Case: Jeta Plastics Moulding (JPM)

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.

Please refer to the attachment below

Case: Jeta Plastics Moulding (JPM) 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 Hours Rate/Hour Material Cost per Unit $4.463 Conversion costs: Labour: Variable 300 Fixed 300 $21.97 $0.659 25.17 $0.755 $1.414 Processing on machine: Variable Fixed 500 500 $51.50 $2.575 35.50 $1.775 $4.350 Finishing: Variable Fixed 100 23.50 $0.235 100 28.50 $0.285 $0.520 Total manufacturing costs before rejects $10.747 Rejects (1) Total manufacturing costs 1.075 $11.822 Selling and administration (2) Total cost Markup (20%) Standard price per unit Standard bid for 10,000 units (3) 0.337 $12.159 2.432 $14.591 $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