You should examine and discuss your reactions and notions about how the material pertinent to a given week relates to your own past/future work/non-work situations.
Each blog entry must have 4 identifiable headings: Summary, Meaningful Ideas, Personal Connecting, Changes. The Summary section is where you highlight the themes found in the materials for the week (2 paragraphs). The Meaningful Ideas section is where you highlight two to three thought provoking ideas that emerged from the materials and why you think they are worthy of being highlighted (2 paragraphs). The Personal Connecting Section is where you discuss how the topics can be applied to your professional and/or personal situations (1 paragraph). Lastly, the Changes section is where you highlight at least two SMART (see: http://hr.wayne.edu/leads/phase1/smart-objectives.php) changes you will make.
The purpose of this assignment is to let you take a little time to reflect, so as to improve your understanding of yourself and understanding of the course materials. Each paragraph should be 100-200 words in length.
What is Reflective Writing?
Your response to experiences, opinions, events or new information
Your response to thoughts and feelings
A way of thinking to explore your learning
An opportunity to gain self-knowledge
A way to achieve clarity and better understanding of what you are learning
A change to develop and reinforce writing skills
A way of making meaning out of what you study
What can I discuss?
Your perceptions of the course and the content.
Experiences, ideas and observations you have had, and how they relate to the course or topic.
What you found confusing, inspiring, difficult, interesting, and why.
Questions you have and conclusions you have drawn.
How you solved a problem, reached a conclusion, found an answer or reached a point of understanding.
Possibilities, speculations, hypotheses or solutions.
Alternative interpretations or different perspectives on what you have read or done in your course.
Comparisons and connections between what you are learning and:
Your prior knowledge and experience;
Your prior assumptions and preconceptions;
What you know from other courses or disciplines.
Tips to help you in your reflective writing process:
Think of an interaction, event or episode you experienced that can be connected to the topic
Describe what happened
What was your role?
What feelings and perceptions surrounded the experience?
How would you explain the situation to someone else?
What might this experience mean in the context of your course?
What other perspectives, theories or concepts could be applied to the situation?
Chapter 9: Managing Costs Across the Supply Chain—The Financial Perspective
Overview
Death, taxes, rock and roll, and the need to reduce costs are all part of a small set of things we know we can always count on. In fact, it is safe to say that unless you work for a university, the government, or certain parts of the health care system, the need to reduce costs will always be relentless and severe. Fortunately, an abundance of techniques are available to help manage costs across the supply chain.
The time has come to view the set of techniques and approaches for managing costs broadly rather than narrowly. This chapter presents a set of techniques you have likely not seen and do not readily recognize.1 In no particular order of importance, this chapter presents some creative ways to manage supply chain costs. While these techniques all rely on cost or financial data for their use, this is one chapter where the presented techniques are not taken from finance.
Learning Curve Cost Models
We have probably all undertaken a task that, as it is performed repetitively, takes progressively less time. What is happening is that learning is taking place. Learning curve models are based on the principle that as individuals become more familiar with a task, the average amount of direct labor required to perform that task or process declines at a predictable rate. The predictable rate is the learning rate or curve. A supplier that experiences learning during production should be in a position to provide a continuous stream of price reductions.
A learning rate is the predictable reduction in direct labor requirements as production doubles from a previous level. A 90 percent learning curve, for example, means that the average direct labor required to produce an item decreases by 10 percent as volume doubles from one level to another. An 80 percent learning curve means the average direct labor to produce an item decreases by 20 percent as production doubles from a previous level. At most firms, learning curve analysis is applied internally. Applying the concept to a supplier’s price, particularly during negotiations, is not practiced nearly as often.
Learning curves apply only to the direct labor portion of production costs, even though the term is often used more broadly (and incorrectly). Learning curves also do not apply to simple items or items where the supplier has extensive experience. Even if an item is new to the buyer, it may not be new to the supplier.
Learning curve analysis works best when a supplier is producing a complex item for the first time. Also, the identification of an incorrect learning rate will skew the estimated improvements, as a supplier moves along the learning curve. And, do not expect to go back to a supplier after six months or a year with a new order and expect to see productivity at the same level as where the previous order left off. Something called the forgetting factor must be considered.
Table 9.1 shows how to estimate a price change due to learning. While material changes may result due to higher volumes, the learning curve analysis only concerns itself directly with changes due to direct labor requirements. However, the reader might notice several other secondary effects that will further reduce a purchase price. First, if a supplier applies overhead as a percent of direct labor (not an uncommon approach when a supplier lacks an activity-based costing system), the overhead allocation will be reduced since the amount of direct labor is reduced. This is legitimate since the product is consuming less labor and machine time. We might also see a reduction in the amount of profit per unit. Again, this is acceptable since the profit margin, which remains constant, is applied against a lower total cost base.
Table 9.1: Learning curve illustrated
A company submits an order to a supplier for 200 units of an item not previously produced by this supplier. Studies by industrial engineers reveal the learning curve for this type of item to be 90 percent. The supplier provides the following per unit information:
Materials
$40
Direct Labor
$60 (3 hours on average per unit @ $20 per hour)
Overhead
$90 (150% of direct labor)
Total costs
$190
Profit
$19 (10% of total costs)
Per Unit Price
$209
Analysis:
Step 1: Estimate the Average Hours per Unit
If the 200 unit order requires an average of 3 hours of direct labor per unit, then a doubling of production to 400 units should require 90 percent (i.e.,.9) of 3 hours, or 2.7 average hours per unit.[*] A doubling to 800 units should require 2.43 average hours per unit (.9 × 2.7 average hours). A further doubling of units to 1,600 units should require 2.19 average hours per unit (.9 × 2.43).
Step 2: Calculate the Direct Labor Hours Required to Make 1,200 Units
Producing 1,600 units should require 2.19 average hours per unit, or 3,504 total hours (1,600 × 2.19 average hours per unit). The first 200 unit order required 600 hours (3 hours on average × 200 units).
The total direct labor hours required for the next order of 1,200 units will be 3,504 (the total hours to produce 1,600 units) – 600 hours (the total hours already consumed to make the first 200 units), or 2,904 direct labor hours.
Step 3: Calculate the Direct Labor Costs for the 1,200 Unit Order
2,904 direct labor hours × $20 per hour direct labor costs means the next order of 1,200 units will consume $58,080 in total direct labor costs. This equals $48.40 in direct labor costs per unit ($58,080/1,200 units).
Step 4: Calculate the Unit Price for the Next Order of 1,200 Units
For the next 1,200 units:
Materials
$40
Direct Labor
$48.40
Overhead
$72.60 (150% of direct labor)
Total costs
$161
Profit
$16.1 (10% of total costs)
New Per Unit Price
$177.10
[*]Recall that the learning curve principle states that average direct labor hours decline by a predictable rate (called the learning curve or rate) as volumes double from one level to another.
In this example the buyer calculates an expected price reduction from $209 to $177.10 per unit. Whether the supplier agrees to this price is open to debate and negotiation. This new figure provides a target to work toward with the supplier. Potential improvements in material costs due to greater volumes could further reduce this price.
If learning occurs and the buyer does not capture the cost benefits, then it stands to reason that the supplier will reap the benefits. A buyer must determine if an item will benefit from learning, and then factor that learning into the supplier’s pricing. Learning curve is a well-established but not well-understood cost methodology among supply chain professionals.
Theoretical Best Pricing
This approach requires detailed cost data from suppliers to identify a theoretical best price (TBP). A TBP is the result of combining the best cost elements across a pool of potential suppliers. As with many cost topics, the easiest way to demonstrate this technique is with an example. In Table 9.2 the TBP given this set of costs and suppliers is $45.48 per unit. How was this arrived at? Notice in Table 9.2 that the lowest cost in each row is highlighted. The highlighted cells are added together to arrive at the theoretical price.
Table 9.2: Theoretical best price
Open table as spreadsheet
Supplier A
Supplier B
Supplier C
Direct Labor
$12.55
$12.78
$13.10
Direct Materials
$10.77
$10.33
$9.25
Overhead
$13.12
$12.78
$15.12
SG&A
$5.90
$5.75
$6.55
Profit
$5.05
$5.95
$5.50
Price
$47.39
$47.59
$49.52
Open table as spreadsheet
Theoretical Best Price = $12.55 + $9.25 + $12.78 + $5.75 + $5.05 = $45.38
Standardized against the best cost:
Supplier A
Supplier B
Supplier C
Direct Labor
1.0
1.02
1.04
Direct Materials
1.16
1.12
1.0
Overhead
1.03
1.0
1.18
SG&A
1.03
1.0
1.14
Profit
1.0
1.18
1.09
Price-to-best-price ratio
1.04
1.05
1.09
The use of this technique serves two purposes. The first is to arrive at a benchmark or target to measure an actual price against. A standardized performance ratio can be created that compares the actual price paid to the TBP. If the price paid for a component, for example, is $14.55 and the TBP is $12, the ratio is 1.21. This means the buyer is paying 21 percent more than the TBP. The second purpose is to identify areas where costs are out of line for each supplier or where possible improvement efforts should be directed.
The second part of Table 9.2 presents a standardized ratio of each supplier’s cost within each row, compared with the best cost for that row. For example, Supplier C’s ratio for direct labor is 1.04 ($13.10/$12.55). This means Supplier C’s direct labor costs are 4% higher than the best cost across the three suppliers. Calculate and interpret all other ratios accordingly. The standardized ratio is an easy way to see what costs are out of line within each row.
Where do we get the data to calculate a TBP? Requests for proposal packages should include a supplier cost form that allows the development of a TBP table. Unfortunately, suppliers sometimes do not know their costs at a detailed enough level to use this approach. And, at times, some suppliers may not be willing to share this kind of information. Nevertheless, this is a technique worth pursuing.
Configured Sourcing Network
A configured sourcing network is not likely a familiar term to the reader. At times, a buyer will develop contracts with distributors that cover dozens, or even hundreds of items. When configuring a supply network a buyer analyzes price quotations from multiple distributors and configures a sourcing network based on the best quotes from each source. While the buyer may use more distributors than planned, the trade-off of developing a supply network that results in a lower total cost will likely outweigh the costs of maintaining additional suppliers.
Table 9.3 illustrates a configured sourcing network. In this example a buyer has requested quotes for six items from five distributors. (This analysis assumes there are no appreciable differences between the items across suppliers that would create significant price differences.) By analyzing the quotations the buyer can identify the best way (i.e., configuration) regarding how to source these items at the lowest total cost.
Table 9.3: Configured supply network
Open table as spreadsheet
Unit Costs:
Item/Part Number
Supplier A
Supplier B
Supplier C
Supplier D
Supplier E
123661 Gloves
$2.45
$2.76
$3.00
$2.40
$2.30
344296 High-density bulbs
$5.40
$4.95
$5.55
$5.32
$5.60
988373 Safety glasses
$6.59
$6.25
$6.75
$6.44
$6.50
746322 Pens
$1.25
$1.33
$1.43
$1.43
$1.20
854471 Soap
$7.70
$7.05
$7.55
$7.35
$7.60
777432 Paper
$3.12
$3.18
$3.23
$3.40
$3.52
Note: Shaded areas represent the lowest price for each part number/item across each row.
Open table as spreadsheet
Total Dollars Based on Volume:
Annual Volume— Units/Pounds
Supplier A
Supplier B
Supplier C
Supplier D
Supplier E
123661 Gloves 25,000
$61,250
$69,000
$75,000
$60,000
$57,500
344296 Light bulbs 14,000
$75,600
$69,300
$77,700
$74,480
$78,400
988373 Safety glasses 5,000
$32,950
$31,250
$33,750
$32,200
$32,500
746322 Pens 25,000
$31,250
$33,250
$35,750
$35,750
$30,000
854471 Soap 5,000
$38,500
$35,250
$37,750
$36,750
$38,000
777432 Paper 8,000
$24,960
$25,440
$25,840
$27,200
$28,160
Total
$264,510
$263,490
$285,790
$266,380
$264,560
Each cell = (price from the first table) × (volume).
The sum of the shaded areas represents the configured supply network total cost, or $248,260 ($248,260/$263,490) = almost a 6% total price improvement.
An important part of this analysis considers annual volumes, which Table 9.3 illustrates. The importance of accurate demand estimates cannot be overstated. The best annual cost, based on quoted prices is Supplier B at $263,490. Dividing the six items among three suppliers (Suppliers C and D did not qualify for any items) yields an expected configured network cost of $248,260, which is about a 6% price improvement over Supplier B’s quotation. The question now becomes whether it is worth the 6% difference to use three suppliers instead of one.
A major assumption when using this approach is that the prices that each supplier quotes are independent of each other. This means a quoted price for one item is not contingent upon agreeing to purchase another item. This independence is what allows a buyer to selectively pick and choose items and distributors. While this example is for a single buying location, the concept can be extended to identify which distributors should supply different buying locations. A buyer may be dealing with hundreds of items from multiple distributors that are being shipped to different locations.
The benefits from this approach are usually worth the effort. Imagine a company with $100 million in indirect spending with distributors that achieves a 6% total annual savings due to a configured sourcing network. Realizing $6 million in savings (less the increased supplier management costs) is not bad for a few weeks work.
Comparisons to External Indexes
This approach features the use of objective, third-party information to verify that the prices paid are reasonable, given actual changes in a marketplace. One website that supply chain managers should become familiar with is www.bls.gov. This site, maintained by the U.S. Bureau of Labor Statistics, contains a wealth of free data and information. It is worth exploring; it is, after all, your tax dollars at work.
Along the top menu bar of the bls.gov website is a category called Data Tools. Simply click on that icon and scroll down until you see Prices Producer. The user now has the choice to select between industry data and commodity data. According to the Bureau of Labor Statistics, a Producer Price Index (PPI) for an industry is a measure of changes in prices received for the industry’s output sold outside the industry (that is, its net output).
The PPI publishes approximately 535 industry price indexes in combination with over 4,000 specific product line and product category sub-indexes, as well as roughly 500 indexes for groupings of industries. The PPI’s commodity classification structure organizes products and services by similarity or material composition. This system is unique to the PPI and does not match any other standard coding structure. In all, PPI publishes more than 3,700 commodity price indexes for goods and about 800 for services—organized by product, service, and end use.2
Let’s illustrate the use of a PPI table and index. Assume you are a buyer of motor vehicle parts to support your company’s fleet operations. One of your primary parts suppliers has informed you that his prices will likely go up next year by 6%, reflecting increases in labor and material costs. Without even looking at the supplier’s labor and material cost elements, the PPI might provide some insight into whether this increase is realistic.
Table 9.4 presents the PPI for motor vehicle parts. An attractive feature of this tool is that these tables can be easily downloaded for analysis in Excel. A critical point to understand is that the numbers in this table are not prices. They are index numbers for the particular item compared to a base year when the index was established at 100. This particular table was established with an index value of 100 in December of 2003 (Base Date: 200312). The P in the table means the data are preliminary and subject to possible revision.
Table 9.4: Producer price index for motor vehicle parts
Open table as spreadsheet
Series Id: WPU141205
Not Seasonally Adjusted
Group: Transportation equipment
Item: Motor vehicles parts
Base Date: 200312
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2005
101.1
101.2
101.1
101.0
101.2
101.1
101.4
101.5
101.6
101.6
101.9
102.1
2006
102.4
102.7
103.2
103.9
103.9
104.3
104.8
105.1
105.2
104.9
105.1
105.1
2007
105.2
105.0
105.0
105.4
105.6
105.8
105.9
106.0
106.0
105.9
106.0
106.1
2008
106.0
106.0
105.8
106.2
106.5
106.7
107.7
108.1
108.5
108.7
108.7
108.7
2009
108.6
108.3
108.3
108.3
108.4
108.2
107.9
107.7
107.9
108.3
108.2
108.4
2010
108.2
108.3
108.3
109.4
109.3
109.3
108.7
109.5
109.5
109.5
109.5
109.5
2011
109.9
110.3
110.5
110.8
110.9
111.0
111.4
111.9
111.5
111.6
111.5
111.5
2012
111.6
111.6
112.0
112.1
112.1
112.1
112.2
112.2
112.2
112.3
112.8
112.9
2013
112.9
112.7
112.8
112.7
112.6
112.6
112.6
112.7
112.6
112.5
112.5
112.5
2014
112.7
112.6
112.6
112.5
112.6
112.7
112.7
112.6
112.7
112.8
112.8
112.6(P)
2015
112.7(P)
113.0(P)
113.1(P)
P: Preliminary. All indexes are subject to revision four months after original publication.
The first thing the reader should notice is the stability of the data index numbers. In fact, from January 2014 (Index = 112.7) to March 2015 (Index = 113.1) there has been almost no change in overall price index for motor vehicle prices. Since the index was established in December 2003 (Index = 100), the net increase in motor vehicle prices over a 12-year period has been a paltry 13.1% ((113.1 – 100)/100). That is just over a 1% increase per year.
Is the supplier in this case justified in seeking a 6% price increase? That request is clearly not in line with what we are seeing in the price index. Perhaps this supplier is not managing costs well or is possibly trying to slip in a price increase. It is possible the supplier might provide an item that uses raw materials that are experiencing pricing pressures. After all, motor vehicle parts are a broad category. The point here is the supply manager now has objective data to have a heart-toheart talk with the supplier.
Target Pricing
A traditional approach to pricing generally assumes that the starting point in arriving at a price is the combination of costs associated with producing an item. A traditional pricing approach would be to add up the costs associated with producing an item, add on a desired level of profit, and arrive at a total cost figure that then determines the selling price. Unfortunately, this selling price may not be what the market was expecting. When a company quickly offers rebates or discounts on a new product, this is a clue that perhaps the selling price missed the intended market segment.
A different approach is called target pricing (also called target costing). This method involves (1) identifying the price at which a product will be competitive in the marketplace, (2) defining the desired profit to be made on the product, and (3) computing the target cost for the product by subtracting the desired profit from the competitive market price. The target cost is then given to engineers and product designers, who use it as the maximum cost to be incurred for the materials and other resources needed to design and manufacture the product.3 It is their responsibility, usually working with procurement and suppliers, to create the product at or below its target cost. Product developers work closely with marketing to identify a selling price that matches customer expectations. Target pricing employs the following formula:
Traditional Pricing
Target Pricing
Costs
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