Become a Member! | Print Page | Contact Us | Report Abuse | Sign In
Submissions to Eli's 6th Riddle (with comments from Eli)
Congratulations to Sanjeev Gupta, winner of Eli's 6th Riddle! 

Please keep reading below the riddle for Eli's Analysis and the winning answer, as well as the rest of the submitted answers!

The BigEric Carpets Case - a riddle by Eli Schragenheim

Eric has built BigEric with his own hands.  He started with one small room and three women weaving carpets based on his own design.  In five years the company grew to about $10 million annual sales.  Three years later it was already close to $100M.  It took another five years to reach sales of half a billion, with nine different regional plants, along their central warehouses, at various locations in the world.  This record of sales ($500M) was achieved in 2005.  From that year on the growth stopped.  Actually sales went down at an approximate rate of 10% every year and this drop in sales happened throughout BigEric’s international markets.  In 2011 the turnover was just $252M, causing a loss of $25M.

What is causing the drop in sales?

The four key people in BigEric have different opinions.

Eric claims that he lacks good local managers to exploit the local demand in the various markets.  This is how states his view:

"Every one of the region managers seems to miss opportunities that practically lie below their nose. They go to the same large distribution chains over and over again and do not try the smaller chains and shops.  Even the factories own outlet-shops do not push enough the newer, and more expensive, designs and prefer to push only those that have been successful in the previous year.  I expect from the regional manager to read the true wishes and preferences of the local customers.  It is a shame that I need to go personally to every local market we have and tell them what to push.  Of course I make some mistakes, but if do not frequently visit the local regions offices and guide them what to do then I would have bankrupt long time ago.”

Bill is the first deputy to Eric and he is charge of the worldwide supply chain of BigEric.  Here are Bill’s views:

"Eric has introduced the methodology of TOC on 2003.  It has improved the flow of products and certainly contributed to the peak of sales and profit in 2005.  But, since then the number of different designs has increased by much.  I suspect that many of the buffers are not at the right size.  I understand that dynamic-buffer-management (DBM) is monitoring the buffers, but it does not always fit the situation where the taste of customers changes very fast.  So, sometimes we increase the target level because the on-hand stock penetrates into the red for long time, but then the enthusiasm of the market goes down (many times because a nicer design appears) and we are stuck with huge inventory.  When we try to get rid of a certain design and offer reduced prices of up to 50% then DBM interprets the situation wrongly and increases the target level and we find ourselves producing an inferior product.  I tried hard to convince Eric to stop with automatic DBM, but he replied "Do YOU have the time to make all those decisions?  I certainly don’t, and I don’t trust the bastards at the regional warehouse to make the right decisions.  Goldratt’s algorithm is still the best we can get.”

Clara is the second deputy to Eric and she is in charge of worldwide Marketing and Sales.

"Eric is a genius designer.  All the success of BigEric is based on his unique designs.  But, the world is changing and we need a change in the character of BigEric’s products.  Problem is that Eric manages the design department.  I think, and I tell him that very openly, that it is me who should manage the design department.  It is part of Marketing and I’m the one facing the decision makers of the big chains and I’m aware of their complaints regarding BigEric’s designs.  There are more than 50 designers in the department and sometimes when they could not get hold of Eric they come to me.  But Eric likes his own decisions about design.  At least I can get hold of him faster than they, because he always picks up the phone when I’m calling. But, I don’t want to do it too often.

"Regarding BigEric’s sales I have to comment that we sell now about 90% of the number of carpets we sold on 2005, the year of the peak.  However, our average price went down considerably and this is the main reason for the low sales figures.  We have now more competition on the same market segment of relatively cheap, but very nice design, of carpets.”

Charlie is the third deputy to Eric and he is charge of Finance and IT:

"Like Eric I’m also a big fan of Goldratt’s theory.  I can tell you that the average T ratio out of the selling price is now about 50%.  It used to be 70% in 2005, our year of reference.  I believe more and more carpets are sold in promotions.  What worries me a lot is the huge amount of inventory that is definitely dead. We have a dozen of designs, approved enthusiastically by Eric, which did not sell even ONE unit!  Frankly I think we have too many designs!  I believe there is a hole in the TOC replenishment theory that seems to support having many SKUs, each of them with relatively low target level.  We have many thousands of SKUs in stock and the number is growing very fast.  When a design is new then a target level is set to cover the maximum forecasted demand for, say, three weeks of sales.  But, if it does not sell then the three weeks become three months of inventory and even three years of inventory.  This is number one problem we have.”

To complement the picture of the company we bring you also the views of two of the regional (and plant) managers.  Both asked that their name and location of plant would not be revealed.

Regional and plant manager 1 says:

"I think I know my local market very well and we definitely not producing the products our potential customers like.  I actively look for additional opportunities.  Two weeks ago a certain super-cheap chain of stores suggested buying carpets for $25M. All what they wanted was stock that is stuck at our warehouse for, at least, a year.  They offered to pay just 40% of the list price and were ready to cut the BigEric label from the carpets they would sell.  Clara agreed to the deal, but Charlie claimed the throughput is negative.  I tried in vain to get Eric on the phone for two weeks.  Eventually the deal evaporated and I still have that stock in my warehouse and the company suffers from $25M loss.  We could finish the year breakeven – if the deal would be carried out.”

Regional and plant manager 2 says: "I do not really have much influence on anything.  They tell me what to produce, when to release the production orders and even mess with the internal priority of orders.  Then I’m told where to send the products.  I have already sent my CV to other industrial companies in my location.”


1.  What is the core problem of BigEric?  You can use the three clouds method and/or CRT and/or an educated guess (with relevant explanations).

2.  If some critical information is missing – what is it?  What did you assume in order to be able to answer the first question?

3.  How would you deal with the core problem?


I have waited until the 2012 TOCICO conference to end to come up with my own answer to the 6th riddle, because I have presented my analysis, and my intuitive way to reveal the inherent simplicity of any organization I have a chance to visit.  Here is a rough-and-ready process to identify the core problem. 

In 2005 the growth of BigEric Carpets stopped and a decline stated.  We need to identify the core problem that led to this negative effect.

TOC suggests two structured ways to do it.  One is the Current-Reality-Tree (CRT), where we start by a list of UDEs, search for the cause and effect relationships between them and then dive down by asking ourselves "what caused this effect?”  Another way is the ‘Three Clouds’ where we choose seemingly three unrelated UDEs from different functions and generalize the three to the core cloud.

I assume both ways should lead us to the ultimate core problem.  But, there is a trap we better avoid.  We, human beings look for the areas we know well and focus on those areas.  This is a trap, because we might fail to note signals from areas we feel less secure. We might then end up identifying a real problem that causes several other symptoms, but fail to reach the real core problem that causes that problem and many others.

Several people answering this riddle fell into this trap.  It looks as if core problem lies within the management of inventories or it lies within the push of new designs that might not match the changing taste of target markets.  Once you notice that you have identified TWO core problems you might already suspect that the real core problem lie lower and those two are actually caused by it.  Then you might notice that there are other UDEs in the story that are not explained by the two more traditional core problems.  For instance, the CEO is disappointed from his regional managers not taking any initiatives. This seems to me as an undesired effect (UDE) that is not explained by the two proposed core problem.  Another UDE is a complaint of a regional manager that he has no influence and he is looking for another job.

Let me suggest an intuitive CRT for identifying a core problem.  Something that I do whenever I visit an organization.  I try to record any effect that I find significant.  If a certain effect is obviously an UDE causing damage then I record it in my UDE list.  If an effect seems just "unusual” or "strange” or "unexpected by my intuition”, but does not seem to be an UDE, it could even be highly desired, then I’d record it in a separate list of "Other Significant Facts”.

Then I look at the UDE list and try to identify a common cause to all the UDEs.  If I fail I try to make groups of UDEs with a common cause, then look on the groups and try to identify a common cause.

Once I think I've found the core problem, I look at the other significant effects.  Are they explained by the core problem?  After all we know that any problem is a conflict and thus every leg answers a need and thus some needs are fulfilled while others are not.  This means we should expect the root cause to cause some positive or significant effects.

Please, read again the case.  Eric is an entrepreneur who has built a company that has grown in almost a viable vision way.  More, he implemented TOC.  He is also a genius designer. 

Eric is also the CEO that intervenes with every region and tells them exactly what to do.  He also decides upon every single design.  He does not have the time to check the validity of the target levels and he assumes his four deputies don’t have the time for that and he does not trust anybody else, thus he claims that "Goldratt’s algorithm is still the best we can get.”

It seems to me that Eric is not just a bottleneck – he is the CEO that makes himself to be a bottleneck.  This is, by the way, a known characteristic of entrepreneurs. 

How do we solve the issue of an entrepreneur who built a fantastic company to the size he/she cannot manage anymore?

Sanjeev Gupta gives Eric a clever advice to set his mindset and manages a "mistakes buffer” to tolerate the mistakes his subordinates. Within that buffer he should refrain from intervening in order to make them, eventually, good managers able to offload much of he currently does (or fail to do) himself.

If this does not work, then the only way for BigEric Carpets to survive is to remove Eric from being the CEO.

The answer provided by Sanjeev, one of the most experienced and brilliant TOC experts, is right on the spot. I assume Sanjeev went with the same intuitive process as I suggested.  Anyway, he is the clear winner for this riddle.

Sanjeev's Answer (winner):  Eric is the company's constraint. He must be finding it difficult to delegate to his executive team -- even though he wants them to make good decisions and be effective independently of him. What he probably needs is a "mistakes" buffer in his mindset as well as in the company's plans, and use that buffer to delegate and develop his managers.

The rest of the submitted answers are listed below, in alphabetical order by LAST name.

1.  Mel Anderson:  I'm writing this response before I read the above discussion.  I will then read what is said and revise my own answer.    Solving canned case studies is seldom a good learning tool.  Too often students lack enough intuition to know the system being studied, they don't really care about a fictitious company, and they aren't accountable for any solutions.  Therefore, they tell the teacher what they think he wants to hear.  And if the teacher is a traditional non-systems thinker living in the cost world, that's what he will get.  TOC-based analysis is counterintuitive to them.  It happens in business all the time.  This firm probably got into trouble because people made decisions based on local optimizations without systems thinking.  Efficiencies, not throughput, were the basic measurements.  Cost-world thinking prevailed, and cost accounting provided the data for decisions.   The solution must begin with asking the right questions.  NOW I will read the above discussion and questions.  Bingo!  It all points to inventory as a cause for loss of profit.  But declining sales are cited; if the firm made money when sales were at the present level (about a quarter billion) on the way up, why are they now losing money with sales at that level and declining.  A market constraint?  Perhaps, but a smart firm always plans for market issues--competition, saturation, slow economy, style shift, international penetrators, etc.  But if inventory isn't developed and managed with that in mind, the first ends up with too much of the wrong stuff and too little of the right stuff.  Further, in a style-sensitive market, it's important to minimize the time between market demand changes and the firm's ability to deliver the changes to the market.  Long order cycles are fatal when style changes are common.  And all that results in unsalable inventories, high inventory costs, borrowing to meet payroll, vendor and tax demands, and resulting borrowing costs--cash flow problems.   As individual department and division managers saw profits decline, they cut costs without knowing the impact of such cuts.  They were not given the authority to manage fully, and Eric lacked the management expertise to handle it.  He was, after all, a carpet style expert and not a system manager.          Most bankruptcies stem from cash flow problems, not simply loss of profitability.  Core problem: non-system thinking in large dispersed firm, with individual divisions taking orders from the top guy who lacks business competencies.    Hewlett had Packard, Wozniak had Jobs; these firms prospered because they had both ends of the spectrum covered--product and management.  Chrysler was floundering, hired Iacocca and got well.    Solution:  hire a manager at the top who knows how to run the system.

2.  Michael Bolaños: 
Eric's policy to push new designs without adequate understanding of market preferences & changes, and blind reliability on DBM not implemented to respond to true market demand, are the key constraining factors. The core problem is that existing policy is no longer suitable for BigEric. It's like they (or probably just Eric) has grown accustom to his own success and inertia has taken over to keep doing what was successfull once even when it's no longer effective.  Losing sight of the five focusing steps, as BigEric finds growth to be no longer concealing inapropriate decisions, does not allow for BigEric to focus on needed adjustments and changes. The initial DBM algorithm worked perfectly when growth was achieved and no need to eliminate unsold inventory was essential for raising cash flow, now BigEric needs to bring in adjustments to that same algorithm to take into account sales of discontinued SKUs as they get rid off overstock items.  New designs could be needed to maintain leading edge in the market, but pushing designs based on forecast, without first exploring whether each new design will be appealing to customers, is the wrong approach. Eric may like his new designs but it's the final customer the one that decides.  Back to the drawing board for BigEric.

3.  Alejandro Cespedes:  Question 1: What is the core problem of BigEric? I’ll use the three cloud method, so first let´s make a list of three UDEs to start with:

- Sales (and profit) are going down
- There is too much (obsolete) inventory
- Many carpets are sold at reduced prices

Cloud #1 (Eric’s view):
UDE: Sales (and profit) are going down
D: Push new designs
B: Increase sales
A: Be a profitable company
C: Control inventory
D’: Push old designs

Cloud #2 (Bill’s view)
UDE: There is too much (obsolete) inventory
D: Follow DBM
B: Ensure availability
A: Be a profitable company
C: Control inventory
D’: Don’t follow DBM

Cloud #3 (Charlie’s view)
UDE: Many carpets are sold at reduced prices
D: Increase number of designs
B: Increase sales
A: Be a profitable company
C: Control inventory
D’: Reduce number of designs

Generic Cloud
D: Take risks by focusing on potentially successful new designs
B: Increase sales/throughput
A: Be a profitable company
C: Control inventory/cost
D’: Limit risks by focusing on successful existing designs

Question 2: If some critical information is missing – what is it? What did you assume in order to be able to answer the first question? There are several important aspects where no information was given and some assumptions were made.

- Availability: The case made emphasis on excess inventory but availability wasn’t mentioned. I assumed that availability was high because of high inventories and the MTA solution.
- Replenishment time vs. season duration: I assumed that replenishment time was long and that seasons are relatively short (maybe even shorter than replenishment time).
- Number of SKUs. Throughout the case it’s said that there are many designs but no specific number was given. I assumed the number of SKUs are in the thousands.
- Terms and conditions with clients. I assumed that clients embraced the MTA solution.
- Excess inventory. The case didn’t provide the actual value of inventory. This would’ve been helpful to see if there’s a relation between replenishment time and inventory.
- DMB algorithms. I assumed the standard DBM guidelines (100% penetration in the red, 500% in the green, 33% increase/decrease factor).

Question 3: How would you deal with the core problem? To deal with the core problem I would invalidate the assumption between D and D’. According to the cloud, there is a conflict between "Take risks by focusing on potentially successful new designs” and "Limit risks by focusing on successful existing designs”. The assumption behind it is that the way to handle new and existing designs is the same. In other words, that the standard MTA solution is applicable to new and existing designs, and this, as the case clearly demonstrates, is not the case. The direction of the solution would be to establish a way to successfully launch a new design (successfully means to reduce risks, because its impossible to ensure every single design will sell good). Specifically we need the following general procedures:
- Define Design categories: I think they should create some kind of carpet categories so that every design has a specific segment so that it targets specific needs and tastes. In computers for example they have two main users: executives and home users, and two main product lines: laptops and PCs. This creates a matrix of four categories: laptops for executives, laptops for home users, PCs for executives and PCs for home users, each with specific needs and tastes. Eric should also lean on his other designers and the marketing director knowledge, because they can be more sensible to market tastes and needs. When the company started his intuition could be enough, but as the company grew this changed.
- Determine design potential: It’s a mistake to establish a buffer for a new design according the maximum forecasted demand within the replenishment time because first of all, there’s no historic consumption data. And second of all, if the product doesn’t sell well, it shouldn’t even be replenished! I would produce a certain amount of carpets and distribute them throughout the stores. During this time there will be no replenishment or DBM because we are just testing the design. If during a certain period of time (i.e. one month) sales are above a certain threshold, then the product should initiate replenishment with the standard MTA solution (buffers are established with real information, inventory is centralized, replenishment is initiated and DBM is activated).
- Design discontinuation: When a design’s sales start to reduce and cross a certain threshold (units per month), the design should be discontinued. Replenishment and DBM should be stopped and inventory should be moved to the outlet stores to give way to newer and pricier designs that fall under the same category of the design that’s being killed off.
- Assortment management: Design categories should be used to balance inventory. Since we are not committing to availability on new designs at the beginning nor the end, we need to be able to replace some designs with other similar ones that fall under the same category. This way we have balanced inventories at the category level, even if they are not balanced at the SKU level.
- Adjusting DBM policies: It seems to me that the company is using the standard DBM guidelines. I think they should create several policies that will reduce mistakes. There should be an inactive policy assigned to SKUs that are being discontinued of offered at discounted prices, and policies where the accumulated penetration that triggers an increase or decrease is bigger so that DBM doesn’t react so fast.
Eric’s success was due to his unique designs. This worked pretty well for a while but the number of designs increased exponentially. And, since the company was implementing the MTA solution by the book, the result were HUGE inventories which later affected sales by taking up space, cash, delaying the launch of new designs, delaying the replenishment of high runners (stores wait for inventory to go down before buying again), pressuring discounts, etc. He needs to create an environment where he can still launch his new designs, test them out without taking high risks and impacting sales of other designs.

4.  Vivek Chopra:  It is extremely difficult to convey in words what a CRT could have easily conveyed. However, since it is not possible to paste a CRT in the space provided, here is the summary.
1) Core Problem:
The core problem of Big Eric is its lack of decision making on retention or phasing out of designs over time. DBM is just not designed to do that work. As a result BigEric has, it seems, surprisingly perpetuated all or most of the designs that it has created till date. This has eventually impacted the strategic constraint of shelf-space in the outlets. There is no shelf-space available for displaying and therefore promoting the new designs which they are bringing out. The fact that they are bringing out designs late in a market where "customer tastes change rapidly” owing to another small constraint in the form of Eric himself, is a different story .
So to summarize, the core problem is lack of decision making, which is impacting the strategic constraint, the shelf-space. There is another interacting constraint in the form of Eric himself who is becoming a bottleneck in taking decisions on which designs to approve. In short, Eric is not taking any decisions! He is still designing as he used to several years ago.

Impact of Core problem:

BM or DBM rely on human intuition to give them the major computational piece of inventory target levels- what is called the "paranoid” consumption during the replenishment period. Driven by DBM policies which do not take into account Throughput component of the prices offered and just focus on balancing demand with supply, BigEric has actually been producing & storing (through increasing inventory levels) more and more of certain items whose demand is being propelled largely due to price reductions. In all these cases, the inventory targets decided through DBM are being driven by truly "paranoid” consumptions during the replenishment period, as if one needs to be paranoid to the same level for losing sales on a $10 shirt compared to a $100 shirt. These items, many of whom are old, have been produced and sold in ever increasing quantities and at ever reducing prices till the time their demand become non-responsive to any more price reductions and then, they are left with one final, large cycle of inventory which is always in the green. Larger inflows of such items into the outlets have resulted in their promoting the old designs over the new since most of their cash is tied up there. This has resulted in the new designs not doing well, till they too are artificially propelled through price reductions, in which case they too get into the vicious cycle of price (& Throughput) reductions and demand increase, fuelling more production from the plant and so on. Higher and higher production of such old items has also clogged BigEric’s production capacity to the extent that it no longer enjoys excess production capacity. It seems very clear, if one carefully studies the CRT that BigEric is no longer an MTA organization- an internal constraint seems to have developed which has resulted in the increase of replenishment lead time, which in turn has resulted in further increase of inventory targets via BM . The new designs coming in have to have as high as 3 weeks of target inventory level and if they don’t do well, which they certainly wouldn’t, owing to lack of focus, they are stuck into the same rut of decreasing prices and increasing demands (someone in the case mentioned : most of the new designs sold through promotions?). The fact that I am repeating myself further emphasizes the vicious circle that BigEric has moved into . Lack of internal capacity has also led to tweaking of the internal priorities in the plant which may result in further increase in target inventory levels for the old designs, in case their production is passed over more than thrice by the new designs in the plant, resulting in their moving into red for consecutive periods. Owing to all this Big Eric has developed a reputation of being a cheap player owing to its price cuts, which has further driven the customer expectations and brought a particular type of customer to its door who always expects price reductions.


3) BigEric needs to tackle this issue in several steps:

Step 1- Identify the internal constraint that has developed in production.
Step 2- To free up the internal constraint and to be an excess capacity organization, identify designs to be phased out based on T/Cu of the designs and on subjective assessments done by sales/marketing on future viability of designs.
Step 3- For designs that have to be phased out stop production in the plant based on replenishment signals. However, do not stop replenishment from the plant warehouse based on BM signals from the regions, till the entire inventory drops to zero.
Step 4- Disposed of "troublesome” inventory that is not selling at all, after removing labels.
Step 5- Considering that the product lifecyles in apparel industry are low (6 months for best selling items and 1 day for worst selling ones), one has to be careful in setting up realistic inventory target levels else one would be stuck with excess inventory eventually ("eventually” is just 6 months away for most items) lying unsold. This serves the purpose of (a) reducing the risk of being caught with huge inventory and no demand and (b) freeing up production capacity that may be unnecessarily used up in producing unsold inventory and lead to a formation of internal constraint. How much inventory to keep can be decided only after resolving the following conflict:

A- Maximize organizational ROI (maximum possible sales with least possible inventory)
B-Avoid lost sales
C-Reduce excess investment on inventory
D-Hold paranoid levels of inventory
D’- Do not hold paranoid levels of inventory OR Hold conservative levels of inventory

B-D assumptions:
i) Products sold are capable of improving profits significantly. Lost sales really hurt.
ii) High inventory should be held at all locations

C-D’ assumptions:
i) Difference between "conservative” and "paranoid” accounts for a significant amount of money- inventory costs are high

What are the situations that can strengthen B-D assumptions?:

Assumption i) a) In some cases, there is a very high chance that the item is going to be sold in very high volumes.
If such is the case and if one is bringing out an Apparel version of an iPad, then this strengthens the B-D branch and one has no choice but to move along B-D. However this cannot be a generic case.
b) In some cases, the Throughput of the item is very high. This is a little more generic case than (a). If there is an item whose T rate is very high and it can significantly improve profits even if the volumes are middling, one may move along B-D and store paranoid levels of such an item (close to 90% or more service level from the sales distribution function)

Assumption ii) This assumption sounds more approprate for completing condition D, but nevertheless is an assumption that most people make. The question is- Do we need to hold paranoid levels at all locations? Experience tells us that if we hold large enough inventory at the plant warehouse, we may still be in a position to respond to sudden increase in sales at multiple locations, without increasing the overall investment substantially.

What are the situation/s that can strengthen the C-D’ assumption:
If inventory costs are high, this assumption gets strengthened and in such cases we may have to move along C-D’ branch and hold low levels of inventory.

The above observations are enough to intuitively guide us towards a possible solution:

Injection 0- Realization from the above assumptions that Throughput cannot be high by itself but has to be high compared to inventory costs. Ditto for inventory costs. It is the T rate of the product that is more important than T itself since the conflict involves a comparison between the 2 entities.

Injection 1: Determine the T rate of the product. If the T rate is high, hold paranoid levels of sales (maybe corresponding to 90% or above service levels) during the replenishment period. If the T rate of the product is low, hold inventory corresponding to conservative levels of sales during the replenishment period.
NBR: In case of apparels the sales distribution function itself may not be accurate, particularly during the beginning of the life cycle of a new product.

Injection 2 to NBR: For a new product or for a product where predicting sales is very difficult and whose T is high, hold paranoid (or close to paranoid) levels of sales at the plant warehouse. But hold only conservative levels of sales at the outlets themselves. This would still require some level of forecasting on what the minimum and maximum levels of sales could be.

Injection 3- Higher the T, higher should be the level of paranoia. Lower the T, lower the paranoia. By this reasoning, when the price of an item is reduced, T reduces and so the inventory levels should be based on more sober estimates of sales. However the estimates may themselves go up and the net inventory to be held in such a case, would be a result of both. For example, if an item at price 100$ with a T rate of 80% was supposed to sell from 40-80 units (min-max) in a day and the replenishment period was 2 days, one would have probably held close to paranoid levels of 160 (80x2) in the outlets. However, the item did not sell and one had to reduce the price to 50$ with a T rate of 60%. The demand however was expected to increase to 60-90 (min-max estimates of sales) due to reduced price. In such a case one may maintain an inventory of 140 (70X2, corresponding to less than 90% service levels) in the outlet rather than 180 (90X2, close to 90% service levels). Better still, one may store just 120 (60X2) in the outlet but close to paranoid levels at a regional level at the plant warehouse.

Step 6- The conflict in step 5 resolved, BigEric shall need to address the constraint of limited shelf space to display new designs in the outlets. This would imply ensuring that there is always enough shelf-space available in the outlets for new designs. These steps shall have to be taken by the outlets themselves as following:

 Step A: Identify the Constraint- shelf-space for displaying new designs
 Step B: Exploit the constraint: Always ensure availability of shelf space for new designs. In this context, this translates to always ensuring that there is some space in the outlets to accommodate "fresh” designs that are coming in. It could be a rule that says ” Always ensure that at-least 10% of the space in the display shelf is available for new designs”
 Step C: Subordinate everything else to the constraint: Base the decision to reduce price/dispose off as sales, on the display-space available in the store. If less than 10% space is available, immediately take a decision to reduce prices to sell of some of the stock based on the certain criteria. Highest priority would be given to stocks that have been in the Green for 3 consecutive periods and have a low T rate (T rate is the T/Cu for an organization with a market constraint). Stop replenishment of the identified stocks from the plant warehouse to the outlet in DBM.
 Step D: Elevate the constraint: This decision may be taken sometime in future by the outlets, if the sales of all items, even old ones are perpetually high and so creating space for new designs is always a challenge.
 Step E: Don’t let inertia seep in: Go back to step 1: To the extent possible, the shelf space for new designs may be identified as a strategic constraint

In short, any decision to reduce prices in the outlet should be taken only be as a means to provide additional shelf-space to new designs, else not. This will ensure that the outlets are not indiscriminately reducing prices but doing so in a focused manner and to achieve the objective of providing shelf-space for new designs.

Step 7- Improve time to market by reducing the design development time. This may be done by decentralizing design development and by sharing decision making on designs with other stakeholders.

5.  Joseph Hopper:  1. The factories are not producing enough popular/trendy SKUs (and are overproducing slow moving SKUs).

Logic: Eric distrusts regional heads, Hence failure to override DBM at appropriate moments, Hence overproduction of discount-promoted SKUs, hence excess inventory and demands on production capacity, hence low production of desired items, hence more discounting, hence lower T
Also ... it is possible that in this process we have attracted lower-end mass-market distribution channels rather than specialty/trendy channels. Hence their demands for different styles of design than what we offer, and the perception of increasing competition. This also explains why Eric mistrusts the regional heads in the first place, because they are focusing on clearing inventory/selling available designs.

2. Plant capacity (or perhaps storage capacity or cash for inventory) is insufficient to meet demands of the existing system.
or perhaps there is something wrong with the DBM system implemented which would explain under-ordering the fast moving items.

3. Put in place a mechanism for overriding DBM when required e.g.
- When large scale promotions artificially increase demand
- When new products with uncertain demand are first introduced
To convince Eric, explain logic in 1) above. Also that this will only occur in specific defined circumstances and not at every whim of regional managers.
Also, consider fire-selling the dead inventory (esp. if cash is a constraint) and delist dead SKUs.
Refocus the organization on targeting right product mix and store/distributor base once above the availability issues are resolved.

6.  Oded Livneh:
  The prime (not root) problem is arteriosclerosis of the supply chain: extremely slow products block the channels and the display area, and waist the most valuable assets: display area, sellers' attention and, by discounts, customers' will to buy.   The root problem is that the supply chain moves only forward.  The root conflict is between is the flow direction of slow products: Buy-and-scrap slow products, in order to increase other products flow vs.  Leave them in the system, in order to gain profit on them.  The injection is that the profit flow of these certain cursed products is dwarfed by the benefit of the other branch of the cloud.  So, products that are defined as "very slow" (say, that flow less then 10 times slower then the median), should be buy-back, and either scrapped or sold in some market that does not effect the main market, for low enough price.   After cleaning the supply chain from all these slow products, a secondary action that may reduce the amount of slow product in the system may be reducing the initial production batches.  If the product is a hit, the automatic mechanism of the dynamic buffer management (DBM) will increase batches soon and fast.  It it's a fiasco, not so many products will be produced.  Another facet of the TOC solution that may worth attention is reviewing the procedure of when we stop producing a model.  It may have been skipped.  An additional issue may be helping Eric to feel the tastes of the market, by closing a feedback loop: He should know and examine every model that was either a surprising success, or a surprising fiasco.

7.  Felix Sanjuan:  BigEric Issue: T < OE = loss of 25$M
There is huge disconect at BigEric, each fuction (dept) have lost focus on the global goal
Situation has deteriorated to the point where OE and Materials surpass the Sales Turnover
Oportunities to cash on "non-moving" inventories are treated with Costworld thinking
Product appear to be out of sync with new market demand re design patterns
BigEric is stuck in the past
What to do:
Urgent focus on Sales of non-moving stock;
releasing dorment cash to found valid market designs
and needed operations cash
Paralell re-aligment of complete organisation to:
Support Sales with new designs and continued promotions to maximize T

8.  Vilius Seskauskas:  Sales went down from $500M to $252M, however sales in units went down by only 10%. The average margin per unit went down considerably. This happened because of big discounts. Why does BigEric give discounts? They have so much obsolete carpets. One reason for these carpets is the way they set initial target levels. Maximum forecast per three weeks is way too big. Forecasts are often wrong, especially for new products. One can have either lost sales or too much inventory. Current situation in BigEric is too much inventory. It is better to loose some sales on the new designs in the beginning than to have so many inventory and discounts latter. This level should be set as small as possible. What are other reasons for too much inventory? DBM interprets discount sales in a wrong way. There has to be a check box in the program, for the program to understand that a rise in sales is not real. Eric also mentioned that he has no time for such DBM interpretation to fix. The main reason why this happens is because Eric is constantly firefighting instead of looking ahead. Regional managers know local taste better and should be left to judge on their own. Other reason is manual buffer enlargement. One should not do this only because level is "too long in red" - DBM should fix this. Having a lot of designs is not a problem. Problem is about the rules how new carpets are treated. Eric should concentrate his attention on how many new designs should be introduced AND how many old ones should be eliminated.  There is nothing wrong to sell carpets, that were fashionable a year ago if they sell well.  Missing information is time for replenishment. I assume it is three weeks, because of the initial target level.  The core problem is Eric not focusing on the right things.  I made a CRT, but I can't put it in the answer box.