by Cyrus Hadavi on Wed, Aug 24, 2016

download.jpgWhere is the “E” in S&OP?

According to Gartner, there can be no effective S&OP process without an S&OE—Sales and Operations Execution, process. In other words, why make a plan if cannot be executed accurately or cannot be translated into execution? Here is what Gartner says:

• The No. 1 challenge among manufacturing companies is connecting sales and operations planning (S&OP) to operational plan/execution.

• Value-adding, effective S&OP process cannot exist without S&OE, as it provides the planning interface to execution.

There has been a recent surge of interest in S&OP. The attraction is primarily in integrating sale and operation as well as better visibility into potential issues. However, the major problem with most, if not all, S&OP systems is that they are far from accurate especially when it comes to capacity and mix of products as well as order level pegging. The inaccuracy of plans leads to all kinds chaotic manual adjustments and tweaking just to get it to work. S&OP shows you the direction but cannot take you there! In order to arrive at your destination at the right time and place you need to be able to execute the plan not just get a high level idea of which direction to go. There may be traffic jams, there may be road closings, there may be flat tires; and there may be bad weather and bad road conditions. In all such instances your S&OP plan is inadequate to deal with such inevitable but unpredictable issues and cannot give you any help as to what your best course of action should be. Their best suggestion is “keep simulating and perform What-if” all possible conditions that might occur! This is not a feasible approach!

To be able to perform execution, you need to have:

1- Accurate plans (not just rate-based planning like spreadsheets)
2- Have a unified data model between plan and execution engines
3- Ability to adjust the plan as needed

Furthermore, execution systems, just like vehicles, can handle all the bumps on the road to make the ride a lot easier. Shock absorbers in your vehicles are precisely a method of execution of plans. In their absence, the ride can be extremely uncomfortable. This is often the case when execution systems are missing and people often end up performing all kinds of expediting and manual changes, trying to absorb the “shocks.” Even more importantly, the main issue is that the financial predictions that they had made regarding the plan at the S&OP level is no longer valid and totally false. For example, use of more expensive substitute materials or more expensive freight methods, because of late deliveries, can substantially add to the real cost of products. To this end, the S&OE system needs to have the capability to monitor the financials, as such changes are made, on an on-going basis. Costs based on S&OP alone is wishful thinking and have no resemblance to the actual.
Another important point that was made earlier above was having the ability to translate plans into execution. In other words, a seamless transition between planning into execution. A unified data model in plan and execution systems is a requirement for this to happen. Furthermore, the planning engine must have a realistic model of the actual environment so that the plans are produced in an accurate manner. Current methods of capacity planning which are based on bucketed rate-per-period, is very inaccurate and insensitive to the mix of products. Even if you had two products A and B, if B takes twice as long as A to make, one cannot plan this unless you know how many B’s and how many A’s are needed. An average of X per day or week is very misleading which is exactly what almost all S&OP systems do. In many cases, such as asset-based industries, the actual models of equipment are a must in order to produce accurate plans. Capacity depends on set-up times, batching, availability of tools to be used on the equipment, processing times and so on.

Lastly, almost all S&OP systems cannot trace orders to the components and supplies that are to be used for every order. Thus, the ability to peg orders, to qualify suppliers, and to find root causes of issues and latenesses are totally impossible for these systems! They can only say what is short and which orders will get what is available. In high tech, pharmaceutical and many other industries, pegging to the right supply, to the right supplier and to the right processes are requirements. S&OP systems must be able to demonstrate such capabilities or else the actual execution of the orders would be a nightmare.

S&OP and S&OE are two essential processes that go hand in hand and in the absence of one or the other the whole purpose of having the system is defeated.

For further information on how Adexa’s S&OP and S&OE work to avoid the aforementioned issues, please send an email to info@adexa.com or visit our web site: www.adexa.com

Topics: Supply Chain Planning, Planning Systems, Spreadsheets, Planning, Sales & Operations Planning, S&OP, S&OE, planning and execution

In-Memory Computing—Only the beginning

Posted by Cyrus Hadavi on Thu, Jul 21, 2016

In-Memory_Computing.jpgIn a few recent sessions with industry analysts, we were surprised that we were asked if our software is in-memory computing! Given the fact that for over 20 years we designed our applications to have all the data in-memory for computation, our immediate response was: Is there any other way of doing it? The response was, yes, there are others which bring in the data from the database when they need it but now they are changing and they are getting orders of magnitude improvement in speed! This improvement in speed must have caught the attention of the analysts which brings us to the core subject of this article. There is more to speed of application than just having all the data in memory. The latter is the easy part. There are also some vendors, try to improve speed by abstraction and over-simplification. I am sure you are aware of quite few who deploy “Spread-sheet” type of capacity planning in their S&OP applications. That is forming weekly or monthly buckets with fixed lead-times! This approach typically either dumbs down how to deal with capacity, or ignores it altogether. It is the old method, with NO notion of product mix and real processing time, that has been around for decades but with a new user interface which makes it slightly more attractive. Therefore, any gain in speed is offset by a very inaccurate and unrealistic plan. In addition, it has no order level information OR any order level pegging functionality. You might as well use your spreadsheets since they give you even more control!

 

To gain real improvement in speed with proper representation of capacity of resources and equipment, deep modeling capability is needed and the mix of products must be taken into account. In addition, to IMC, one needs to have data representations and algorithms that provide real-time answers to very complex supply chains at order level. As an example, if one material is not available, does the system go back to search all over again for a new method of making or will it just backtrack one step to find an immediate substitute pegged to that order? If a resource is a bottleneck, will it look for a whole new routing or will it look for an alternative, process or equipment. How this data is represented and how the algorithms divide and conquer in parallel processing is what makes the application fast. Just using IMC is only the beginning, there is a lot more that goes into a comprehensive planning system that can analyze tens of millions of data points from material availability to resources and tools and skill levels, to say a few, in almost real-time.

Topics: Supply Chain Performance Management, Planning Data Integration, Supply Chain Data, Spreadsheets, Attributes, Sales & Operations Planning, SCP System, S&OP, Adexa

Spreadsheets and Planning

Posted by Cyrus Hadavi on Wed, Apr 06, 2016

Givspreadsheet.jpgen that more than 90% of the enterprises in the world use spreadsheets in one form or another, one may conclude that spreadsheets are the most desirable and successful enterprise software in the world! So, why would you want tospend so much money and effort to invest in planning software? The justifications to use spreadsheets are that they are simple, easy to manipulate and they “do the job!”  There are a number of reasons, discussed below, that make spreadsheets inadequate for planning purposes. Mostly the fact that just an ad hoc plan can be far inferior to other more optimized plans; and in the absence of suitable systems and algorithms, one cannot tell one from the other. I am sure you have heard of the expression: good is the enemy of great! In case of spreadsheets, it is merely the perception of good that is preventing companies to do something exceptional and distance themselves from their competition! It is amazing that companies invest hundreds of millions of dollars in people and equipment and then rely on a simple spreadsheet to run their business and make use of the resources that they have so heavily invested in. Every one percent improvement in plan can translate into millions, if not tens of millions, of dollars in inventory savings and higher utilization of resources. In fact, it is more than just savings that need to be considered; it is more relevant to know that there are opportunities for increasing revenue and market share, by deploying adequate planning systems. More recently companies have been investing more heavily in supply chain execution systems such as warehouse management and logistics or even shop floor sequencing. The problem is that executing without a good plan results in a more efficient way of doing the wrong thing! What is the point of building and delivering the wrong goods to the wrong place in an “efficient” manner? Planning prevents making costly mistakes, it makes companies more responsive, it shows where to spend money before it is spent and it creates opportunities to expand market share by having the right product at the right place at the right time. A multinational CPG customer of Adexa with over 100distribution centers reduced inventory by 33%, reduced material cost by 5% and improved delivery performance by deploying planning systems that enable optimization and improve visibility of the entire supply chain. ROI for the project was over 2100% realized within half a month! The point is that before deploying Adexa, they were running a successful and profitable business but could not see the hidden potential of their supply chain and opportunities that could be exploited using a more sophisticated system.

There are many reasons that make spreadsheets less than ideal for planning purposes. Spreadsheets cannot account for mix of products (different mix results in different capacity needs and different lead-times). They assume fixed lead-time whereas in reality lead-times are variable depending on the mix. In addition, they do not take into account availability and synchronization of material and capacity at the same time. Furthermore, there are myriads of other constraints such as tool availability, setup times, batching possibility, process and product attributes etc. that all need to be accounted for that spreadsheets cannot model. Many users are fond of spreadsheets because they can manually manipulate the plan.  The question is why is there a need for manual interaction? The answer lies in the fact that the plan that is being created is not accurate enough to execute therefore requires manual adjustments.  The planning systems create an accurate and near-optimal plans such that little manual effort is needed.  Finally, spreadsheets cannot perform incremental planning, dynamic allocation and ATP/CTP, and the underlying models are static, deviating from reality the more they are used. As an example, one of our clients used to take up to two weeks to figure out delivery dates of orders to respond to its customers. It would take about a week of spreadsheet planning in their HQ in US and another week with their subcontractors in Asia. After they started using Adexa’s planning engine, the commitment dates to their customers have been practically instantaneous and more importantly accurate and reliable.

With the recent innovations in processor speed of computers and advances in programming and Artificial Intelligence, we are now in a position to accurately predict inventory requirements at every level of the supply chain by considering the probability of usage of every part# from raw material to WIP to finished goods. This allows companies to keep the right amount and mix of inventory at different stages of supply chain to maximize responsiveness at lowest cost of inventory. Such disruptive technologies help to save tens of millions of dollars in inventory cost and improving responsiveness dramatically.

When it comes to efficiency, use of spreadsheets to perform planning function is probably as good and efficient as using a bicycle to travel from Los Angeles to New York city! It gets the job done but …

Topics: Supply Chain, Supply Chain Planning, Inventory Planning, Excel, Spreadsheets, WIP, Manufacturing Planning, Inventory Optimization, CPG, Factory Planning, Material Planning, Scheduling, Business Planning, MRP

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

Inventory Optimization is like Baseball's Moneyball

Posted by kameron hadavi on Wed, Oct 10, 2012

iStock Baseball Money XSmall resized 600

How do the Oakland A’s achieve results like this at a fraction of cost of a team like the Yankee’s?

2002 New York Yankees: Team Salary $126 million; 103 Wins 59 Losses; Division Winner
2002 Oakland Athletics: Team Salary $ 40 million;   103 Wins, 59 Losses; Division Winner
2012 New York Yankees: Team Salary $198 million; 94 Wins 68 Losses; Division Winner
2012 Oakland Athletics: Team Salary $ 55 million;   93 Wins, 69 Losses; Division Winner

You have most likely seen or heard of the story behind the movie “Moneyball”.  In 2002 the Oakland Athletics had a very limited budget to “carry” their team roster through the season, and they still had to compete with topnotch teams in their league.  Some of the teams they had to compete with, like the Yankees, spent up to four times (4x) as much as they did on their “inventory” of ball players (i.e. “products” in baseball).   The A’s turned away from traditional thinking on how to allocate their budget to field a team, which meant relying on the gut feel of managers and buying the highest priced players.  Instead, they started to rely on “Sabermetrics”, the use of statistical analysis to determine the most cost-efficient baseball players based on measure of in-game activity/history.  Hence, based on mathematical models, the A’s figured out how to best optimize the team at every position on the field.  The result was that Oakland won 103 games in 2002, made it to the playoffs, and tied with the Yankees for most wins that season. Again, Yankees spent more than three times (3x) of what Oakland paid for its team, in the same year.

 
Coming back to the manufacturing world, in the same manner that Sabermetrics can help optimize the baseball players on a team, Multi Echelon Inventory Optimization (MEIO) can optimize your inventory that is deployed throughout your supply chain, in order to achieve target customer service levels, and maximize profit.  There are obvious parallels in taking the Moneyball philosophy to the optimization of inventories.  Instead of the General Manager in baseball using statistics to determine the best players to have on a baseball team, the Supply Chain Manager can use statistics and mathematical models in a MEIO system in order come up with the highest profitable scenarios.  By examining these scenarios, the Supply Chain Manager can decide how to right-size the inventory levels at different locations, and achieve targeted customer service levels, at the highest margins.


Of course, instead of baseball metrics (e.g. RBI’s, on base%, ERA, salary), there are statistical supply chain metrics (e.g. Demand variability, supply variability, BOM, Inventory value, etc.) that can be used to objectively calculate the value of each unit of inventory that you plan to place at a given “position” in your supply chain (e.g. Raw Materials, WIP, Finished Goods, etc.).  This would make it possible to optimize inventory deployment for meeting certain customer service objectives, and squeeze the most profit out of your supply chain, while not exceeding the budget allocated for working capital. 

 
The Oakland A’s are back in the playoffs again this year, with a budget that is one-third of the Bronx Bombers.  Not surprisingly, the use of statistics (i.e. the right system) is helping them get the most out of their small budget.  


Adexa has the equivalent of Moneyball’s Sabermetrics for your Supply Chain, it’s called the Inventory Optimizer to ensure each dollar of inventory is spent in the best possible way.

 

About the Author:  Bill Green is the Vice President of Solutions at Adexa, for more information about him please visit William Green profile link.    

Topics: Multi Echelon Inventory Optimization, Supply Chain Planning, Inventory Planning, MEIO, Inventory Management System, Manufacturing Software, Inventory Optimization, Inventory

Reducing Supply Chain Risk With Better Inventory Planning

Posted by kameron hadavi on Tue, May 10, 2011

Supply Chain Riak ManagementIn our last blog article, we talked about how today’s advanced planning technology can help with managing risk in a supply chain (read: Use Advanced Planning To Manage Supply Chain Risk). More importantly, we talked about how uncertainty (i.e. risk) in the supply chain, most often, leads to imbalances in the inventory levels. The following table was used to show how common supply chain issues lead to either too much, or too little, inventory at different points in the supply chain.   

Inventory Planning Issues

The good news is that many of the most frequent risks, and their impact on the inventory levels, are quantifiable.  For example, most companies have a good idea as how reliable major suppliers are, how often certain machines breakdown, or how accurate are their demand forecasts. Furthermore, the negative effects that indirectly  propagate to other parts of the supply chain can also be considered.  For example in Japan, many of the suppliers who were not directly damaged by the recent earthquake, still felt the ripple effects of difficulties in procurement of raw material, shipping Finished Goods, and other logistical problems.  These too, can all be calculated with a proper supply chain inventory model.

Let’s talk about how supply chain planning technology can help.  Since risk and its effects on inventories can be measured then wouldn’t it be logical to manage supply chain risk from within your Inventory Planning system? In fact, today’s advanced Multi-Echelon Inventory Optimization (MEIO) systems are intelligent enough to be used for supply chain risk management.   Forecast streams, incremental costs, revenue factors, service impact, etc. can all be dynamically modeled in a MEIO system.  Supply chain risk scenarios can be simulated and their effects on inventory levels, profit margins, and customers can be closely examined.   Such a technology can make it a lot easier to decide whether it would be worth to operate at a higher cost structure (for example, by introducing alternate suppliers, or increasing buffer inventories), or consider other options to mitigate risk. In some cases, you may even realize that it would be too expensive to greatly reduce certain risk factors.  That is your choice, but as long as you can fully and systematically assess the consequences.

An MEIO system with supply chain risk management capabilities would be most useful in assessing the more frequent risks, causing the infamous inventory seesaw effects, rather than risks that may occur twice per century—such as Japan’s recent earthquake. Take Apple for example, which was in middle of iPad2’s launch, as the disaster occurred.  According to CNBC, some of the components of this device are built only in more advanced manufacturing countries, such as its unusually thin battery.  Chances are that Apple will not dramatically change this supply strategy due to a similar risk in the near future—even as it delayed iPad2’s launch date in Japan by two months, and the wait time for all online orders increased to 4-5weeks.  However, you can be sure that Apple has assessed many alternate supply strategies based on risks of much higher probability.      

Risk assessment can never be too accurate.  A Multi-Echelon Inventory Optimization system can be your best tool in simulating, assessing, and mitigating risk factors, and their full impact on your supply chain.   Feel free to use the comments section to tell us what tools you are currently using to manage risk in your supply chain.

For more information about MEIO, use the following links:

Download this ePaper: Demystifying Multi-Echelon Inventory Optimization

Youtube video: Inventroy Planning Defined As Part Of S&OP

 

Kameron HadaviAbout the Author:  Kameron Hadavi is the Vice President of Marketing & Alliances at Adexa, for more information about him please click here.

Topics: Multi Echelon Inventory Optimization, Supply Chain Planning, Inventory Planning, Enterprise Risk Management, Risk Planning

Use Advanced Planning To Manage Supply Chain Risk

Posted by Cyrus Hadavi on Thu, May 05, 2011

Supply Chain Risk ManagementThe biggest risk in any supply chain is having either too much inventory, or too little, at different points in your supply network. Too much of it leads to additional cost, as well as waste of capacity and space for products that are not selling. On the other hand, not enough inventories would obviously lead to less revenue, and in many instances loss of valuable market share.  After 3 years, GM is most likely to reclaim the title of the world’s largest automaker from Toyota, the father of best supply chain practices in the industry--due to the Japan’s earthquake’s devastating effect on its production and inventory levels. Could it happen to you? You bet!

Some may argue that there are many more risks other than the two specified above.  Our experience shows that all the other factors lead either to availability of inventory, or lack of it.  Consider the following scenarios:

Inventory Planning Issues

As you can see, every one of the above issues can create a risk that would ultimately lead to either too much, or too little, inventories at different points of the supply chain. So, you should consider adjusting inventories based on what risk level is best for you. Conversely, each potential risk would have an impact on availability of inventory. The amount of impact can be estimated by its relative importance. For example, a delay from a key supplier of Boeing, for a critical part, can cause months of delay in delivery of the Dreamliner—this is a much bigger risk factor than bad weather forecasts in some parts of Asia, during the monsoon season.

For each one of the potential issues listed above there is empirical data as to how often it happens. Most companies keep track of their supplier performance and supply chain issues with respect to delivery and quality. Based on this data, you can determine what the financial consequences of such events would be using advanced planning technologies that are now available to you. The use of this technology allows a more holistic approach, taking into account the entire supply chain’s risk rather than pockets of exposure, such as the supply process, design issues, forecasting errors, or manufacturing glitches.

An unfortunate disaster, such as the recent earthquake in Japan, can cause many supply chain problems for a myriad of companies.  By simulating an event such as this in a supply chain risk management system, you can estimate the potential loss as well as what it would have taken to avoid such a loss. If the cost of avoiding such a loss, which happens, say, once every 50 years does not justify it, then a number of steps can be taken to mitigate risk rather than building just-in-case inventories. For example, many automotive companies could have a standby supplier at a slightly higher cost, which can step in and mitigate the risk of supply disruption.  Thus, the higher cost structure would be justified by removing the risk of halting the entire supply chain, when frequent risk factors materialize into supply problems.

In general, risk and cost have an inverse relationship; the higher the cost, the lower the risk, and vice versa. The idea is to know where the trade off is and at what cost the enterprise is willing to mitigate certain risk potentials. Of course, this does not mean that every time you increase the cost, you are necessarily lowering risk. 

In summary, use advanced supply chain planning technology for a speedy answer on when to take a risk, and when not to, based on objective financial consequences. All it takes is a holistic process to risk assessment, and the right planning system.  The technology is ready. Are you?

 

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

Topics: Multi Echelon Inventory Optimization, Supply Chain Planning, Inventory Planning, Enterprise Risk Management, Risk Planning