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PARADISE PLASTICS

In September of 2006 Sashank Ojha, Division Manager of Paradise Plastics, faced an important

pricing decision on a major new bid opportunity. Sashank knew that pricing too high meant

losing a bid that would employ currently unused capacity. On the other hand, too low pricing

meant losses on the job. In the first two months after Sashank arrived in November of 2004,

the presses were running only about 40% of available machine hours. The division had recently

lost two large contracts and was struggling to find a solid market position. Sashank had

instituted a policy of "contribution margin pricing" to restore profitability. He reasoned that

the fixed costs were already in place and there was heavy excess capacity. Any orders that

generated positive contribution would enhance bottom line profits. In two years, machine

running time was up to almost 50% of available machine hours and the number of different

products manufactured was up from 30 to 50.

THE COMPANY

In addition to the 50 different products PP was selling, it was also typically experimenting in

the factory with a few others at any given time. New product introductions seemed to Sashank

to be a key step in filling up the factory. His best estimate of sales for 2006 was Rs 600,00,000

and he thought PP would again be just above the break-even level on profits. An estimated

income statement for 2006 is shown in Exhibit 1. The division had 20 full-time employees.

Since the factory was not unionized, factory employment fluctuated monthly, based on

demand. Factory employment had ranged between 13 and 31 people in the past 2 1/2 years.

Through strict attention to quality control, and by aggressively promoting its products, PP had

developed a reputation as a reliable supplier of high quality products. In several markets, PP

products were specified by major customers and had become the industry standard for quality.

PP sold its products in both domestic and foreign markets and faced a highly competitive

environment. In the post liberalization competitive era, pricing was a key to success, both

from the point of view of securing contracts, and from the point of view of profitability.

Manufacturing at PP was done in two different modes. Some of the high volume products

were manufactured to stock in long runs to minimize set-up costs and to maintain required

inventory levels. However, for most products, production was in response to a specific order.

THE COSTING ENVIRONMENT

There were five major injection molding presses in use at PP. The machines were of varying

ages and all experienced frequent down-time because of set-ups, raw material problems, regular

repairs, and special repairs related to complex products or new product problems. The factory

typically operated 2 shifts a day, 5 days a week, but volume fluctuations also led sometimes to

one shift or three shift operations. There were four common stages involved in manufacturing a

product: (1) set up of the production machine, (2) the production operation, (3) the assembly

operation, and (4) the testing operation. The set up, assembly, and testing operations were

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labor-intensive. The labor content of the production operation varied widely from product to

product.

In injection molding, molten plastic is forced into a mold where it is "cured." The curing process

requires cooling the mold, usually with water. Once the product has cured, the mold is opened

and the product removed. Some products were produced in stationary molds that required little

manual intervention. Water was passed through these molds during the curing cycle. At the

completion of the curing cycle, the molds were opened and the products were ejected

automatically. For these products, the direct labor content was minimal and the operation was

machine-paced. Other products were produced in removable molds that required manual

intervention. After the molten plastic was injected, these molds were removed from the

molding machine and placed into a vat of water for the curing cycle. At the completion of the

curing cycle, the molds were opened manually and the product removed. For these products,

the direct labor content could be significant since the operation was labor-paced.

The products also varied widely in terms of the assembly and testing time required. On the one

hand, the company manufactured pediatric syringes used in the care of premature infants.

These syringes required extensive attention to quality control and a considerable amount of

manual assembly in a "clean room." On the other hand, the company also manufactured

wheel chocks that required only a cursory inspection and no assembly. The other products

produced by PP varied between these two extremes.

In addition to the product costing complications caused by the wide mix of manufacturing,

assembly, and testing requirements, there were difficulties caused by the machines. Typical of

the industry, the machines used at PP differed widely in terms of their reliability and their

performance when producing different products. A machine problem meant that the machine

would have to be stopped and reset. Because the machine stoppages were highly

unpredictable, incorporating a normal or average machine failure cost into the product cost was

difficult.

On the other hand, the materials, assembly, and testing costs of most products were well

understood since each of these costs could be measured with reasonable accuracy. Materials

costs could be estimated by the weight of the final product since the material in most defective

products could be reused. The assembly and testing operations involved the use of machines

that were both highly reliable and labor-paced. These difficulties and the costing issues were all

on Sashank's mind as he considered the milk crate contract.

THE MILK CRATE CONTRACT

Dairies in Western and Northern India use plastic crates to ship milk cartons from the dairies

to the stores. The annual sales volume of milk crates in the local region (Northern India) was

about 300,000 units. Dairies merged their orders for crates through the Dairy Council in

order to take maximum advantage of possible quantity discounts. Sashank had been asked to

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submit a bid on an initial order of 150,000 units. It was clear in Sashank's mind that a

successful initial bid would give PP a competitive advantage in future orders.

Sashank felt that the successful bid price for these crates would be "Rs 150.00 plus or minus

ten percent." Sashank had been approached by the customer several times and felt that PP's

reputation for quality would ensure that a Rs 150.00 bid would be successful. As a result,

estimating the bid price was not the major issue. The question to be resolved was whether or

not, given its cost structure, 150.00 could cover PP's costs of producing this product.

Discussions with Prashant Shukla and Vaibhav Gade, PP's technical and production

supervisors suggested that the machine cycle time to produce this product would be 50

seconds per unit. The product would be produced in a stationary mold and would be

automatically ejected at the rate of one every 50 seconds. As a result, Sashank calculated

that it would require 20831 hours of machine running time to fill the order. On the basis of his

discussion with Prashant, Sashank expected that the rate of defective crates produced by this

process would be negligible. Following discussions with Vaibhav, Sashank felt that during the

machine cycle time the machine operator would have sufficient time to trim the excess plastic

(flash) off the previous crate that had been made and stamp that crate with the particular dairy's

name.

Based on PP's experience, which was comparable to the industry average, Sashank calculated

that the molding machine would run for only 60% of the time that it was scheduled for

operation. The rest of the time that it was scheduled for operation the machine would be

down for repair, set-up, or maintenance. Consequently, Sashank estimated that it would

require 34722 hours of scheduled machine time to achieve the required 2083 hours of machine

operating time. Since the operator would be required for most of the repair time, all the set-up

time, and all the maintenance time, an operator would have to be scheduled for each hour of

scheduled machine time.

Sashank decided that the production of the milk crates could be undertaken on PP's 750 ton

injection molder. This would require that some of the production scheduled for that machine be

rescheduled to other machines. Because PP currently had excess capacity available on other

machines, Sashank felt that the new order would not require sacrificing any production of any

other products.

The cost of a production mold used to manufacture the milk crates would normally be Rs

4500,000. However, the Dairy Council already owned a suitable mold which they had agreed to

lend to the successful bidder on the contract. Each milk crate weighed 1.6 kilograms.

Polyethylene would be used to produce the milk crate. The cost of polyethylene was Rs 50.35

per kilogram. Sashank felt that plastic trimmed off crates, or plastic in defective crates, could be

1 150000*50/3600

2 2083/0.6

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reprocessed at a minimal cost. Consequently, the cost of raw material per crate was estimated as

Rs 85.53.

Since the machine operators were paid Rs 300.00 per hour (including benefits), the labor cost

per crate was computed as Rs 74. The materials cost to stamp the crates was estimated as

Re 0.50 per side, yielding a total cost of Rs 2 per crate. In addition, a stamping machine

costing Rs 250000 would have to be acquired. The life of this simple stamping machine was

estimated as 10 years, at least.

The crates did not require packaging for shipping and the Dairy Council paid for shipment.

Sashank estimated that the labor costs to load the crates on a truck at the factory door would

be Re 1 per crate. As a result of these calculations, Sashank believed that the direct variable cost

of producing the milk crates would be Rs 95.5 (85.5+7+2+1).

This still left the matter of the overhead associated with producing each milk crate. This issue

had been a source of continuing concern to Sashank on almost every contract he negotiated.

Sashank knew that a common "rule of thumb" in his plant was to apply variable overhead to

products at a rate of Rs 650 for each machine hour (running time). An industry rule of thumb

was to estimate total variable cost as being 1.3 times the direct material and direct labor costs.5

Based on a recent study of PP's costs, the corporate controller estimated that, on average,

selling price must equal at least 2.33 times the sum of direct material and direct

labor costs in order to earn average industry margins of 6% (pre-tax) when operating at the

industry average 90% capacity utilization ratio (scheduled hours). Some

comparative data on industry economics is summarized in Exhibit 2.

Sashank wondered about the accuracy of any of these approaches in general and, in

particular, he wondered if anyone was suitable in this situation. Sashank looked at the ratio

of market price to the sum of direct material and direct labor cost for some of his more

popular products and found that this ratio varied from two to seven. As a result, he wondered

what, if anything, was the implication of the 2.33 factor.

As a guide to understanding the relationship between direct costs (material and labor) and

fixed manufacturing overhead Sashank developed the data that appears in EXHIBIT 3.

The plant accountant advised Sashank that plant fixed manufacturing overhead did not

include direct materials, direct labor, variable overhead or plant supervision (about Rs

2500,000 per year). In addition to manufacturing costs, PP was incurring about Rs 110,

00,000 per year in Selling, General and Administrative (SG &A) expenses.

3 1.6*50.35

4 (50/0.6)*(1/3600)*300

5 A survey of CMIE indicated that the total of variable costs was, on average, about 74% of sales for injection

molders. Since the sum of direct materials and direct labour costs was, on average, 57% of sales, this implied that

total variable costs were, on average, 1.3 times the sum of direct material and direct labour costs (74% = 1.3 x 57%).

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Sashank was not sure how to use Exhibit 3 to help him assign overhead cost to the milk crate

order. The results did seem to indicate that overhead was virtually unrelated to the level of

output in the factory. The results thus did seem to support his "contribution margin

pricing" policy. Sashank was still unsure, however, as to how he should approach this large

incremental order. He observed that: "If I only knew my cost structure better, I would feel

more confident about what I am doing. Right know I feel that I am shooting in the dark."

EXHIBIT 1

Estimated Income Statement (2006 in’ 000s)

Sales (Given) 60000

Direct Material plus Direct Labor (1/2.33 =43% of Sales) 25750

Variable Overhead (15,000 x 650) 9750 (16% of Sales)

Contribution Margin (CM) 24500

Fixed Overhead (10250 + 11000 + 2500) 23750

Profit Before Taxes (Just above breakeven) 750

EXHIBIT 2

Industry Economics

At "Normal" Capacity (90%

Utilization)

At "Fulll" Capacity

Average PP Average PP

Sales 100% 100% 100% 100%

DM + DL 57 43 57 43

Variable Overhead 17 16 17 16

Fixed Overhead 20 35 18 31.5

Profit Before Taxes 6% 6% 8% 9.5

When operating near capacity, PP shows up as the High CM/High Fixed Cost/High Profit

Player. But note that the profit impact (Profit % of Sales) of PP's apparent strategy only shows

up near full capacity. High volume is a key to high profit for PP.

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Exhibit 3

Year Month Direct Labor Hours

(production,

assembly, testing)

Indirect Labor Hours

(set-up, repair, and

maintenance)

Total Machine

Hours (running

time)

(FMOH) Fixed

Manufacturing

Overhead

2004 January 1679 1305 1885 176800

February 2298 863 1775 859800 March 3785 991 1800 673100 April 2646 1287 1643 209700 May 2606 1686 1848 797900 June 2661 1505 1274 382200 July 1670 938 1182 176500 August 1844 1337 1003 353650 September 1839 1343 1351 304700 October 2088 1295 1837 503600 November 2330 1743 1533 208650 December 1434 1416 601 303900 Total 26880 15709 18321 4950500

2005 January 1694 1019 1104 190550

February 1701 933 1128 235600 March 2103 1532 917 566250 April 1756 1192 1211 58050 May 2184 1276 1249 328600 June 1625 890 829 503150 July 1775 1256 1278 381050 August 2007 1728 1095 551400 September 2094 1337 1824 759900 October 2178 1503 1788 234500 November 2992 1868 1471 474200 December 2079 1751 1313 280750 Total 24188 16290 15207 4564000

2006 January 2714 1922 1899 914650

February 2240 1328 1567 786650 March 2275 1663 1723 1999400 April 1737 1157 954 151650 May 1547 1443 654 467900 June 1389 1434 634 1008300 July 2394 1948 1735 815400 August 990 856 1005 713350 Subtotal* 15286 11751 10171 6857300

*Annualized for 2006

(12/8)

23000 17500 15000 10250000

To explore the causal relationships reflected here, Sashank developed the following four linear regressions: Regression R

2 t-Stat

1 (PFMOH) versus Machine Hours (MH): PFMOH = 184050+ (243* MH) 0.07 1.48

2 PFMOH versus Direct Labor Hours (DLH): PFMOH = 216050 + (142.5* DLH) 0.04 1.15

3 PFMOH versus Indirect Labor Hours (ILH): PFMOH = 84200 + (312.5 * ILH) 0.07 1.49

4 PFMOH versus MH and DLH: PFMOH = -3950 + (144.5* MH) + (93.5* DLH) 0.09 0.07 & 0.81