Bad policies hurt the supply chain

I think just about everyone involved with understanding and managing supply chains agree that the supply chain works best when volatility is minimized. Some organizations go to great pain and expense trying to figure out ways to manage their supply chain when faced with sudden demand changes and volatility.

Nevertheless, many supply chain participants continue to maintain policies that actually increase volatility in their own supply chains. Here are some examples:

1. Short-term promotional pricing
2. Volume discounts linked to shipment batches
3. Period-end promotions
4. Salesperson incentives linked to period-end dates

Short-term promotional pricing

Short-term price promotions contribute to the bullwhip effect and create tremendous inefficiencies all up and down the supply chain. The policy—especially when repeated with some frequency—causes buyers to hoard product. They buy extra-large batches of product when “on sale,” and store it up against the days when the product is not “on sale.”

Some short-term promotions are so predictable that buyers actually delay purchases at regular prices knowing that, if they wait, they can buy at a lower price later.

By the time all of the costs and expenses to the supply chain are added up, it would be difficult—in most cases—to prove that short-term promotional pricing actually adds to the bottom line at all. In fact, studies by some firms specializing in creating and managing pricing mechanisms have shown that consistent pricing at a marginally lower level actually produces more sales and profits than higher prices accompanied by short-term promotions.

Consider a brand like Wal-Mart. This is a firm that has master-crafted its supply chain and built its reputation on consistently lower prices. By doing so, it has—over the last several decades—supplanted previously known giants in the retail industry such as Sears, Penney’s, Kmart and more. Yet, Wal-Mart is not known for “sales” (i.e., short-term promotions). It is known for its consistently lower prices.

Volume Discounts linked to shipment batches

Let me say, off the bat, that there is nothing wrong with volume discounts, per se. The problem is linking volume discounts to transfer batches. In order to realize volume discounts without causing supply chain hoarding and needless volatility, the volume discounts should be separated from the shipment batch.

For example, your customer might get a volume discount if they agree to buy 100,000 units next year, but you might agree to transfer them to them in relatively equal weekly or monthly shipments. This evens out production (on the supply end), warehousing (on the receiving end), and doesn’t make it look like someone sold 50,000 units in March and another 50,000 units in September with little or no activity between.

Period-End Promotions and Salesperson Incentives linked to Period-End Dates

These two are frequently related. Salespeople with the need to reach certain goals for end-of-quarter or end-of-year sales, in order to boost their commissions, begin a big push. This push is usually accompanied by some authority to also offer special discounts.

All up and down the supply chain, prices are being discounted, volatility is being recklessly increased, and, all the while, production lines and warehouses are increasing their operating expenses to meet the boost in demand. Overtime and extra staffing costs are eating up the lion’s share of the profits that might otherwise have been generated if volatility had been reduced, rather than increased, by rational policies.

 

Of course, there are other wrong-headed policies that needlessly lead to higher volatility in our supply chains, but these are a few that come to mind. These are things well within the span of control of executives and managers where corrective action is easy and at little or no cost. It just take rethinking the way we do business and not being afraid to gore some existing “sacred cows.”

Understanding the “chain” in supply chain management

After 30 years of growth and development, I am not at all certain that I would rename “supply chain management” to anything else. What I might try to do is to get people to recognize the real implications of the name it already has.

Let's look at that key middle word in the name: "chain."

Very few organization "manage" the supply chain as a "chain."

A great many managers and executives are content to manage only their "link" in the chain. If things don't go well, they may try to substitute one connected link for another (e.g., change vendors or find new customers, for example). But they do not recognize or manage the chain as a chain. They still manage pretty much within the four walls of their own "link" (i.e., company).

The important thing to understand about a "chain" is the interdependence of the links and that the strength of the entire chain is governed entirely by the strength of the weakest link in the chain.

The interdependence of a chain should drive organizations inexorably toward supply chain collaboration and, even further, toward a genuine mutuality. In many cases, the fastest, best and most secure way for organizations to improve their own profitability is to work together with other supply chain participants to strengthen the weakest link in the chain—not seeking to replace that link. That means that all the participants in the supply chain—or at least the strategic links—must be (or become) open to collaboration and even invite new ideas from other participants in the chain.

Collaboration and end-to-end data sharing can help end the damaging effects of "the bullwhip," help firms in the supply chain break their frequently misguided addiction to large batch sizes, and help redefine purchasing and pricing metrics that can lead to more frequent replenishment while holding both truly variable costs and operating expenses low for all the participants.

High-level meetings should be sought between executives and managers for all the critical players in the supply chain. The healthiest supply chains are those where all the participants are making satisfactory profits and a few strong players in the supply chain are not using their leverage to increase profits through policies that weaken other important links in the chain.

How can you tell when your "supply chain management" team is beginning to act like they are part of a "chain" and not just content to manage their own "link"? Look for the following signs:

1. Metrics and actions taken for improvement reach outside "our link" and efforts are made to optimize the "whole chain" by identifying and seeking to strengthen the weakest link.
2. Management up and down the supply chain have learned to not ignore the industry's larger ecosystem. They monitor the ecosystem for signs of impending change, manage proactively, and share information freely.
3. Supply chain managers recognize that there will always be a "weakest link" and, while seeking to strengthen the present "weakest link," learn to pace the flow of products by the "drum" of the present "weakest link." They also recognize that any loss of productivity at the present "weakest link" is productivity lost to the whole supply chain. (As a corollary, supply chain managers should recognize that time, energy and money spent strengthening links other than the present "weakest link" will not improve the performance of the "chain.")
4. Managers and executives involved in the supply chain have ceased using metrics stuck in "cost-world" thinking and have seen that it is synchronizing product flow and increasing throughput that lead to ongoing improvement and higher profits.
5. Supply chain managers have recognized that profits depend upon meeting customers' needs and demands, and that understanding these needs and demands is essential from product design forward through all the processes and links in the supply chain.
6. Collaboration across the supply chain begins with product design so that maximum external variety (end-products) can be achieved with minimal internal variety (raw materials, components and subassemblies).
7. Supply chain collaboration is leading to strategic flexibility in both products and the processes of maintaining supply chain flows.
8. Wherever possible, all along the supply chain, the flow of product is buffered with capacity rather than inventory. (Supply chain partners may make strategic capital investments in other parts of the supply chain to build needed capacities as part of the collaboration.)
9. Managers and executives involved in the supply chain have made it a priority to develop strategic alliances and partnerships all along the supply chain in order to recognize and strengthen the present "weakest link."
10. All across the supply chain, metrics focus on increasing throughput (not cutting costs).
11. Forecasts are still used for planning, but "pull" is used to drive all execution in the supply chain.
12. The focus is now on synchronizing the flow of product across the supply chain, not on balancing supply chain capacities.

ONE ADDITIONAL NOTE:

On the contrary side, some "big dogs" (or "big dog" wannabees) in the supply chain think they are managing "the chain," but they treat it more like a "leash." They yank their smaller suppliers around until their suppliers are either driven out of business or simply won't do business with the "big dogs" at all any more.

This kind of attitude is bad for business and bad for the economy in general. The best suppliers are profitable suppliers. If any organization is destroying the supply chain's profitability one link at a time, it is destroying its supply chain by weakening one link after another. These weak links will not have reserve capacities to respond to changes in demand or make up for supply chain losses when "Murphy" strikes.

P.S. - I was going to write on the other words (i.e., "supply" and "management"), but this is probably enough for now. Thanks.

Increased supply chain confidence through simplicity

Traditional approaches to inventory management and replenishment divide inventory stocks into two portions:

1. Working stock – the inventories designed to cover daily demand
   
2. Safety stock – the inventory quantities designed to cover variation in supply or demand or both
   

Years of statistical analytics and software development have been focused on improving the ways in which lead-time, demand and safety stock values are calculated. So much, in fact, that most of the people who use supply chain management, inventory management, or replenishment software frequently do not even understand what the software is doing, how it is doing it, or why it works or does not work.

Some years ago I was consulting a firm and, in the course of the business, reviewing how they went about their inventory management and replenishment. They had software that did inventory management and that included replenishment calculations.

So, we were sitting together and he was describing to me what he was doing on his computer. He said, “Here’s the ordering screen. It shows historical demand here [pointing], and the recommended order quantity here [again, pointing]. And, I don’t know exactly what this number is for [pointing], but if I think the system is suggesting that I buy too much or two little, I can adjust this number until the suggested order quantity lines up with what I think it ought to be.”

Well, of course, what the system was doing was exponential-smoothing of demand and the value he was adjusting was the value of alpha in the formula.

What I refrained from asking him (only by biting my tongue) was, “If you are going to simply adjust the system’s findings to your intuition, why use the system at all?”

The moral is: Systems that are not understood—and most complex systems are not understood—are also not trusted. Especially if they frequently—or even, regularly—produce what are perceived to be unreliable results.

The artificial divide

The artificial subdividing of stock quantities into “working stock” versus “safety stock,” and adding complexities around the factors used to calculate the one value versus the other provides no added value. In fact, the complexity actually leads to less reliability because the users frequently do not know how to set the input parameters effectively. Not to mention the fact that the parameters that are effective today may not—in fact, likely will not—be effective tomorrow or next week.

The fact of the matter is, in most cases, the only awareness of the division between “working stock” and “safety stock” quantities is found in the software itself and those that may be intimately acquainted with the software and its configuration. The people on the warehouse floor typically do not know when they have made an incursion into “safety stock.” They don’t know that the first 41 units they picked for order number 8789089 were from “working stock,” and the last nine units were taken from “safety stock.” And, they should not care.

Even the managers frequently have no visual signal that an incursion has been made into “safety stock.”

Inherent simplicity

Employing Theory of Constraints (ToC) Dynamic Buffer Management (DBM) makes life easier to understand for those responsible for inventory management and replenishment (read: supply chain managers). The buffer size (for any given item in any given stocking location) is a single number. (Let’s say, 1,000 units.)

The formula for setting the initial buffer size is simple and easily understood. Typically that formula is something like this:

Initial Buffer Qty = [Average Daily Demand] * [ToC Replenishment Days] * [2] * [Paranoia Factor]

The only factor that really needs any kind of explanation is the “Paranoia Factor.” This is merely a multiplier selected by intuition and based on senses of the criticality of an item. An item might be critical because it is used in the production of 800 other items; or because the majority of your customers all buy this item; or because one hugely important customer relies upon you for this item; or dozens of other reasons.

Once the initial buffer size has been calculated and set, the buffer is divided (mathematically) into three “zones.” The top third is called the green zone, the middle third is called the yellow zone, and the bottom third is called the red zone.

Going forward, the DBM system simply monitors for conditions at each replenishment cycle and adjusts the buffer size according to rules. The rules are typically:

1. Too Much Green – The item has been found in the green zone on three consecutive replenishment cycles; therefore, reduce the buffer size by one-third.
   
2. Too Much Red – The item has been found in the red zone on two consecutive replenishment cycles; therefore, increase the buffer size by one-third.

It’s that simple. No complex formulas for calculating and managing variability in demand or supply.

On top of that, supply chain managers can have simple visual signals as to the status of their buffers. A simple view of the inventory data (by location) can readily provide red light, yellow light, and green light indicators for the buffer status in any stocking location for any item. No math and easy to equate to action:

• Green light – no action required
• Yellow light – take note, perhaps investigate critical factors like larger-than-normal orders or orders pending for critical customers
• Red light – consider expediting measures, if necessary

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NOTE: There are more options available with DBM, such as identifying and managing SDCs (sudden demand change items—like seasonality), managing Virtual Buffers (between stocking locations, such as warehouse-to-warehouse replenishment, or broader supply chain visibility and collaboration). It is not the intent of this article to exhaust the applicability of DBM.

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RKL eSolutions, LLC is in the process building a cloud-based solution to help you manage your inventory in just such a way—using Dynamic Buffer Management and the Theory of Constraints. Contact me or fill out the contact form here if you would like more information.

The biggest supply chain management mistake over the last 30 years?

I would have to say that the biggest mistake made in SCM over the last 30 (or more) years is the industry’s reliance upon forecasting.

1. Forecasts are virtually always wrong. They may be wrong by a little bit, or they may be wrong by a lot. But they are--for all practical purposes--always wrong. The forecast may be wrong and you have too much inventory--which your firm may call "good' ("Great job! We didn't have an out-of-stock.") or it may call it "bad" ("Hey! Wake up! We are holding too much inventory!"). The forecast may also be wrong and you have too little inventory, which (again) management may call either "good" ("Great job! We sold out of that!") or "bad" ("Hey! Wake up! We lost sales on that because we ran out of stock!").
2. Forecasts only lead to one of two conditions: over-stocks and out-of-stocks.
3. Forecasts offer no assurances of being responsive to the market.

Personally, I believe that if the industry had spent as much time, effort and money on increasing replenishment frequency (reducing lead-time), improving supply chain visibility (end-to-end), making inventory management more agile (providing rapid response to changes in end-user demand) and better understanding and management of sudden demand changes (seasonality and similar events) there'd be a more sales, lower prices, reduced obsolescence and happier supply chain managers everywhere today.

Replenishment frequency

Both Lean and Theory of Constraints management have certainly taught us that replenishment cycles should be as short as possible. One-for-one replenishment is ideal. But short of that, daily is better than weekly; weekly is better than every two weeks; and so forth. When the costs of obsolescence, lost sales, lost customers (due to lost sales), marketing costs required to recover for lost customers, and the many other costs associated with out-of-stocks (on the most popular times) and over-stocks (on the "dogs") if find it hard to believe that most organizations would not perform better with more agile suppliers and logistics even if the so-called "cost of goods" might be marginally higher. Correct valuation of Throughput certainly should teach us that lesson in many, many cases.

End-to-end supply chain visibility

One of the things wrong with today's supply chain is that the manufacturers actually believe that they have made a "sale" when then they sell the product to the distributor. In turn, the distributors believe that they have made a sale when they unload some product on a wholesaler--and so forth on down the supply chain.

The truth is, until the end-user has made a purchase, all the other "sales" have simply put inventory into the supply chain. Inventory that will become obsolete or eat demand for newly-introduced products when liquidated at "discounted" prices. Either way, it's bad for profits in the supply chain.

Imagine how much better it would be if the manufacture (in Malaysia, or wherever) knew within 24 hours precisely how many finished goods were being purchased by end-users every single day. They would know how to pace their production and manage their inventory buffers--as would everyone else in the supply chain!

Inventory management agility

Instead of setting inventory policy once a year, or even several times a year, systems should dynamically adjust for changes in demand (via supply chain visibility) constantly. And, instead of complexity and hard-to-understand formulas, inventory managers should be able to respond to simple visual signals indicating the condition of inventory in their direct control--as well as signals coming from across the supply chain.

Managing sudden demand changes

Supply chain systems should be able to rapidly analyze historical data and identify SDC (sudden demand change) items by simple rules. The systems should then help the supply chain managers understand how to manage build-ups and build-downs for SDC items based on the supply chain production capacities for each item or group of items.

Personally, I think time, energy and money spent in these areas--some of which is now happening--would do a "world" of good (pun intended).

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What do you think?

What’s wrong with EOQ?

Economic Order Quantity (EOQ) EOQ is essentially an accounting formula that determines the point at which the combination of replenishment costs and inventory carrying costs are the least. The goal being to minimize both the ongoing costs of carrying inventory and the expenses involved with replenishing inventory.

The basic EOQ formula looks like this:

As you can see, this formula attempts to balance (simultaneously) the following factors related to the business expense linked to holding and replenishing inventory:

1. Usage rates – how many are sold or consumed over a period of time (one year in the basic formula)
2. Cost of replenishment – how much it costs the firm to replenish a single inventory item (SKU) from the point of recognizing the need for replenishment through putting the quantities back on the shelf
3. Carrying costs – all of the costs and expenses related to storing and handling of the inventory quantities held

Let us take a look at how these factors interact in a practical example:

In our example, we have an item that has a cost of $25 per unit, and the average daily demand is five (5) units. For this firm, the cost of replenishment is slightly above average—sitting at $30 per PO line processed for inventoried goods.

Observe what happens to the EOQ on this item as the cost of carrying inventory moves through the range from five percent (5%) to 40 percent.

When inventory carrying costs are very low compared to the cost of replenishment (five percent and $30, respectively), EOQ recommends big orders. In this case, each order would support more than 75 days of average demand.

On the other end of the spectrum, when carrying costs are quite high (40 percent) relative to the cost of replenishment, EOQ suggests smaller inventories (as the result of smaller orders) and the order cycle is slashed to almost one-third its former value (now, just over 26 days).

Underlying assumptions

The assumption being made in the construction of the EOQ formula is that the cost of carrying inventory is linear. That, at a five percent rate, a one dollar decrease in inventory on-hand will lead to a five cent reduction in carrying costs to the firm. Similarly, at a 40 percent carrying cost rate, a one dollar decrease in inventory on-hand will lead to a 40 cent decline in carrying costs.

Unfortunately, the linear relationship assumed by the EOQ formula simply does not exist.

When calculating the cost of carrying inventory, a large number of factors are generally considered:

1. Warehouse space rental (or equivalent)
2. Utilities expense
3. Property tax expense
4. Maintenance expenses on the warehouse and warehouse equipment
5. Inventory write-offs/write-downs
6. Other inventory shrinkage
7. Financing expenses for the warehouse, the equipment, and the inventory itself
8. Insurance expenses on the warehouse and the inventory
9. Labor expenses related to warehouse operations

When inventory is reduced $1,000 in a warehouse with a calculated 25 percent carrying cost, what are the likely real impacts on expenses for carrying inventory?

1. Warehouse space rental (or equivalent) – no change
2. Utilities expense – no change
3. Property tax expense – no change
4. Maintenance expenses -  no change
5. Inventory write-offs/write-downs – possibly some change, but not necessarily at the same “average” rate
6. Other inventory shrinkage – same as above
7. Financing expenses for the warehouse, et al -  no change
   Financing expense on the value of the inventory – some change possible
8. Insurance expenses on the warehouse, et al – no change
   Insurance expenses on inventory – some change
9. Labor expenses – no change

In short, only three of the nine items involved in calculating the cost of carrying inventory would likely change based on $1,000 reduction in inventory. That’s because increases or decreases in the volume and dollar amount of inventory held in a warehouse operations produce relatively large but non-linear changes operating expenses.

As inventory grows, changes like adding a second shift in the warehouse, acquiring additional warehouse space, or adding manpower to handle increased volumes happen incrementally. The EOQ formula has no way to account for these non-linear changes to operating expenses. Therefore, your EOQ decision-making my be entirely off the mark for success and increased profits.

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What’s the answer?

To manage your inventory quantities, I would highly recommend the application of Dynamic Buffer Management. [Click on the link and read the article there.]

To deal with non-linear changes in your enterprise—decisions that may lead to major changes in inventories (increases or decreases)—you need a broader formula that considers your system (your enterprise) as a whole. That would be this one:

Where,

• ROI = Return on Investment
• delta-T = Change in Throughput 
• delta-OE = Change in Operating Expenses
• delta-I = Change in Inventory or demand for other Investment

This formula would cover changes like adding a second shift (change in Operating Expenses) or building a new warehouse (change in Investment).

Think about. Contact me if you need further clarifications.

Finding Common Ground Between CFO and COO–Part 5

[Continuation]

A New Management Paradigm

Toyota’s success—despite Japan’s own significant recession in recent years—is attributable to management paradigms that differ significantly from traditional management practices in the U.S. Some of these are likely recognizable to you in the following table:

	Traditional Paradigm	New Paradigm
Customer requirements	Quantity	Quality – improved experience and results
Quality [1] improvement	Generally costly and tend to reduce productivity	Saves money while increasing throughput
Internal competition (through reward systems)	Produces conflict – a few win, but many lose	System-thinking eliminates internal competition leading to improved performance
Cooperation	Too frequently leads to reduced competitiveness	Brings improvement where many win – maybe, everybody wins
Management	Command and control	Creating a work environment that supports top performance of the system and ongoing improvement
Workers	Seek to satisfy or, at least, appease management	Work together with management to satisfy the customers’ demand for constantly improving quality
Worker evaluations and incentives [2]	Increases internal competition and produces little long-term improvement	Encourages better performance and ongoing improvement
Purchasing	Buy almost entirely based on cost metrics	Buy based on the system’s performance and build relationships with key vendors

Note: This table was adapted from work originally done by W. Edwards Deming.

[1] In the table above, we are employing the term “quality” just as it is described in the text [see Part 4]. However, the term “customer” may be an internal or an external customer. Work to improve quality coming from a vendor is an effort that improves the firm’s experience and results. Similarly, improving quality coming from operation ‘A', which hands off to operation ‘B’, improves the experience and the result of operation ‘B’ as the “customer” of operation ‘A’.

[2] With regard to “evaluations and incentives,” we are referencing the traditional individual performance metrics taken within silos of operations, rather than on the performance of the system as a whole.

All Profit Lies Outside Your Organization

Inside the four walls of your business, everything over which the CFO and COO have direct control can contribute nothing but cost or expense to the bottom-line. Every opportunity for making money lies outside the organization and, therefore, outside the direct control of management and executives.

You can make more money by buying smarter—raw materials, services, et cetera—thus reducing truly variable costs (TVC) and increasing throughput. And you can make more money tomorrow than you are making today by selling smarter to existing customers, new customers or both.

These actions can have other affects, as well. The affects are depicted in the figure below.

 

A side-affect of buying smarter—what you buy, from whom you buy, how (delivery terms) you buy, and when you buy—is reducing inventory. The wonderful side-affects of reducing inventories—when done wisely as a result of system-thinking—are improved profits, higher ROI, and faster cash velocity.

You probably recognize all of these factors as improvements—improvements you would like to see, perhaps.

The new management paradigm unifies the CFO and COO by turning the organization from it navel-gazing introspection to a recognition that the customer is the most important part of the production line. No matter how you fine-tune your company’s internals, if the internals are not focused on the externals as the only source of profits, you are far more likely to create internal friction and heat without actually lighting a fire that will produce increased throughput and profit.

One of the advantages of the accompanying figure is the systemic clarity—the inherent simplicity—it delivers. It helps CFO and COO begin easily translate financial goals (i.e., net profit, ROI, and cash flow) into day-to-day actions (i.e., increasing throughput, reducing inventories and reduce or hold the line on operating expenses while support significant growth in throughput). [Note: For organizations that don’t have to deal with inventories, per se, the “inventory” may be broadened into “investment” or demand for capital investment. For example, if it is possible to reduce, defer or eliminate the need for an investment in new office space, then that would qualify as a “reduction” in the demand for new investment.]

[To be continued…]

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?