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Virtual Strategy Magazine recently reported,, on a BDO study,, about the risk factors most frequently cited in the 10K reports of the 100 largest publicly traded US technology companies. The table below is a summary of those results.


On its own, the list is quite interesting. As noted in the article, the 10-K filings were made before the Japanese tsunami. I would expect that more recent filings would include Supplier/ vendor concerns (#7) and Natural disasters (#12) which would elevate the ratings for these risks.


I also find it interesting to study the risk factors that have gained prominence in the last year. The table below shows the top five risks ranked by percentage change between 2011 and 2010.



The fastest growing concern is "Inability to maintain operational infrastructure and systems." Perhaps this is an indication that executives are concerned that they have too many systems and that the systems they have are too complex or too difficult to integrate.


Clearly, the prevalence of world conflicts and natural disasters, coupled with global markets and suppliers, explains the rise of "Natural disasters, war, conflicts and terrorist attacks." As mentioned above, I would expect this category to be cited even more frequently in 2011/2012 reports.


I find the rise in "Failure to properly execute corporate strategy" fascinating. From being mentioned in 27 percent of 10-K filings in 2009, it has jumped to being cited in 93 percent of 2011 filings. I wonder what impediments are worrying executives.


It has always been difficult to "Predict customer demand and interest, innovation." However, this risk factor is also growing as a concern for executives.


Finally the rise in, "Credit or financial risk of customers, vendors or suppliers" tells me that executives are either dealing with riskier business partners or that the general economic situations is putting more companies at risk.


What is not discussed in the Virtual Strategy article is what companies can do to mitigate the impact of these risks.


I think there is actually a common, underlying theme to these five fastest-growing risks:

Systems supporting key business processes are too complex and too cumbersome to support the rate of change in today's technology companies.


There is a clear an obvious link between my above statement and the fastest rising risk factor. To my mind, the remaining four rising risks are all related to managing the business despite rapid, uncontrollable change. Current business processes, and the systems supporting them, frequently take a month or more to detect a business-altering change and to change course to adapt to that change (whether the change is seen as a problem, an opportunity, or both). I suggest that new processes and response management strategy are required so that the time to detect and react to change can be shrunk to days, even hours.


For example, following the Japanese tsunami, I have heard anecdotes about some companies launching response teams and securing alternative sources within hours of the disaster. On the other hand, I have also heard of companies, months later, which are still figuring out the parts that are likely to be in short supply and how to select alternative suppliers. Clearly, the latter will have much more difficulty maintaining production in the face of global supply shortages.


What do you think? Does your company need systems and processes which are simpler to use, more flexible, and more responsive? Do you know of examples where fast, responsive, flexible systems gave you a competitive advantage, or where their absence resulted in serious losses?

Originally posted by dklett at

There was an interesting article written in HuffPost Business a while back about nine companies and their stories when their demand exceeded supply.


Will this problem ever go away? It is argued that if you have brand loyalty then the risk of perishable demand and worried investors is low. This argument holds for Apple where customers are willing to wait. Does the same hold true for BMW when their entire supply of 5 Series was consumed in one month in 2010? Some people just need to get a car. Brand loyalty may not be as influential. Which companies plan for limited supply versus the risk of excess inventory? The article talks about the Kentucky bourbon called Rip Van Winkle. Have you heard of it? Probably not as it is usually hidden behind the counter of the liquor store. They would rather keep production low than risk having inventory. Other companies with short life cycles may do the same. They must get their product to market as soon as possible but cannot risk the bottom line impact of scrapping product when demand is not meeting forecast. There is also the case where limited supply is not planned and can have serious consequences. Canadian company Lululemon faced shortages when their apparel line exceeded expectations and were forced to pay premium freight to accelerate supply. Margin erosion is often a result of demand exceeding supply.


So what does this really tell us? For the most part, forecasts are inaccurate. It has been proven that improving forecast accuracy results in higher customer service with the same inventory or the same service level with less inventory. How do you improve forecast accuracy? Companies are finding more innovative ways to address this. Many are recognizing that improving demand response will reduce the cost and error of forecast error. Improved collaboration with trading partners; customers and suppliers also improves forecast accuracy. Duncan Klett has written an interesting white paper on Demand Planning where he is really talking about the value of response management in the demand planning arena. He statistically proves that by focusing on customers with high demand variability, reducing cycle time (more frequent demand updates) will improve service and reduce inventory. Collaboration is another component where the sharing of up-to-date forecast information between trusted partners results in improved accuracy and reduced latency.


What are your thoughts?

Originally posted by cmcintosh at

It's been pretty hectic around here as we are gearing up for the Gartner Supply Chain Executive Conference- the must-attend conference in supply chain is only a week away. Here's the top five things we're doing at the conference:






5) We're attending: Kinaxis will have a staffed booth at the event. Come by booth #7 and say hi to the team!




4) We're tweeting: We'll be tweeting from the event as well! Follow #gartnerscc, @kinaxis, or @milesahead for live commentary on the events.






3) We're sponsoring: Kinaxis is once again the proud sponsor of the Supply Chain Top 25 Dinner celebrating world-class supply chain achievement.






2) We're presenting: We are hosting a Solution Provider Session in the Camelback Ballroom H on Thurs June 2nd at 3:15pm




But most of all...




1) We're having fun: We are turning our presentation session into a live taping of the LATE LATE SUPPLY CHAIN SHOW. Laugh and learn with Kinaxis business consultant and resident comedian, Bill Dubois, as he interviews senior supply chain executives to get to the heart of their response management challenges and strategies. Guests include:




Bob Gentile, VP of information technology, Qualcomm


Todd Jackson, VP of strategic programs/corporate operations, Boston Scientific


Abe Eshkenazi, CEO, APICS


Trevor Miles, director of thought leadership, Kinaxis






The first 40 people that come to our Solution Provider Session at the conference will be the proud owners of an exclusive LATE LATE SUPPLY CHAIN SHOW On-the-air desktop speaker. No one will leave empty-handed with the great free giveaways we have planned for attendees.




We hope to see you there! If you have still yet to register, Gartner is offering $400 off the conference price if you register at with priority code SCCKXS.




Originally posted by lsmith at

In a White House Blog post this month, the role of the President's Council on Jobs and Competitiveness in promoting supply chain innovation and helping small businesses was highlighted.The blog described how small business growth can influence regional employment and the Council's objective to provide constructive guidance to help make that a reality. While the blog did describe some of the methods the council is using to achieve their objectives, I was left wondering how the council can help level the playing field for small businesses when competing with large rivals.Who hasn't heard tales about the virtual disappearance of the local hardware stores when faced with competition like Home Depot and Lowes?Small businesses face many of the same supply chain dynamics and risks but without the level of resources in systems, expertise, and business leverage. The recent recession was particularly difficult for small businesses which often have very limited capital and a much lower risk tolerance. I can count more than 10 small businesses within a 3 mile radius of my home that didn't survive the recession.Still, small can often translate to nimble with a freedom of transformation that is difficult to achieve in large company bureaucracies.So how can the council help small companies address the disadvantages while leveraging their strengths?




Large companies have been investing heavily in developing sophisticated response management capabilities to address the volatile nature of demand and supply while minimizing their investments in inventory. Coupled with Lean Enterprise practices, these companies have achieved distinct cost advantages. I'm wondering if the council shouldn't be actively promoting methods for small companies to learn and adopt lean practices.Going one step further, perhaps the government should be subsidizing system investments that would help small business be more responsive to the dynamics of the current business environment. The objectives of the Council are laudable and a business environment where small companies can compete and thrive will indeed serve to increase both product and supply chain innovation. Do you have other ideas on what the Council might do to help?




Originally posted by kzuber at

Just a short post today to let you know what we recently developed a newsletter which includes complimentary access to a 13-page Gartner S&OP research report titled "Sales and Operations Planning Maturity: What Does It Take to Get and Stay There?" (Jane Barrett, Michael Uskert, 1 November 2010).




Companies with mature S&OP processes testify to the predictability and transparency it brings to the business. While neither the process nor this revelation is new, the fact is that two-thirds of businesses do not progress beyond the first two stages of Gartner's 4-stage maturity model. This complimentary Gartner research report provides recommendations for achieving higher stages of maturity, and highlights the benefits of doing so.




Download the newsletter here.




Is your company facing a growing urgency to derive greater value from your S&OP processes? What are the steps you are taking in response?



Originally posted by lsmith at

Here is part 2 of the ten critical data issues to be considered in structuring the outsourced supply chain data model. Click here to check out part 1.




Model Contractual Terms




As demand fluctuates and supply plans are adjusted, it is important to be able to quickly determine if contractual terms are being violated.




5. Tolerances, demand and supply changes




Outsourcing agreements often put limits on demand and supply change within specified periods to determine excess inventory liability. In the supply planning process, forewarning of potential liabilities is certainly desirable. By capturing these tolerances, planners can simulate different supply plans and evaluate demand and supply changes outside of agreed tolerances to provide some mitigation against excess inventory liability.




6. Inventory rebalancing expectations




Brand owners often expect their contract manufacturers to source component inventory from existing excess at other nodes before purchasing more. Rules must be understood so that inventory transfers can be simulated.




Simulate Supply Alternative Strategies




Perhaps the biggest benefit of having this data model in place is the ability it provides to brand owners to simulate supply alternatives across the entire supply chain. While contract manufacturers and component suppliers are responsible for managing manufacturing operations, brand owners, with this visibility, can actively collaborate with them and ultimately coordinate activities to manage supply and minimize risks for all partners. A successful collaboration process will increase trust levels and ultimately strengthen the relationship between brand owners and suppliers.




7. Alternate supply plans




Product availability based on existing supplier commitments compared to product availability based on projected supplier capability using the supply chain model is often the starting point for analysis. It should be possible for the brand owner to simulate potential supply alternatives by:


  • - changing rules for end item selection
  • - changing sourcing rules for suppliers,
  • - transferring existing inventories
  • - simulating other changes in planning policies, such as lead time
  • - Planners can use those simulation results as the basis for collaboration with suppliers.




8. Supply sourcing: strategic end item selection




One alternative strategy to improve supply may be to change the mix of equivalent products that are planned. This end item selection can be complex in many environments. Item selection could be based on purchase agreements for strategic components, customer qualification status for specific end items, end-of-life plans for products, etc. Selection rules should be made visible in the data (perhaps as part of the bill of material or represented as part to part transfers), so that planners can review and adjust them for simulation of alternatives.




9. Supply sourcing: supplier selection




Use of alternate suppliers is one of the most common strategies for supply improvement. It is advantageous to be able to identify all potential supplier relationships, not just those currently active, if planners are to be able to simulate and evaluate potential supplier changes. For example, all demand may be sourced to a single supplier, but, in the event of a demand increase, the planner may want to simulate splitting supply across two or more sources, perhaps on a percentage basis, perhaps on absolute quantities, or perhaps based on supplier capacity. Rules should be structured in such a way that planners can simulate time-phased rule changes or can simply override supplier information on particular orders.




10. Metrics for supply plan evaluation




What makes an effective supply plan? Clearly the decision making process will be unique to an organization and will usually balance key performance indicators (KPI) relating to customer service, revenue, costs, potential liabilities. Change will be frequent, and it is important for brand owners to be able to respond to change by simulating supply alternatives and measuring the impact on the overall plan.




Building a set of metrics for this comparison of alternatives is a key component. Planners should be able to compare several alternate strategies before selecting the optimal one in the event of supply constraints. The impact of alternate strategies on KPIs should be able to be ranked and compared across scenarios to obtain a balanced scorecard and an objective way of determining the best course of action.




So, Is it worth it?








Increasing supply chain complexity is driving the requirement for more complex data models. The complexity can be overwhelming without the proper tools and processes in place. But the challenge cannot simply be ignored because it is daunting. The market is driving the complexity and companies are required to manage it.




For many organizations, current processes are unsustainable and unacceptable. To survive and thrive in this dynamic environment, companies must adapt. And while it is certainly not without its challenges, it is also not without great benefit when done right.




Originally posted by jmarshall at

Outsourcing manufacturing to specialists who can provide unique value and drive down costs is now the business norm. While companies may be going about it with more caution and consideration than perhaps in the early 2000s, the manufacturing outsourcing model itself is not in question.


Brand owners are quick to discover that the first critical impact of outsourcing is the loss of visibility of detailed supply and demand data that they once held in their own ERP systems. Without this visibility they cannot make information-based supply management decisions. While getting access to detailed supplier supply and demand data is usually their first focus, it soon becomes apparent that tools that can allow them to view, analyze, and manipulate this data are also a very high priority.


The following are ten critical data issues to be considered in structuring the supply chain data model for maximum utility.


Capture Core Data From Partners


More and more frequently, outsourcing agreements include provisions for data sharing, which address both content and frequency of data feeds. Working closely with suppliers to understand the details of this data is a critical component of the collaboration process.


1. Part numbering issues


Part numbering schemes will usually vary across supply chain nodes. How will common or equivalent part numbers be established for global planning and netting? Cross-referencing supplier parts to brand owner part numbers is the most common approach.


However, it may also be necessary to consider parts in groups for netting purposes. For example, some suppliers may identify parts at the revision level, while others do not, or planning may be done at a product line level, not the detailed part level. System support for use of alternate parts and/or aggregation of supply and demand across multiple parts may be a critical requirement.


2. Core supply node master data and supply-demand details


Parts, bill of materials (BOMs), on hand inventories, local order policies, priorities, scrap, and yield factors are usually required for each supply chain node, as well as all active demand and firm supply records. It should be possible to match the local planning behavior of the outsourced supplier reasonably closely. This becomes particularly important when there are multiple levels in the supply chain. Incorrect planning at one level can radically skew requirements for downstream suppliers.


Semiconductor manufacturing provides one example here, where wafer fabrication, assembly, and test may all be handled by separate suppliers with potentially different lot sizing, lead times, and yield factors at each stage. Without matching each supplier's planning policies it would be impossible to accurately plan for product availability.


3. Supplier constraints, both capacity and material based


Suppliers may have shared constraint information, and sourcing may be constraint-based. For example, a supplier may commit to producing a fixed quantity per week of a specific part, or grouping of parts, or he may commit to a fixed percentage of available hours on a particular manufacturing line. If known, these constraints should be reflected in sourcing rules and should be adjustable by the planner for simulation.


4. In transit quantities, lead times


At any given point in time, a significant portion of the existing inventory may be in transit between supply nodes. Clearly, synchronizing the timing of data collection for all nodes, including in-transit quantities is critical, if data collection is not real-time. In practice, getting the in-transit data right is often one of biggest data hurdles and a clear understanding of how in-transit quantities relate to supplier commitments is mandatory. For example, are current supplier commitments net of in-transit shipments, or should commitments be decremented by in-transits?


Lead time information is normally available by supplier, but, when modeling the full supply chain, transit time between partners becomes more and more important to model cumulative lead time.


Stay tuned – the rest of the list will be posted on Monday!

Originally posted by jmarshall at

I have been following the debate about the use of the terms IBP (Integrated Business Planning) and S&OP (Sales and Operations Planning) over the past few months with a lot of interest. It is with much trepidation that I step into this proverbial hornet's nest after Lora Cecere wrote a blog titled " What Happens in Vegas should not Stay in Vegas!" in which she argues that:


To get started, let's get beyond the nuance of the debate. This debate is not about the TERM. I REALLY don't care what term is used or what process is called. I agree with Shakespeare, "A rose by any other name would smell the same...." But, I don't agree with the conventional views on Integrated Business Planning (IBP) in three areas: focus, emphasis, and readiness.


Basically Lora argues that IBP is simply sophisticated S&OP. I'm not sure I agree. I think this characterization misses some subtleties between the two terms. Let's start with Lora's argument:

The number one change management issue with S&OP is and continues to be the role of the budget. If the company wants to maximize opportunity, the budget should be an input into the process, but not constrain the process.


Yes, I agree, but this is looking at the issue from the wrong perspective. What is broken is the budgeting process, which should be a continuous process driven by the operations forecast. And there is a lot of discussion in the Financial Planning and Analysis (FP&A) space about this, starting from an article titled " The Inherent Folly of Cash Forecasting" by Gavin Swindell in BusinessFinance. Gavin states that:


... The Hackett Group, recently published a survey of CFOs, and 70 percent rated cash flow forecasting as their top priority to be worked upon in 2011. Now, maybe I am being a little simplistic, but I find this strange.


Gavin argues that cash forecasting should be a "dependent" forecast based upon the operations plans for demand and supply. In fact he states:

The point is there is no need to forecast cash in a well-run business. It should be calculated. Anyone who is applying serious effort or cost to do so is papering over a business weakness presumably because they feel they have to or because they cannot fix the underlying causes. In many businesses, the cash flow from operations and the inherent working capital will week in week out account for the majority of transactional volume and value that businesses find hard to plan and predict accurately.


I agree.As importantly so do many others, for example in CFO Russ Banham states in a blog titled " Let It Roll" that:

Unilever parted with its annual budget in 2010, with no tears. So did Norton Lilly International. Statoil and American Century Investments have scrapped their budgets; others are expected to follow suit.


Russ is arguing that the annual budgeting process is broken and needs to change to a rolling process, and gives as an example Unilever which has moved to a quarterly budgeting process with a forward view of eight quarters. Russ has a great quote from Statoil:

Statoil, the large Norwegian oil-and-gas producer, decided to abolish the traditional annual budget in 2005. “We still do what the budget unsuccessfully tried to do for us: target-setting, forecasting, and resource allocation,” says Bjarte Bogsnes, vice president of performance-management development. “We used to try to force these three purposes into one set of budget numbers, which created serious problems. For example, how can you expect an unbiased sales forecast from a sales manager if that number also will become a target? And how can you expect unbiased cost or investment forecasts from the organization if those forecasts also serve as an application for resources, and everybody sandbags?”


Who am I to disagree when even the McKinsey Quarterly in an article titled " Just-in-time budgeting for a volatile economy" published in the Spring 2009 edition in which the authors, when commenting on the budgeting process, state that:

Managers often spend significant amounts of time on it, only to be dismayed by how little value comes from four to six months' effort. Under volatile conditions, when economic forecasts change from week to week, developing one reliable budget to coordinate business units and track performance for an entire fiscal year is very difficult. Following the traditional budget process may even be unproductive.


In fact they argue that the budgeting process needs to include the following:

  1. Scenario planning with trigger events
  2. Zero-based budgeting
  3. Rolling forecasts
  4. Quarterly budgeting


Perhaps even more importantly budgeting as part of FP&A covers a lot more than demand/supply balancing, which is the cornerstone of S&OP. Lora may argue with me that a mature S&OP should include much of what I discuss above, which is true, but the breadth of S&OP does not usually cover workforce management, R&D spend, capital expenditure, indirect procurement, and a whole host of other areas of interest to the budgeting process. Perhaps the most important of these is workforce management because so much of a company's cost base is salaries for it employees. Deciding how many people should be in Marketing in a certain region should be based upon the forecast for that region.The manner in which the Marketing budget is spent should depend on the make-up of the projected revenue for that region.The same is true for Sales and Admin, Procurement and Warehousing, etc...


Bringing all of these different cost elements together based upon the revenue forecast is integrated business planning, whether we call it IBP or not, and has a much wider scope than does S&OP. But, for all the reasons others have given, the budgeting process should be driven by the revenue forecast generated as part of the S&OP process, not the other way around. And of course adjustments to the S&OP plan may need to be made because of financial constraints that force, for example, a delay in hiring in R&D or expenditure on capital equipment, which impact the revenue projections.


Lastly supply chain management (SCM) is very manufacturing focused and, as a consequence, so is S&OP. Of course we can talk about SCM in Retail, but the heart and soul of SCM is manufacturing. So what is the equivalent of S&OP for say a Financial institution or a consulting organization? What about bio-pharmaceutical companies which while still having large manufacturing divisions are primarily focused on research and development on one side and sales and marketing on the other side, which is reflected in the fact that their cost of goods sold is often less than 20 percent of revenue and Selling, General and Administration can often be more than 40 percent of revenue?I'm not convinced that S&OP is sufficient to run these organizations optimally.


So I don't think IBP is simply sophisticated S&OP.So who do you agree with: Lora or me?

Originally posted by tmiles at

There has been a lot of talk about in-memory databases, but it’s important to recognize that not all in-memory databases are created equal.


Typically, these mega-software vendors' databases are optimized for performing queries on large but fairly simple data sets. While some of the query times cited are appealing, raw query performance is only a part of the equation....and I would argue, that it's the easy part. Certainly, the ability to query millions of records in a couple of seconds is scientifically interesting, but there is little business value in query speed. Business value comes from computational speed: the speed it takes to support an online and mobile supply chain community of thousands simultaneously performing complex "what-if" scenarios and analytics on large data sets — calculating things like capacity constraints, clear-to-build, ATP and CTP, Excess & obsolescence avoidance, part substitutions, S&OP, forecasting, etc...


That’s where we come in. When dealing with complex data relationships, the proprietary database employed by RapidResponse provides a significant performance advantage over the alternatives. Here's just one example (this example is detailed out in the technical paper, RapidResponse – How is it so fast?):


Using a Dell Desktop system, RapidResponse can do a simple query on over 4-million BOM records in 0.170 seconds.


Ok, so that’s pretty cool, but where it really gets meaningful is when you look at a complex calculation like running complete netting and counting the number of planned order recommendations. That was done in 45 seconds! RapidResponse is also very efficient at caching, so when you run the same complex calculation again, it takes only 5 seconds.


This is the type of calculation that our customers are able to perform when and how often they wish. In fact, users can simultaneously request the same calculation and still get their independent answers within seconds. That’s because our analytics code is directly compiled into the database engine where it has direct access to the in memory data. Less moving of the data between database and analytics means much better performance.


The superficial is fun, but it's the substance that matters.


By the way, John Sicard posted a great blog last year that gives the history behind our in-memory technology leadership that dates back 25 years, you can check it out here:

Originally posted by rpuvan at

I was recently reading an article in SupplyChainDigest titled: " Rethinking China".The article ponders a couple of topics; one, is it really beneficial for the US economy to have such a trade deficit with China even if it helps individual companies?; and two, whether we really have free trade with China or rather a labor arbitrage situation.


I work with many large OEM's based out of North America, almost all of which are publicly held corporations who must answer to Wall Street each quarter. That is why much of their supply chain is either outsourced or done in Asia.This is nothing new. For years we have seen outsourcing in all types of areas to help companies improve their bottom line. Being in the IT business for the last 20 years, there has been a huge trend to outsource IT services to India and the results have been mixed. Companies were (and still are) willing to take some inefficiencies in effort because of the low cost labor force. For example, offshoring work typically requires more effort, perhaps up to two times than what it would take to get it done locally. In fact, I noticed many companies being forced to use this labor force because it looked like a competitive advantage for their company. If you weren't outsourcing then there was a school of thought you were paying too much money for services and you weren't using best business practices.Over time and with experience, many times bad, companies have tried different strategies to make it work, and it has for many companies. But some companies have determined that they wanted less inefficiency and possibly higher quality so they bring some of the resources to North America to do some or all of the work which can be significantly more expensive.Many of the large Indian IT firms will propose a mixed model of some work onsite and some offshore.In addition, with the boom of the IT industry in India, the labor costs are increasing and those costs are being passed on to the companies. So as the cost increases for Indian resources, there is a new quest to find the next low-cost, high skill labor pool.


The author of " Rethinking China" shows that over the last 12 years, the trade deficit between the US and China has increased by 400 percent.Wow, that is a staggering figure particularly when you consider that the majority of that deficit is China manufacturing finished goods and shipping them to US vs. commodities.Obviously, this has taken many jobs from the US economy, however, one could argue that our labor force can do higher value work.Much of the manufacturing that these companies have shipped to China is labor intensive work because their labor cost is so low. But perhaps as the Chinese economy grows, the labor force will insist on higher wages and better working conditions, which would likely increase costs to the North American based companies. Perhaps there is a difference in quality as well. I have noticed some companies trying more mixed manufacturing methods where they send some of their people to supervise the plants in China or take part of the manufacturing back in house.


It will be curious to see how the industry looks in ten years.Will companies be looking to other countries for low cost manufacturing labor costs as the labor costs rise?Which countries will those be? Will there be quality issues in manufacturing?Will there be consolidation of the manufacturing in China to a few high quality companies? Clearly the trend of outsourcing is here to stay but the model of who does it, how it looks, and where it happens may change over time.Will the IT outsourcing experience parallel the outsourcing of manufacturing?I am interested in your experience and predictions.

Originally posted by mrupert at

Short post today to let you know that our very own chief blogger, Trevor Miles, recently presented a session at the High-Tech Forecasting & Planning Summit last month. His session was called "Is Forecasting Fatally Flawed?" Does that title seem a little familiar? Well that's because the session was based on a recent blog post he did by same name.




You can check out the PPT deck from the event here:




Or view the on-demand webcast here:



Originally posted by lsmith at

David Manners wrote a blog on Apr 28, 2011 titled ' Why is the supply chain so opaque?' on his Mannerisms blog, in which he states


The complexity of the electronics supply chain is such that, six weeks on from the earthquake, no one is sure what its effects will be on their businesses...
For an industry which manufactures to tolerances measured in billionths of a meter, in which the researchers win Nobel Prizes and the salesmen have PhDs, it’s anomalous that it can’t forecast, plan, locate, track and measure its output.




The cause of the supply chain opacity referred to by David is the degree of outsourcing, coupled with ever increasing product portfolio complexity, which is due to mass customization and shortening product life cycles. Statistical forecasting is a ‘large number’ tool that requires long histories and frequent sales to achieve a high level of accuracy.Digital cameras have life spans of six months and less. Smart phones have a life span of 18 months and less - and this is decreasing even as the number of models and model variants explodes. The shorter life spans means there is little history to go on and the explosion of model variants is greater than the increase in sales volume.It is no wonder that consumer electronics companies can seldom get forecast error, as measured by MAPE at a month lag, below 50 percent. Forecasting at the product family level only makes matters worse because this hides trends that are critical to determining component and capacity requirements, even though forecasting at the product family level may lull you into a false sense of security by reducing forecast error.




Yet as stated by Research in Motion, the Blackberry owners, in a webinar hosted by SCMWorld on Apr 28, 2011 (the replay wasn't available at the time of writing this blog), product portfolio complexity is required to compete in a consumer market with ever changing requirements. This is in stark contrast to many pundits who advocate reducing supply chain complexity, the primary cause of opacity, by reducing the product portfolio. I am the first to agree that a sound product portfolio analysis is something everyone should do, but outsourcing isn't going away, neither is mass customization. So I say embrace complexity by providing visibility. But in today's highly outsourced environment visibility must span several tiers of the supply chain from customer through OEM to contract manufacturer and on to the component suppliers. If you have distributors, then at least get a 'sell through' measure of demand, not just a 'sell in.'




But access to data across the supply chain is not visibility.Without a manner in which to respond rapidly and profitably to actual demand, access to data adds nothing.But I agree, access to information across multiple tiers of the supply chain is a start. Being able to detect changes from the plan, understand the consequences of the changes on customer commits, capacity requirements, or component requirements, and evaluate alternative courses of action in both financial and operational terms quickly and effective is the clue to gaining visibility. Only this will reduce the opacity in today's supply chains.



Originally posted by tmiles at

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