Dynamic Buffer Management (DBM) for the Supply Chain

Dynamic Buffer Management (DBM) for Inventory and the Supply Chain on Prezi

Here is the presentation I made to the RKL eSolutions ERP User Group in Lancaster, PA, on Friday, 11 May 2012. Please contact me directly via the link below if you would like a copy of the accompanying white paper, as well.

Consider the possibilities (especially now, in these challenging times)

A recent survey of published results by manufacturing and service companies[1] that have applied constraint management methods effectively shows:

• A mean reduction in lead time of 70%
• A mean reduction in manufacturing cycle times of 65%
• A mean improvement in due-date performance of 44%
• Mean inventory reductions of 49%
• A mean combined financial improvement (revenue, throughput, profit) of 76%

[1] Mabin, Victoria J. and Steven J. Balderstone, The World of the Theory of Constraints: A Review of the International Literature, St. Lucie Press, Boca Raton, FL, 2000

[Excerpt from Schragenheim, Eli and H. William Dettmer, Manufacturing at Warp Speed – Optimizing Supply Chain Financial Performance, St. Lucie Press, Boca Raton, FL, 2001]

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If you would like help getting started with apply constrain management to your business for rapid ROI and ongoing improvement, please contact me. Find me on LinkedIn.

Finding Common Ground Between the CFO and COO – Part 4

[Continued from Part 3]

The Banking Trade

Our next example of how businesses might leverage business intelligence (BI) to segment their markets and thus allow them to increase throughput in significant ways comes from the banking industry. In this case, a bank creates a data bridge between a legacy database and databases maintained by its departments. The new application gives branch managers and other users access to business intelligence to determine who their most profitable customers were and which customers might be above-average targets for cross-selling new products.

Implementing these new tools liberated the IT staff from the task of generating special analytical reports for the departments and gave department personnel relatively autonomous access to a far richer source of customer-related data.

However, the bank need not stop with “cross-selling.” Consider that if the bank has information on “the most profitable customers,” they could dig deeper to determine the geographic and demographic corollaries among their “most profitable customers.” Uncovering and analyzing these corollaries employed in conjunction with a simultaneous thrust to unlock what the bank’s employees know—that is, tribal knowledge—might help the bank develop carefully targeted irrefusable offers. Such offers would undoubtedly allow the bank to

• Sell more existing products and services to new customers
• Create new offers that will attract new customers from the “most profitable” demographic and geographic market segments
• Create new offers that may interest existing customers and make offers that may be even more profitable for the bank

 

Your Business

Regardless of your industry, it is highly likely that a joint effort made by the CFO and the COO to unlock and join two valuable sources of data will lead to many valuable ideas for increasing throughput. Those two sources of data are

• What is available through (formal or informal) business intelligence about your customers
  
  with
• What is available—but probably undocumented and poorly understood—in the minds of your managers and employees in the form of tribal knowledge.

For this reason, I strongly suggest that for most SMEs (small-to-mid-sized business enterprises) the very first place to look at rapid ROI from business intelligence is to be found in market segmentation.

Understanding Your Customers’ World

One of the errors made by CFOs and COOs in most organizations use a definition of “quality” that is totally objective. After all, how else could or should the firm measure it? Most use a definition along the lines of “without defect” or “within tolerances” or “meeting or exceeding specifications.”

Toyota, however—the firm that came from behind to become a dominating automobile and light-truck manufacturer throughout the world—has learned and predicates it operations on an entirely different definition of quality. Toyota’s measure of quality is:

Does the product make the customer’s experience and results better or not?

Toyota’s concept of quality originated from concepts introduced to Japan in the 1950s by W. Edwards Deming. It was Deming who said:

“Constantly improve the design of product and service. This obligation never ceases. The consumer is the most important part of the production line.”

As a result, Toyota’s measure of quality takes into account, not just what the customer buys, but also:

• Who buys the product: Because the who will lead to different expectations and different feelings about the experience and the results expectations.
• When the product is purchased: Because the circumstances leading to the purchase of the vehicle will also contribute significantly to defining the experience and the results expectations of the buyer.
• Why the product is selected: Because the why is another significant contributing factor to the buyer’s experience and to defining the buyer’s expected results.
• Where the product is purchased: Sometimes product purchases are driven by regional factors (e.g., climate, urban versus rural or back-woods). These factors will affect the buyer’s experience and results expectations.
• How the transaction is structured: The economic construct of the transaction may include multiple factors such as the duration of the warranty, the payment terms, the time of delivery or lead-time, and more. These factors also influence the buyer’s experience and the sense of results.

Segmenting the market requires the whole supply chain to understand the customer because, fact of the matter is, No one in the supply chain has made a sale until the end-user has made a purchase. This is why both the CFO and COO should seek first to understand their customers. Next they should seek to segment their market—because different customers buy under differing circumstances and for different reasons.

These actions should lead to a plan for the creation of irrefusable offers which should, in turn, lead to rapid ROI.

[To be continued…]

Herding vendors, customers and the rest of your supply chain

Not long ago I had an opportunity to watch Temple Grandin, a 2010 biopic directed by Mick Jackson and starring Claire Danes as Temple Grandin, a woman with autism who revolutionized practices for the humane handling of livestock on cattle ranches and slaughterhouses. This is an outstanding film that shows how one autistic woman, through loving support and sheer willpower, has brought much needed change to an industry.

But I think what Temple Grandin brought to cattle-handling has much broader implications. When pitching her revolutionary—and seemingly costly—design for cattle-handling facilities at the first slaughterhouse, she was roundly criticized because the managers and executives say only the cost of building the system. Only through her keen insight and persistence was she able to get them to see that every day they were pay higher costs by not using a system like the one she had designed.

It’s all about flow

Grandin’s vision was simple (see: inherent simplicity). She boldly suggested that the industry will make more money by understanding and working with the cattle than by failing to understand them and constantly struggling against them. Her facilities’ design simply leveraged the natural tendencies of the cattle themselves to keep them cool, calm and collected as they moved through the operations.

She properly pointed out how very costly it was to pay large numbers of cattle-handlers to be constantly poking and prodding the cattle through the chutes. Not to mention the lost time, lost productivity, and damage done when the anxious movements of the cattle led to backups, herd-busting breakouts, or animals with broken legs that required heavy equipment to get them out of the way.

Grandin was all about “flow” and how an unperturbed flow would increase both production and profitability.

Lessons learned

I don’t want to take anything away from the best reasons to watch this wonder film: Temple Grandin. The best reason to watch this film is, of course, because it is such a wonderful story about overcoming adversity and achieving something when it seems that all the odds are stacked against you.

Nevertheless, I think there is a huge message here for business—and the supply chain.

Why do we hire so many “cattle-handlers” and spend so much time, energy and money poking and prodding our customers, our vendors, and—yes—our employees trying to get them to move along a little faster? Why do we spend so much of our time, energy and resources trying to get the flow moving again when our vendors or employees just don’t seem to “act right”? Why is it our all too frequent first response to problems with our supply chain—from one end to the other—is, “We need to hire more ‘handlers’ to keep the flow moving”?

Don’t we have enough “handlers”? Don’t more “handlers” just keep adding to our operating expenses and make it just that much harder to turn a profit?

Isn’t it time that we took time to really understand what motivates, demotivates or even stampedes our customers, our vendors and our employees?

What we’re looking for is “flow” that doesn’t require so much poking and prodding. The way to get is to work with those who must contribute to the flow. Poking and prodding—and hiring more “handlers”—is just too costly. So, it’s time to redesign our flow in a way that leverages the participants’ natural motivations for productivity, profit and success.

What do you think?

How do forecasts fail? Let me count the ways…

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 a Kinaxis Supply Chain Community]

CFO Magazine’s 2011 Conference on Corporate Performance Management (CPM)

I am pleased to announce that I have been selected by CFO publishing to officially blog on their Corporate Performance Management Conference to be held in Dallas, Texas, September 11-13, 2011. The focus of the conference will be improving business analysis and bottom-line performance. As you know, both topics are near and dear to my heart, so I look forward to hearing what the great line-up of speakers will have to say on the topic.

Speakers will include:

• Thomas Davenport, President’s Distinguished Professor of Information Technology, Babson College; author, Competing on Analytics and Analytics at Work
• Wayne Eckerson, Founder and President, BI Leadership Forum; author, Performance Dashboards: Measuring, Monitoring, and Managing Your Business
• Eric Lundberg, SVP & CFO, ALM
• Steve Player, North America Program Director, Beyond Budgeting Round Table (BBRT)
• Robin Washington, SVP & CFO, Gilead Sciences Inc.

If your business could benefit from better understanding the processes, structures, tools and people required to achieve the kinds of changes necessary to make you more profitable tomorrow than you are today, then this conference could be just the ticket for you or some members of your management team. By clicking here, on the picture above, or the CPM icon in the column to the right of this post you can register now. Better yet, by entering the code “BLOG” along with your registration, you can save $400 off the normal registration price! Don’t delay your registration. Do it today.

This is your opportunity to learn from real movers-and-shakers about how to leverage dashboards, budgeting, planning, and forecasting toward improving your firm’s bottom-line. Even assessing the performance of  your supply chain and the inherent risks you might face are covered.

See you there!

The Dangerous Dichotomy—Part 3

[Continued]

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.

Why?

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?

The Dangerous Dichotomy—Part 2

[Continued]

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]

What does “demand-driven” really mean?

Recently I stumbled across a whitepaper entitled Demand-Driven Inventory Management Strategies: Challenges & Opportunities for Distribution-Intensive Companies (Fraser and Brandel 2007) prepared by Julie Fraser and William Brandel, principals at Industry Directions, Inc. What I found amazing about this article is that it doesn't really get to the point of "demand-driven inventory management strategies." Instead the focus is on better systems, better data, better use of the data, and better forecasts at the SKU level (rather than at the "product family" or "product category" levels).

Now, maybe I'm an idealist, but when I think of "demand-driven" inventory, I think of an integrated supply chain that functions in such a way that when an end-user takes a unit of product off the shelf at the retailer's store (or whatever model is being used), that action triggers the production of one unit at the manufacturer's plant with a minimum of mid-stream manipulation.

See the accompanying illustration, and let me describe for you my concept of a demand-driven supply chain. We will start at the bottom of the illustration – where the action begins – at the retail store. Ideally, each retail store should stock just enough product to cover one day's sales plus a "buffer" to allow for expected variability in demand.

At the end of each business day, the retailers should transmit to their associated distribution center (DC) the quantities sold of each SKU in the supply chain depicted. It doesn't matter whether the DC is owned by the retail chain or the distributor, the process would and should work the same.

Next, depending upon the agreed replenishment cycle (although daily is ideal), the DCs would prepare replenishment orders to be shipped to the retail outlets. The goal would be to replenish exactly the quantity that was reported as sold (plus or minus any adjustments for seasonality, special promotions, etc.) at each outlet. Meanwhile, the DCs will have reported to their supplying warehouse how many units of each SKU that they have sold (again, plus or minus any adjustments).

Each DC should stock only enough of each SKU to cover the replenishment cycle from the domestic warehouse plus a "buffer" to cover any variability in demand. On its scheduled replenishment cycle – and, again, daily is ideal – the domestic warehouse should ship out replenishment orders to the DCs. In the meantime, if the replenishment cycle is longer than one day, the domestic warehouse will have transmitted daily sales numbers back to the off-shore warehouse, so that the consumer purchase made at the retail outlet is transmitted all the way back to the manufacturer within one business day.

Following the pattern we have discussed already, the domestic warehouse should carry just enough of each SKU to cover variability in demand and supply (lead-time). The size of the "buffer" should include a calculated allowance for disruptions in the supply chain where it is most vulnerable (e.g., overseas transportation, or other). Naturally, since this represents aggregate demand, estimates of demand will be more accurate at this level than they will be at either the DCs or the retail outlets. As a result, the domestic warehouse inventories will be larger, but not nearly as large as if each lower level in the supply chain tried to estimate (read: forecast) demand for periods into the future. This approach helps keep inventories to a minimum and makes the whole supply chain more responsive to changes in demand.

Likewise, the foreign port warehouse should carry just enough stock of each SKU to cover variability in demand from the warehouse(s) on the opposite shore plus any variability in lead time from the manufacturing plant which, as we shall see, should be near zero.

Since estimates of demand variability will be most accurate at the level that demand is most highly aggregated, the manufacturer is the most reasonable place to keep the largest "buffer" of inventory for the SKUs in the supply chain. The manufacturer should carry enough stock of each SKU to cover production lead time variability. (Typically, this buffer length should be only three times the actual production time for each SKU. That is to say, if a day's aggregate supply of SKU #1001 can be produced in a single day of production, then the buffer for SKU #1001 should initially be set for three days. Then production should be scheduled in batches as small as is practical for the SKU.) Generally, production should be scheduled at the manufacturing plant based on producing the actual demand reported via the supply chain plus enough to fill any "holes" created in the buffer created by unusual demand in a prior period.

Now, that's what I call a "demand-driven" supply chain. It is do-able and it makes life better for everyone. Here's why:

• Lower inventories everywhere
  
• Reduced write-offs due to obsolescence
  
• Lower inventory carrying costs all across the supply chain
  
• Manufacturing is more responsive to changes in market demand – not separated from real feedback by weeks or months
  
• Fewer lost sales due to stock-out (And the value of lost sales are almost always under-estimated in supply chain calculations simply because they are done by "averages," but the items most likely to suffer stock-outs are the most popular selling items, not average performers.)
  
• Reduction or elimination of expediting costs across the whole supply chain
  
• Dramatic reduction in overstocks (and about 73% of companies report overstocks simultaneously with expediting for items that are running short), which leads to less price-cutting to liquidate unneeded inventories
  

©2010 Richard D. Cushing

Works Cited

Fraser, Julie, and William Brandel. Demand-Driven Inventory Management Strategies: Challenges & Opportunities for Distribution-Intensive Companies. White paper, Boston, MA: Industry Directions, 2007.