The sales manager of Jeta Plastics Moulding (JPM), Frank
Morris, was concerned about

the bidding results of the last two years. JPM is a small
manufacturer of high pressure

injection-molded plastic parts, supplied to the automotive
industry. They are qualified

as a Tier 2 supplier and their customers are Tier 1
companies such as Lear, Magna,

Levine Controls and Faurecia. Tier 1 companies supply
directly to car assembly plants on

a just in time basis.

Over the past few years, JPM’s success in winning large
contracts had steadily declined,

forcing JPM to pursue greater numbers of small contracts and
moving up the supply

chain and becoming a Tier 3 supplier. This has become a
serious problem; the

company’s total business has dropped to such an extent that
it is currently operating at

only 70% of capacity.

Frank realized that there was something wrong with their
method of preparing bids. In

the past two years, Frank found that the rate of success in
winning bids increased as the

total size of the contract decreased; particularly he
observed that they were really

successful in the Tier 3 segment.

In their attempt to increase the total amount of sales for
JPM, they had submitted

almost double the number of bids compared to previous years,
but the number of bids

submitted for Tier 2 contracts remained the same although
the success rate declined

sharply. This resulted in two people from the accounting
department spending most of

their time preparing the cost data for the bids.

JPM used a standard full-cost accounting system, and bids
were prepared with the

objective of earning a 20% markup on total costs. Standard
hourly operating rates were

developed using regression analysis of monthly prior-period
costs for each machine and

process. These costs, labeled as conversion costs, included
all labour, job setup, and

mold development costs as well as fixed and variable
processing overhead costs. The job

setup and mold development costs were fairly constant from
job to job. The coefficients

from the regression analysis were used as the rates for
variable-cost items and the

intercept values were divided by full capacity processing
hours to determine the rates

for fixed-cost items.

Frank has the idea that there is something wrong with JPM’s
current bidding system.

Accordingly, he decided to test alternative approaches in
preparing their next bid for a

fairly small contract for instrument panel components requested
by Levine Controls Inc.

He started with the usual bidding method based on the cost
estimate prepared by the

accounting department (Exhibit 2-1), and made a mental note
that he would normally

have submitted a bid of $145,000. He then made his best estimates
of the probabilities

of winning the contract at various bids (Exhibit 2-2) based
on the past experience of the

last two years and the profile of the customer.

REQUIRED:

Using the case approach discussed in class, determine what
Frank Morris should do.

EXHIBIT 2-1

Cost Estimates for Contract to Supply 10,000 Automobile
Instrument Panel Components

to Levine Controls Inc

Standard Standard
Cost

Hours Rate/Hour per
Unit

Material $4.463

Conversion costs:

Labour: Variable 300 $21.97 $0.659

Fixed 300 25.17
$0.755

$1.414

Processing on machine: Variable 500 $51.50 $2.575

Fixed 500 35.50
$1.775

$4.350

Finishing: Variable 100 23.50 $0.235

Fixed 100 28.50
$0.285

$0.520

Total manufacturing costs before rejects $10.747

Rejects (1) 1.075

Total manufacturing costs $11.822

Selling and administration (2) 0.337

Total cost $12.159

Markup (20%) 2.432

Standard price per unit $14.591

Standard bid for 10,000 units (3) $145,910

Notes:

1) A 10% standard allowance was added for defective units
which would be rejected

during final inspection. This reflected a normal spoilage
rate.

2) Selling and administration costs were all treated as
fixed.

3) This contract would utilize 2% of JPM’s total capacity.

EXHIBIT 2-2

Probability Estimates Regarding the Potential Contract to
Supply 10,000 Automobile

Instrument Panel Components to Levine Controls Inc.

Probability of Bid Amount Winning Contract

$135,000 95%

145,000 85

150,000 80

155,000 75

160,000 65

As of today, Frank wants to carefully evaluate JPM’s method
of preparing bids and find

an explanation of how the rate of success in winning bids
was affected by this bidding

method. However, he also is facing an immediate challenge
that has to be solved:

considering only quantitative factors, what amount should
JPM bid for the instrument

panel component contract? What qualitative factors should be
considered before

deciding on the amount of the bid?

When thinking in the long term, there are other issues that
should be considered. A

couple of months ago top management has decided to replace
the existing production

system with a new, completely automated computerized
production system. This is

aimed at keeping up with technological advances in the
industry and hoping to improve

the company’s success in winning large contracts in the Tier
2 segment. This new system

will expand the total production capacity of JPM and
eliminate all labour except

maintenance and some handling. Fixed costs, however, will be
significantly increased.

What would be the implications in the bidding process of JPM
once the new

computerized production system is installed and what actions
need to be taken before

moving to the new system.

Proposed marking key:

Proper format and presentation: 5%

Introduction: 15%

Problem identification: pricing setting tied to full costs
10%

Analysis:

Current system: 15%

Determining the price of the bid: 20%

Assessing the changes in the future system: 10%

Alternatives: 10%

Recommendation: 5%

Regarding the recommended solution (2% each):

Solves the problem?

Uses the analysis?

Is derived from alternatives?

Is based on theory?

Makes business sense?

Case: Jeta Plastic Moulding (ADMS3510 Winter 2008)

Student:

Case Approach (5%)

format, spelling, grammar, sentence structure

Introduction (15%)

All relevant facts describing the company and its situation

Problem and Issue identification (10%)

. short term bid to Levine Controls (4%)

. long term issue related with bidding process (6%)

Analysis (45%)

Description of the limitations off the current system (15%)

a. The fixed processing rate is based on full capacity

b. 70% of capacity: under-allocation of fixed costs.

c. The costing of rejects is inappropriate: only variable
costs

d. “Standards” based on prior period costs are
inappropriate.

e. Learning curve: unit variable costs for large jobs <
for small jobs.

d. Inappropriate to use a single markup rate for all sizes
of jobs

e. Estimate competitors’ cost behaviour patterns and
capacity.

f. Using probabilities and contributions for preparing bids

Determine the price of the bid (20%)

a. price based on contribution margin (10%) or based on full

costs (5%)

b. Proper use of probabilities of outcome to determine the

expected value (10%)

Assess the changes in the future system (10%)

Alternatives (10%)

At least 2 mutually exclusive alternatives in terms of
bidding

process, calculation or price.

Recommendation (5%)

Clearly state what the company has to do immediately

Tests of the recommendation (2% each for a total 10%)

Solves the problem?

Uses the analysis?

Is derived from alternatives?

Is based on theory?

Makes business sense?

Subjective evaluation after comparing with other reports

Total