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Run Your Supply Chain without a Bullwhip!

  
  
  
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.

Inventory Optimization is like Baseball's Moneyball

  
  
  

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 http://adexa.com/company/green.asp    

Reducing Supply Chain Risk With Better Inventory Planning

  
  
  

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: http://www.youtube.com/watch?v=K0kpf2Qi_aE

 

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

Use Advanced Planning To Manage Supply Chain Risk

  
  
  

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.

Supply Chain Planning for South Africa's Largest Processor of Chicken: News Release

  
  
  

 Supply Chain Planning for FoodLos Angeles, CA, May 3, 2011—Adexa, Inc., the global provider of Supply Chain Planning and Demand Planning solutions, announced today that Rainbow Farms (Pty) Ltd, South Africa’s largest processor and marketer of chicken, has selected Adexa as its supply chain solution provider.  The first module, Adexa’s Collaborative Demand Planner will be implemented at Rainbow and Vector Logistics, one of the country's major 3rd-party logistics service providers for the CPG/food industry, and also for Rainbow.

The management teams of both companies are determined to improve and automate their joint Sales & Operations planning processes.   The goals of the project include reduction and optimization of inventories throughout the supply chain network, and creating a fully collaborative platform that drives the supply chain through more accurate and intelligent customer forecasts.  

“We want to make better use of our infrastructure, reduce inventory and working capital, and further improve on our high standards of customer service,” said Chris Creed, Managing Director for Vector Logistics.  “To that end, we needed collaborative tools to get closer to our customers, and more advanced planning systems for production and profit planning.  Tools provided by our own ERP system, and the spreadsheets, did not take us nearly far enough, but Adexa will.”

“Rainbow and Vector are very important and strategic customers to Adexa,” said Cyrus Hadavi, Adexa’s CEO.  “As a result of their selection, we have established new sales and support channels, in partnership with Sizwe Africa Business Consulting, to better serve them and our upcoming customers in that region.”

About Rainbow Chicken and Vector Logistics  

Rainbow Farms (Pty) Ltd, is South Africa’s largest processor and marketer of chicken.  Vector Logistics (Pty) Ltd, a division of Rainbow, is a specialist third-party logistics service provider (3pl) for the food and food-related industries within southern Africa across the retail, wholesale and food service sectors.  Visit: www.rainbowchickens.co.za and www.vectorlog.com

For more informaiton contact:

Ron Wilson

Marketing Director

888-300-7692 (Ext. 3)

rwilson@adexa.com

 

South African partner:

Richard Harris

Director, Sizwe Africa Business Consulting

+27 82 805 3360

Richard.harris@sizweafrica.co.za

Risk Management: Run Your Supply Chain Like An Insurance Company

  
  
  

Supply Chain RiskEveryone is aware of potential risks in running a supply chain but what is the process by which you evaluate that risk? And, figure out the alternative solutions to lessen or eliminate it?

I bet most companies, if not all, have no real objective risk management process in their supply chains. At best, they have processes in place for different organizational pockets within which risk is mitigated. Some examples are evaluation of suppliers by the Purchasing Department to ensure supply continuity, or redundancies in capacity, and even building too much, or too little, inventory—which proves more costly.

The fundamental question: what is the damage, when something goes wrong? And, what price are you paying to avoid such inevitable risks? Payment of an insurance premium is exactly that. You pay for a service that allows you to recover from a financial disaster or lawsuit. Insurance companies do their risk assessment very well and ask for a premium that makes them profitable even though every now and then they have to cough up the cost.   Are you doing the same with your supply chain? What is the premium you are currently paying (within your own supply chain) to avoid a potential disaster? What is the potential cost of that disaster? And, is it worth the premium?

A common example of this is delivery performance vs. inventory (mix) at hand. I am sure you are familiar with the exponential operational curves that imply doubling your inventory for a 5% improvement in your delivery performance, from 92% to 97%. Does this make sense? How much is really enough? And, what is the actual cost of missing delivery rather than cost of holding inventory?

Management teams are encouraged to avoid risk. In other words, their incentive is to deliver rather than miss delivery. So, the employees will go out of their way to ensure delivery at company's cost! Again, does this make sense? Example: “sand-bagging” the forecast and “padding” the supply to avoid shortages are steps taken by two different organizations and processes, Sales vs. Production. Furthermore, supplier selection, cost turbulence, and delivery issues are also padded in an isolated way, adding to the overall inefficiency of risk management.   How do you really assess the risk of one supplier over the other, especially as it impacts your bottom line and customer service?  Consider the recent unfortunate disasters in Japan, as many of the car makers are struggling for alternate resources to get their parts delivered;  earthquakes in Taiwan, SARS epidemic in China, dock worker strikes at Los Angeles ports are all other examples of supply risk.

Some element of risk avoidance is built into the jobs of each person, or department.  However,  if each person avoided risk in all the steps to deliver the goods, it would create too much cumulative redundancy--which would cause much higher additional cost in the final product.  This can be avoided with a more holistic approach.

We believe that objective risk assessment must be part of the supply chain planning process and systems, so that objective decisions are made based on financial consequences rather than protecting select customers, or individual employees. To this end, a holistic approach offers more than just  a simple spreadsheet-based S&OP process, but a Financial Sales & Operations Planning solution. The key word is “Financial”, that is integrated into the rest of the enterprise’s operations. Cost, revenue, profit, and risk become part of the supply chain equation, along with customer delivery and supplier management.

When was the last time you took a risk in your supply chain? What was the consequence? How much did the company benefit from it or lost because of it? Would you have liked to have a better optimization and analysis tool to evaluate your options? We invite you to join us in creation of the next generation of supply chain tools, integrating Financials with Sales and Operation Planning (FS&OP).

 

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


When should I ignore the customers when planning my supply chain?

  
  
  

Supply Chain PlanningThe first answer for most people is:  “never”.  So, lets put this in context, we are not asking if you should totally ignore your customers’ demand and market signals; we are really asking how important is it to track and consider individual customer demands/orders when planning your supply chain?

If you are a  business-to-consumer enterprise, the individual demands do not really impact your supply decisions.  For example, giant consumer product companies (from TV to toothpaste) do not track the individual orders when planning supply.  They are all aggregated up to a total demand for a product.  To that end,  this aggregated-planning approach is ubiquitous in the CPG industry, which has high volumes and low variety of consumer products.  For these industries, it is sufficient to aggregate all the end item demand into a total, and then net the total demand from the on-hand inventory, one period at a time.  The required production, or distribution, is calculated to make up for the predicted deficit.  That production quantity goes through a Bill-of-Materials Explosion (or the equivalent DRP calculation) and the dependent demand is used to do the same calculation on the next level of the BOM.  Devised in the mid 1980’s, this CPG logic is the dominant logic used by most supply chain planning systems, today.   Of course, each company has its own variations on how to handle capacity and material constraints, or includes an LP (Linear Programing) engine to optimize on cost, but the basics of the logic are all the same--they all lose visibility to individual customer demands when planning. 

How about turning the question around, when is it not OK to ignore customers when planning your supply chain?  When does a company need to look for a different logic in their planning system, than the typical CPG logic described above?  The answer is when you have critical constraints in your supply chain that cause you to have to stop treating all customers, and the associated demands, in exactly the same manner.  This comes into play when you need your planning system to help you figure out what orders should get critical capacity, special priority, or materials that are in short supply.  Examples of this are contractor capacity that is used to make multiple products, but is in short supply.  Another example is a critical common component that goes into multiple products.  The need to have visibility into orders when planning also comes into play when customer specifications require dependent levels of the BOM to be processed differently from each other.  An example of this is “date-code” considerations, or qualifications for specific manufacturing locations.  In each of these cases, the identity of the order and its attributes are important while planning it.   

In conclusion, when looking for a new supply chain planning systems (like for demand planning, inventory planning, S&OP, etc.), a company should do the simple check outlined above and decide if traditional CPG logic used in most planning systems today is sufficient to handle their requirements.   Given today’s savvy customers and their complex needs, many enterprises opt for much greater demand visibility and attribute based planning systems. 

To learn more about this topic download this ePaper: Attribute-Based Planning: How To Avoid Commoditization.  

Monolithic Power Systems Plans With Adexa: News Release

  
  
  

Monolithic Power SystemsApril 7, 2011-- Adexa announced today Monolithic Power Systems, a high performance fabless semiconductor company, has selected and are implementing Adexa’s supply chain planning, and demand planning solutions. 

 “Our product portfolio has grown to hundreds of diverse products for worldwide customers, and we interact with multiple Foundries, Assembly and Testing sites.  We turned to advanced information technology solutions to further optimize the whole demand and supply planning process, and to ultimately better service our customers,” stated CEO, Michael Hsing, of Monolithic Power Systems.  

With deployment of the new systems, Monolithic Power Systems expects to further improve visibility, accuracy, and performance optimization in its supply chain, while enhancing collaboration across multiple business units.

“We selected Adexa through a long RFP process involving multiple leading vendors.  Adexa demonstrated very strong expertise in our industry and system implementation, and overall commitment to their customers”, added Dr. Henry Zhao, Director of Global IT of Monolithic Power Systems.

“Semiconductors has always been a big focus for us,” said Cyrus Hadavi, Adexa CEO.  “In the past year we have been seeing strong demand for our planning solutions from the Fabless side of the industry.  We are glad to see this trend continuing into this year as Monolithic Power Systems is being welcomed into our customer base."  

For more information about challenges and planning solutions for the fabless industry, download this ePaper: Overcoming The Shortcomings Of Fabless Planning Systems 

 

About Monolithic Power Systems, Inc.

Monolithic Power Systems (MPS) is a high performance analog semiconductor company headquartered in San Jose, California. Formed in 1997, the company has three core strengths; deep system-level and applications knowledge, strong analog design expertise, and an innovative proprietary process technology. These combined advantages enable MPS to deliver highly integrated monolithic products that offer energy efficient, cost-effective solutions.  Visit: www.monolithicpower.com

Planning Proliferation Of Products In A Fabless World

  
  
  

Semiconductor Supply Chain Palnning“Complex” is the common word we hear from many of our Fabless Semiconductor customers in describing their supply chains.  We talked a bit about that in our last blog posting entitled: Fabless Semiconductor Planning: Between a-rock-and a-Hard-place!  In this article, I want to touch on another culprit in complexity of a Fabless enterprises (or Semiconductors in general), proliferation of products

It’s no secrete that Fabless supply chain are faced with ever increasing number of products, and with that comes a lot more part#’s.   It’s one thing to deal with 3 products, and another thing to deal with 30.  The part#’s involved increases exponentially with every end-product.  Imagine this, in most cases our fabless customers are dealing with 100’s of end-products.  This makes crunching through the numbers for a supply chain “plan” very difficult and slow.  Remember, in planning the entire supply chain, these part#’s have to be used for demand planning (when the customers order it), operations planning (how to build it), inventory planning (what to keep on hand), and Supply planning (which suppliers to use and when).   The level of complexity is mind-boggling.

One of the new trends in dealing with this level of complexity is through Attribute Based Planning.  We have written a lot about this in the past but it seems like our readers can’t get enough of it, and for good reason--it works.  Attributes really simplify modeling the entire supply chain by utilizing the “characteristics” of products to describe them, rather than using unique part#.  For example, you may have a grade A, B, and C chips, at speeds of 1.66Ghz, 2.66Ghz, and 3.0Ghz.  You can give all 9 potential combinations a unique product name, or you can have only 3 product names by referring to the attributes of (Grade + Speed).  This is a very simple example, but you can learn a lot more about this by either reading the Attribute Based Planning ePaper or watching the “What is Attribute Based Planning” video on the Supply Chain Planning Channel

You can apply attributes to all levels of planning but there is a catch--your planning system has to be able to handle attributes for the process its intended for.  For example, for Demand Planning, the customer orders have to be described by their attributes within the system.  For Production planning, the product routes have to defined by attributes within the same system, and so on.  Basically, the entire logic and algorithms of your planning system has to be attribute-based, or you are stock with the unique part#’s. 

For fabless companies, who deal with massive product proliferations, attributes will make life a lot easier on your many planners.  They get to collaborate together much faster, and avoid a lot of clutter.   Below, see how Silicon Laboratories is using attributes in their planning environment.  Also, For more information on this topic download: Overcoming The Shortcomings Of Fabless Planning Systems ePaper.

 

 

For more information on this topic download: Overcoming The Shortcomings Of Fabless Planning Systems ePaper.

 

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

Fabless Semiconductor Planning: Between A-Rock-And-A-Hard-Place!

  
  
  
Fabless Semiconductor PlanningMost fabless semiconductor companies are stuck between a rock-and-a-hard-place.  On one end, they have big customers demanding what they want, when they want it; and on the other end, they have big suppliers manufacturing their products—some 16 time zones away.    Synchronizing and managing capacities and deliveries through a complex supply chain like this cannot be easy.  Compounding the complexity is the short life-cycle of such products and the long manufacturing lead-times through outsourced Fabs.  With every new product, you basically have to revamp a good part of your supply chain, quickly.    The common theme to all of these challenges is time and uncertainty

Now let’s break the time and uncertainty factors down to their components.  When it comes to manufacturing anything, there is always a Planning cycle-time, and a Manufacturing cycle-time.  The latter, is the pure production time it takes to manufacture a product.  Fabless companies don’t control the manufacturing lead-time, since all of their production is outsourced.  However, they do have the opportunity to manage the suppliers’ capacity that is committed to them—which becomes part of the Planning cycle-time.  They also have to worry about the uncertainty of what they will order with the amount of capacity that they have been promised.  This makes the Planning cycle-time, and accuracy of the plan, twice as important to a fabless enterprise.   Planning cycle-time, is the amount of time a company needs to plan, react, and/or rollout a new plan based on market demand, inventory positions, and supplier capacity commitments.  Its reduction translates into less uncertainty and increased accuracy.  To that end, reducing planning cycle-times is a colossal competitive factor in this market.  Imagine cutting weeks out of your planning lead-times, which would directly impact your customer service, market share, and competitive positioning—amongst other things.  

How can you battle time by achieving shorter lead-times?  Or in terms of fabless, how can you reduce your Planning cycle times and increase plan accuracy?  Before I answer that, let me ask you a question, how can a manufacturer produce goods faster?  The simple answer is: better technology, and faster machines.  The same thing goes for planning systems.  If you want to fundamentally do it faster then you will need a new technology that can help you plan faster, collaborate more, and give you more visibility, thereby enabling better plans.  There are many processes that need to have faster planning times such as demand planning, operations planning, inventory optimization, and of course supply planning.  In picking the right system for your enterprise make sure you consider all these processes and how well the system adheres to your supply chain.   After all what’s the use of faster delivery times, if your inventories and cost is going through the roof.   

Adexa is one of the providers of such technologies and systems, with a great deal of focus on the fabless industry.   Below, one of our fabless customers talks about how they are using our systems to deal with fabless industry's tough challenges.   Also, For more information on this topic download: Overcoming The Shortcomings Of Fabless Planning Systems ePaper.

 

 


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

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