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Are your metrics working against one another?



In the former Soviet Union (USSR), an professional weight-lifter was promised a bonus every time he broke a world record. So, being a shrewd “capitalist” (I guess), he decided to break world records one at a time—one or two grams at a time. Naturally, he got many, many bonuses, but it isn’t exactly what his handlers had in mind.



Some organizations pay rewards to their marketing department based on a “new customer” metric—the number of new customers garnered over a specific period of time. Of course, the idea is to build the customer base.



Meanwhile, many of these same businesses reward their sales department to meet or beat quarterly sales goals. So, in far too many cases, their salespeople are out burning through customers—alienating them through high-pressure sales techniques—in order to make their quarterly bonuses.



They may also reward their inventory managers to keep their inventory lean. So, while the salespeople are out making customers angry while getting their end-of-quarter orders (to get their sales bonuses), the warehouses are leaning out their inventory to meet end-of-quarter inventory numbers in line for their own bonuses. So, when many of those orders need to be delivered, they will be late—making the an already alienated customer all the more angry with the treatment endured.



I could go on, but I won’t. I’m sure you get the idea and you’ve suffered (or at least heard of) some similar well-intentioned reward systems go awry.


Some have suggested that these are “reward-motivated abuses,” seeking to blame the employees for doing exactly what management has told them to do, and for which management has agreed to reward them. How, then, can these be “abuses”?


Too much complexity


The problem here is not that the intended goals are not worthy: of course companies want more customers, more sales and lower inventories. The problem is the inherent conflicts evoked by the presence of too many “levers” being offered without linkages.



What’s lacking is a unified goal upon which the whole “system”—the whole organization—can be measured and each participant in the process of reaching that goal might be appropriately rewarded.



Simpler really is better.


“Simple” levers and the “simple” linkages


Link Actions to Financial Goals.jpg
The linkages are simple, but in order to prevent your organization—or any part of your organization—from sacrificing tomorrow’s profits for today’s bonuses, your (for-profit) organization’s singular goal should be simple as well. Eliyahu Goldratt set it forth so clearly years ago: The goal is to make more money tomorrow than you are making today.



This simple goal is very easy to understand and very measurable—and it will help prevent improper actions like the following (an many, many more):


  • Burning through customers to make short-term sales goals—because of the reduced long-term Throughput and the added operating expenses required to capture new customers    
  • Slashing inventory to reach inventory goals at the risk of alienating customers—because it drives Throughput down and operating expenses up    
  • Using company politics to cover or support inefficient or ineffective work efforts or policies—because it drives operating expenses higher (among other things)



Think about it. I think you’ll really like “simplicity” compared to “complexity” once you understand how it can drive your whole “system”—your whole organization—toward improvement (instead of piecemeal).



What do you think?


[Cross-posted at GeeWhiz-to-ROI]

I’m sure many of you are familiar with the common Venn diagram of “project  management success.”

FIG PM Budget-Time-Quality.jpg

PMI (Project Management Institute) and  others advocate that a project is successful if it is on-time, within the  budget, and of high quality (or, at least, meeting the project’s original  standards for quality). Of course, this is true when compared to the  alternatives of over budget, late or of poor quality.


But, in the business world, we shouldn’t undertake projects—any kind of  improvement project—for the sake of the project itself. So, while this might a  satisfactory view of the project manager’s or the project team’s performance, it  really doesn’t tell us very much about the net effect on the business.

Another popular Venn diagram used relative to technology deployments is the  processes-people-technology one.

FIG PM Processes-People-Technology.jpg

Here the aim is assure that the technologists involved in the project  carefully consider the business processes that must be supported by the  technologies deployed. Furthermore, the IT folks should also understand the  people involved and they will desire to apply and benefit from the new  technologies.


However, once again, we should be reminded that a business enterprise should  never undertake any kind of improvement project merely to automate  business processes for automation’s sake. Nor should they undertake an  improvement project with the sole aim of people-pleasing.


In a for-profit organization, there are proper metrics to use for IT  decision-making, but these are not the ones.


Consider, for example, the business that spends $150,000 on an IT project.  The project is deemed to be “a resounding success” based on the following  results:

  1. The project was completed on time
  2. The project was completed under budget
  3. The project met all of the initial quality requirements
  4. The project’s technology deployments properly supported the intended  business processes
  5. The project’s new technologies were well accepted and utilized by the people  involved
  6. The company was no worse off after this major undertaking (and everyone has  heard the horror-stories of huge IT failures)


So, the project management team all got big pats on the back and a few VP’s  got bonuses and all the stockholders and stakeholders are pretty happy about the  whole “successful project” thing.


But, my question is: Should they be happy?


They just spent $150,000 with an admitted ROI (return-on-investment) of a big fat ZERO!


To me, that’s just not good business!


There is a Venn diagram that I, personally, have never seen, but it is the  one Venn diagram that makes sense for business investments of every kind because  it includes the three factors that should always be considered for “success.”  Here it is.


Here are the questions that should be asked about every improvement  project—IT-related or not:

  1. How much does the project increase Throughput (where  Throughput is defined as revenues less truly-variable costs directly linked to  producing the revenues)?
  2. What affect does the project have on Operating Expenses? Do  they go up or down? If so, by how much? Is the change “real” or a calculation  based on “savings” when no one will actually be laid-off or no additional  Throughput will consume the man-hours “saved”?
  3. How much will our Investment change? Besides (as in our  example) the $150,000 we will invest in the project itself, will our inventory  go up or down? Will we need to invest in new buildings, or can we sell off some  capital equipment and increase our cash?


When you have the answers to these questions you will have the  answer as to whether your technology project was just a “project success” or a  “business success.” And, while the numbers may not be precise, knowing that they  are approximately right will give you far better understanding of your company’s  success or failure than not considering them at all.


What do you think?


[Cross-posted at GeeWhiz-to-ROI]

The only certainty about forecasts is that they will be wrong. So, let’s start to enumerate some of the reasons forecasts are wrong:


  1. Frequently, they aren’t forecasts at all; they are only guesses
  2. As W. Edwards Deming said, “Wherever there is fear, you will get wrong numbers.”
  3. Forecasts are not prophecy and were never intended to give the actual answer to, “How many units will be sold next month?”
  4. Forecasts are always based on assumptions and frequently the assumptions are wrong
  5. Forecasts attempt to predict variable behavior into the future
  6. Forecasts cannot take into consideration every potential variable that might affect the result for two reasons: a) we don’t know all the variables, and b) even if we did, there isn’t enough computing power in the universe to take them all into consideration
  7. Forecasts almost always are given as a single number (in the business context) when, in fact, they should be expressed (at a minimum) as a number and the standard deviation surrounding that number
  8. Many forecasts originate with salespeople
  9. The salesperson provided his “best guess” forecast
  10. The salesperson provided what he/she thought he/she could sell
  11. The salesperson provide a “safe number,” so that he/she can “hit her target”
  12. The salesperson provided an “average” calculated from who knows what—last year? last three months? extrapolated from last week?
  13. The salesperson provided a “big number” and will try to hit it because of pressure from sales management
  14. We try to forecast too far into the future—say, three months instead of three days
  15. The forecast is based on the assumption that—except for the things we specifically know will change—everything else will remain the same (but it never does)
  16. Our suppliers’ lead times are unreliable, so we don’t know the actual period our forecast needs to cover
  17. We forgot to carry the 2 when doing the math
  18. Our Excel™ spreadsheet formulas and references are off, but we haven’t noticed it yet
  19. Our forecasts for our finished goods are pretty good, but when MRP blows down through our multi-level BOMs, the forecast explodes due to our minimum batch sizes, percent-over and other production policies
  20. Some departments just can’t get their homework done on time and we have to produce a number from somewhere



Go ahead, feel free to leave your comments adding to the list.


[Cross-posted at GeeWhiz-to-ROI[

Somehow, in the dark recesses of the past, someone came up with the idea that  we should (at least in our minds) segregate our regular stock (inventory  quantities) from our “safety stock” as if there were some difference between the  two. “Safety stock,” APICS and others suggest, is to cover “variations” in  lead-time or demand, while our “regular stock” is to cover “normal  demand”—whatever that is. But for most businesses today, variation in  demand is the rule, and not the exception. Furthermore, isn’t  it true that our whole stock quantity is really what we want to  manage—not some isolated portion of our stock that we describe logically as  “safety stock.”


Simpler is better. Our whole stock quantity should buffer the system (read: the whole enterprise) from losses in throughput (read:  profits).


For years I have worked with small-to midsized enterprises (SMEs), many of  which I first touched when they were in transition from entrepreneurial to  enterprise in nature. When I found them, they generally knew very little about  their inventory. Oh, sure: they knew in a general sense which items were  profitable and which were not. They also had a general handle on which items in  their inventory were the “fast movers” and which were “the dogs.” Nevertheless,  when it came to managing their inventory quantities they almost all struggled  with the all too common problem of being sold-out of some items (and thus  incurring losses of potential sales and profits) while, at the same time finding  that they were overstocked on dozens of other items (so that they were  simultaneously incurring high carrying costs and lower cash flows as a result).  The problem was, from month to month, it was almost never the same items that  were sold-out versus over-stocked. They could never predict what quantities were  going to sell, so they couldn’t predict what quantities to stock.


Constraints management (Theory  of Constraints) suggests—as I said above—that our whole stock of any item  (taken in total) should serve one purpose: to buffer the system from losses to  throughput. Now, it is not the purpose of this present writing cover all of the  various details of a full Dynamic Buffer Management solution. The simplicity of Dynamic  Buffer Management (DBM) is what makes it so appealing. The following is a  real-life application of DBM in action.


The raw data we have on our example SKU looks like this:

ToC DBM RawData 20110812.JPG


We have just two months of data from 2007, full years’ data from 2008 and  2009, and a partial year for 2010. Note that demand in 2008 was fairly stable,  ranging between 72 and 220 units per day. However, demand is 2009 become wildly  erratic—ranging from just 1 unit per day to 389 units per day. Over the entire  recorded history for this SKU, we find the following statistics:

ToC DBM SKU Stats 20110812.JPG


If we graph these data, the results look like this:


ToC DBM Graph 20110812.JPG


Now, it’s nice to know that a third-order polynomial curve fits pretty nicely  with a six-period moving average of these data, but most SMEs do not have a  staff statistician available to them to help analyze all their inventory history  in order to determine how to set parameters like stock levels, safety stock,  reorder points, line points and more. Nor, do they have confidence that  statistics will necessarily serve them better than their intuition has in the  past.


What they are looking for is something SIMPLE, RELIABLE, EASY TO UNDERSTAND  and EFFECTIVE. Dynamic buffer management is all of that.

Let’s imagine that we are at the end of year 2008 and we want to set up DBM  for year 2009. We’re going to do so based on our 2008 history.


The first thing we need to know is: how big should our starting buffer be for  this item?


Well, it ain’t rocket science! Establishing a starting buffer  quantity requires the knowledge of a few facts because it is more important to  be “approximately right” than to be “precisely wrong.” No matter how much  precision (read: time, energy and money) is put into calculating a “precise  number” for the size of the buffer (or any other business ‘forecast’ number)  that number will end up being “precisely wrong” 99.999 percent of the time.


So, to find an “approximately right” number for the starting buffer is  more important than finding a “precisely wrong” one. In our example, we used the  following formula:


Starting Buffer Size = average period consumption over the  Last 12 months + (safe replenishment time in days * average consumption/day * 2  * paranoia factor)

Some of these numbers are arbitrary:

  1. “Safe Replenishment Time” is nothing more than a “safe” estimate of the time  it would take to replenish the item under normal circumstances. Almost anyone  working in purchasing or replenishment or manufacturing can pick that number for  items with which they work day-in and day-out. If one says, “Five,” and another  says, “Eight,” then use eight. It’s that simple.
  2. The number “2” used in the formula is also arbitrary. It is nothing more  than an additional safety factor to cover unusually high demand or unusually  slow delivery. In a moment you’ll see why it is not terribly important in the  long run.
  3. “Paranoia Factor” is our third arbitrary number. This value is used to cover management’s concern about things like:
    1. “Our inventory will skyrocket” – so let management set a paranoia factor of less than one on some items
    2. “If we run out of this item, we lose sales on other things, too! – so  increase the paranoia factor
    3. “This is a high-margin item and we don’t want to lose a single sale” – so  make the paranoia factor larger


For our example, we calculated a starting buffer size of 11,954 base  on a paranoia factor of 1.000. Let’s watch what happens using the  actual consumption figures from year 2009.


ToC DBM DBM Example 20110812.JPG


Now, let’s see how DBM helps us out:

  • Period 1: We just stocked up to almost 12,000 units and in period one  we had the worst month ever! We sold only 23 units! Have we done the right thing  here?!?
    Even though it seems like we have plenty of stock, we follow our  basic rule: Whatever we consume, we replenish. So, we place a replenishment  order for 23 units.

    At the end of the period, our “Buffer Status” = 99.81  percent. We have almost a full buffer.

  • Period 2: Things return to normal now. We consume 3,315 units, we get  our replenishment supply of 23 units, and we end the period with a buffer status  of 72.27 percent. That’s okay. We really don’t get concerned as long as the  buffer remains in the green zone—that is, above two-thirds.

    We  dutifully place our replenishment order for your consumed quantity—3,315  units.

  • Period 3: We consume 2,153 units and get our 3,315 units from our  replenishment order. True to form, we order replenishment for the 2,153 units,  and we end with the buffer solidly in the green at 81.99 percent.

  • Period 4: Wow! We consume 7,903 units; get our replenishment of 2,153  units and our buffer status ends up in the red zone. The red zone is a  buffer below 33.33 percent full. [NOTE: Here I’m going to play along with some  anomaly in Excel’s failure to calculate and apply conditional formatting  correctly. We’re at 33.89 percent and this should be “Yellow,” but it’s not.  Excel says it’s “Red,” so we’re going to call it “red.” Close enough!] We take  no immediate action other than to note that this is the FIRST PERIOD in which  our buffer has fallen into the red zone.

    We place our standard  order to replenish period consumption.

  • Period 5: We have another great period for this item. We consume  8.476 units; get our replenishment order for 7,903 units, and end the period for  the SECOND PERIOD IN SUCCESSION in the red zone. The buffer reached 29.09  percent.

    Other than placing our replenishment order, we take no specific action.

  • Period 6: We’re hit with record sales and move 11,666 units. Even  after replenishment order arrives, we still are sitting near the bottom of the  red zone at 2.41 percent.

    Since this is the THIRD SUCCESSIVE  PERIOD where we have ended up in the red zone for this buffer, we  take action to INCREASE THE BUFFER SIZE BY ONE-THIRD. Our replenishment order is  now for the 11,666 units consumed PLUS the buffer increase of 3,985  units.
  • Periods 7 and beyond: We will continue to monitor and manage the  buffer dynamically applying these simple rules…


As you can see, this is a very SIMPLE, YET EFFECTIVE, way to facilitate stock  management. There are some other principles that should be understood—such as  the fact that the BUFFER actually contains both the stock in the warehouse and  what is in-transit (or, in manufacturing, if a make-item) and is due within one  “Safe Replenishment Time” period.


This is so simple!


Most inventory systems could do this with relatively minor tweaks. It is  really just managing inventory by “max stock level”—when quantities fall below  the maximum stock level, replenish back to the maximum stock level—with some  kind of data view (perhaps even using Microsoft Excel™) to display the buffer  status with action signals.


Let me know what you think.


[Cross-posted at GeeWhiz-To-ROI.]



The conclusion of the preceding article was that, without doubt, reducing  out-of-stock occurrences will tend to increase revenues. Increasing revenues  will certainly satisfy the sales and marketing team, who have been mandated by  the firm’s executives with doing that very thing. But, the question remains, can  actions be taken to reduce out-of-stock occurrences in such a way that will  satisfy what should be everyone’s goal of helping the business make more  money tomorrow than it is making today?


We believe it can.


Consider a distributor that buys products from Pacific rim suppliers. One  line of products produces gross profits of about 80 percent. Of the costs  associated with this product line, about 15 percent are the actual product cost  (including any taxes and duties). The remaining five percent are the costs per  unit of shipping the product by ship from its source to the firm’s distribution  centers.


Like the product in the example provided in the preceding article (see “The Dangerous Dichotomy—Part 2”), this line comes in an array  of styles (or color or sizes). Some of these variants sell better than others,  naturally. However, because the distributor (wrongly) believe that they are  stuck with a three-month or longer lead-time to get these products,  they feel that they must forecast demand well in advance and place their orders  based solely on this forecast.


The three-month lead time consists of the time it takes to produce enough  product to fill a container (or meet some other policy-based “cost-saving”  arrangement), plus the time for ocean-going transportation, and the time to get  it takes to get the items through customs and provide land transportation to the  destination distribution centers. But, because the forecast is always wrong, the  firm inevitably finds itself in the situation we described in “The Dangerous  Dichotomy—Part 2”; that is, they experience out-of-stocks on several of the  variants while being overstocked on several other varieties of the product.


The firm is aware that they can ship these items by air—in much smaller  quantities, of course. However, doing so doubles the per-unit cost of  shipping these products.


When managers hear that simple phrase: “Shipping by air doubles our  freight costs,” that is usually all they need to hear. They think of those  “slashed margins” and “higher costs” and that is where the conversation  ends.


But, consider this: Doubling the per-unit cost of shipping on this  product line reduces the margin from 80 percent to 75 percent. Sure,  that is, in fact, a reduction in profit margins on this product  line.


Now, consider this: Shipping by air forces shipment in smaller  batches. The smaller batches in the shipments mean that the manufacturer can  produce the batches for shipment in less time—perhaps as short a time as a few  days. Shorter lead times mean the original forecast and the original  order need only cover the starter stock—the stock to be sold while the firm  figures out what styles or colors are going to be the “big-sellers.”


When the “big-sellers” are known, replenishment stock can be ordered and  shipped by air, but the firm is likely to actually make more money than  they did when they were paying lower shipping costs.




The reason is simple: At a 75 percent gross margin and a five percent  increase in shipping costs—between multi-mode sea-land transportation and air  transportation—every additional sale (resulting from reduced  out-of-stocks on the popular models) covers the difference in shipping costs for  15 units (i.e., 75 percent gross margin divided by the five  percent increase in shipping costs).


Besides the obvious advantage found in the extremely high likelihood of  increased profits—despite “doubling your shipping costs” and suffering “reduced  margins”—this thoughtful approach has all of the following advantages, as  well:

  1. Happier and more satisfied customers
  2. Less likelihood of customers being lost to competitive sources
  3. Fewer lost customers means the firm is more likely to be able to sustain  revenues with lower marketing costs
  4. A happier and more productive sales and marketing staff—able to spend their  time capturing new customers and markets instead of appeasing disgruntled  customers who could not buy the product they wanted
  5. A happier and more productive organization overall—with less in-fighting and  a real sense of success and accomplishment
  6. More satisfied management and executive team
  7. A far greater opportunity for success in the future


All of these benefits accrue to an organization that discovers “system  thinking” (i.e., seeing their organization as a whole, rather than as  disconnected pieces and departments). Meanwhile, the firm still caught in “the  dangerous dichotomy” is still fighting fires day-by-day and trying to keep the  smoldering animosity between the factions from breaking out into open  warfare.


Makes you want to give “system thinking” a try, doesn’t it?


Cross-posted at GeeWhiz-to-ROI.



In the preceding article we discussed how—all too frequently—management inadvertently creates a schizophrenic organization by assigning responsibility for increasing revenues to one part of the organization while assigning cost-cutting to another part of the organization. Usually the other part of the organization is everyone else—everyone not assigned to the task of increasing revenues. What happens in such cases, is that the business is driven to a dichotomy that tends to pull the organization apart.




Of course, this effect of pulling the organization apart is entirely unintentional. Management wants to move the business toward greater profits and profitability. Sales and marketing—those generally commissioned with increasing revenues want the organization to succeed and grow. And, all the others, whose marching orders are to cut costs also really want the company to find success. So they are doing their best to keep costs down.


Nevertheless, seeming unreasonable demands made by sales and marketing are a nearly constant irritation to inventory and production managers. And what appears to be the simple inability of folks in purchasing, production, scheduling, warehouse and shipping to get their house in order so that sales and marketing can achieve their goals of increasing revenues is a cause of very real frustrations.


So, even though everyone in the organization really wants to move the organization toward success, it is clear that no one in it has a view of what it takes to make the whole organization—the whole “system”—move in the desired direction. Those who are instructed to “increase revenues” have no real view or interest in holding the line on costs or operating expenses. But, what is worse, those who have been instruction to “cut costs” generally have no visibility into what it might take to increase revenues. They are not privy to the “levers” that might affect increasing sales. Plus, the various departments involved in “cost cutting” are quite often, themselves, fragmented in their view of what it takes to be effective.


A simple example


Let’s take one simple example relative to supply chain thinking.




Most businesses vastly underestimate their losses from what they too frequently believe is a good thing. When they say, “Folks, we sold out of product X!” they are frequently thinking: “This is great! ‘Sold-out’ means we have lower inventories! It means we sold more than we expected to sell!” or similar thoughts.


But look at the results of out-of-stock conditions in the example above.


First, everyone needs to recognize that the things that “sell-out” are the most popular items. Second, because these are the most popular items, there is no reliable way to know how many more units the firm might have sold if they had had more units in stock. Certainly extrapolating from “average sales” is insufficient.


In our example (above), a product comes in five styles (‘A’ through ‘E’). The firm chose to stock 280 of each of these five styles and the quantities actually sold are found in the “Qty Sold” column.


In our scenario we are supplying what cannot actually be known—that is, the actual market potential (“Mkt Potential”) for each style. In this case, the firm ended up selling-out of two styles (‘C’ and ‘D’), while being overstocked on Styles ‘A’, ‘B’ and ‘E’. Extrapolating from “Average Sales” one might believe that the firm lost $5,400 in revenues. However, when calculated from “market potential” for each style, the actual amount surrendered in lost revenues due to being sold-out calculates to $12,900—more than double the estimated losses from averages.


Of course, this lost-sales number is a guess—since there is no reliable way to know the actual market demand for a sold-out item. But, what is not a guess is that when a business is out-of-stock on a popular item, it is almost certainly also losing sales on other items when customers go elsewhere for the items they are seeking. Plus, every time a customers goes shopping somewhere else, the “out-of-stock” business stands a good chance of losing the customer to another supplier.


Doubtless, reducing out-of-stock occurrences will increase revenues. That will help satisfy the sales and marketing team in our troubling dichotomy above. But, the question remains, can that be done in such a way that will satisfy what should be everyone’s goal: helping the business make more money tomorrow than it is making today?


[To be continued]        


Cross-posted at GeeWhiz-To-ROI.

Far too many business executives have created an artificial dichotomy  within their own organization that is potentially dangerous to their  firm's survival and almost certainly destructive of profits. What is  that artificial dichotomy, I hear you ask?


The answer is simple: Businesses all too frequently put the responsibility for increasing revenues into  the hands of one part of their organization, while putting an entirely  different group--usually most of the rest of the organization--in charge  of reducing costs.


While, on the surface, this may seem to make sense; it really does not.

Here's why.


The Revenue-Increasing Group

The  folks in the organization put in charge of increasing revenues--usually  the sales and marketing departments--generally are measured only on the  things pertaining to revenues. Because it is not a part of their reward  metric, the folks in sales and marketing are, therefore, wont to make  decisions that may:

  1. Increase the costs of production
  2. Drive inventories up
  3. Increase operating expenses
  4. Reduce output


Now, they don't do these things intentionally. They are just trying  to do what they have been mandated to do by management and senior  executives.


But, if increases in revenue are stymied or shrunken by, say...

  1. Failures to meet delivery-time promises
  2. Out-of-stock conditions on finished goods or components
  3. Lay-offs or cut-backs in production, warehousing or elsewhere


Then, the revenue-increasing group has an "out" for not  performing up to expectations or forecasts. Their excuses are generally  based on the performance of the other part of the organization.


The Cost-Cutting Group

The other part of the  organization is, as I said, usually all the rest of the organization.  These folks have all been instructed and, frequently, are being measured  based on "keeping costs down." There interest is in doing everything  they can to...

  1. Keep the costs of production down
  2. Holding inventory levels as low as possible
  3. Making sure that operating expenses are minimized


These parts of the organization's management also want the  organization to succeed. But they are not being measured based on the  organization's (the "system's") success. They are being measure on their  performance against budgets for costs and expenses.


The folks working in these other departments have no malice of  intent, but when sales and marketing brings a request to engineering or  production that is going to increase the costs of production, they are  not likely to look too kindly upon the idea. When sales tells these  folks that they could sell more if they just had more inventory, they  may nod their heads in affirmation, but the are not likely to take  affirmative action because they aren't rewarded for that effort. To the  contrary, they are more likely to be rewarded for holding inventory  levels down and increasing inventory turns.


So, the battle rages

And, of course, the battle does not end there. When  cost-cutting fails to make the firm more profitable, this group is just  as willing and able to point fingers at the "sales guys," and point out  how their frequent interventions, their calls to change production or  shipping priorities, and their demands that end-of-period orders "get  out the door" prevent serious cost-cutting by...

  1. Driving overtime expenses up
  2. Increasing requirements for both raw material and finish goods inventories
  3. Reducing production by breaking up shop floor production runs with new priorities on a daily basis


Hence, these two separate factions--who should be working toward a  single end--are first formed by management and then each becomes the  excuse for the other for non-performance. Meanwhile, the firm as a whole  suffers reduced profits, higher operating expenses, and--generally  speaking--too much inventory (made even more unbearable by having too little of the things that the customers want when they want them).


To be continued...

If your organization is not  presently experiencing this warfare--even if subtle or boiling just  beneath the surface of a "mask" of "team work"--then you are a  fortunate one and, more likely than not, you know a firm or have worked  in a firm where this is or was true.


This internal conflict is evidence of the lack of "system  thinking." When executives give different directives to different parts  of the organization--in the hope of squeezing some profit out of "local  optima," rather than global metrics that encompass the goal of the whole  system--the whole organization--this is what one must expect.


There is an answer.


[Continued next post....]


Cross-posted at GeeWhizToROI.