Costs and Contract Terms Essay

Executive unofficialOver the span of 168 simulated old age, team Honeybadgers managed the Littlefield Technologies job shop. The teams objective was to maximize the firms gold position relation back to the rest of the class. Using 50 days of historical data, the team reviewed re-order points, re-order quantity, might, mode pass judgment clock times, and therefore wad terms. The team also weighed the be of new works against dandy for inventory and interest rates, evaluating the return on investment and the impact a new machine had on break times. Using this consideration set, team Honeybadgers bribed one tuning machine, one stuffing machine, and changed the contract terms on ten occasions. Ultimately, the team placed 5th.Actions & AnalysisChanging Contract termA 7 day stretch forth time generated higher(prenominal) revenue enhancement than the other contract terms during the runner 50 days. However, we observed that there was a stretch of 5-8 days when the superstar time was be misfortunate a 1 day lead time during the first 50 days. Evaluating the first 50 days more closely revealed that approximately every 15-20 days, the lead time dropped substantially. nonicing a pattern, and aware that a different contract time could generate more revenue, we decided to micromanage the contracts to optimize revenue. For the duration of trick, we adjust contract according to the tr discontinueing lead time. In times of high demand, when a lead time was more than 18 hours, we opted not to use contract 3 because of the terms of each order (avg. job cost+ edict cost = $608.33) Micromanaging the contracts according to lead times was a temporary solution. This strategy allowed us to optimize revenue when we did not catch the keen to purchase a machine.Purchasing set and Stuffing MachinesWe originally valued to purchase twain(prenominal) a tuning and stuffing machine because both stations had dogged stretches when energy was maxed out. However, withou t sufficient capital, we had to ration purchases. The tuning machine was at capacity more often. At one point the machine was at capacity for 18 days in a row. Purchasing the tuning machine eliminated a bottleneck at that station, which allowed us to produce more DSS products. Although the Tuning machine was prioritized, the bottleneck at the Stuffing machine was nearly as problematic as the Tuning stations. The Stuffing machine was at capacity for 15 days in a row.After purchasing the Stuffing machine, bottleneck shifted again, and we were able to produce more DSS products. We did not purchase a third machine because it was unclear whether the revenue earned would beginning the cost of the machine. The lead time was hovering around a day when we had the capital to make the purchase, and we did not believe the additional machine would improve our lead time enough to justify a purchase. In retrospect both machines should have been purchased preliminary. We will evaluate the benef its of this approach in the Risks and Evaluations section.Choosing Not to scoopWhen we became eligible to take out a loan, we decided to forego the resource because we did not need to borrow. Our cash standing was relatively high throughout the simulation because micromanaging contract terms proved jolly effective. Another obstructor was the grossly high interest rate. A 20% interest rate mitigated any added benefit gained from taking out a loan.Choosing Not to change re-order pointRe-ordering kits was a sizeable fixed cost, but we did not adjust the re-order point / order quantity because demand variability was fairly high. We were aware there was an opportunity cost associated with guardianship in any case overmuch inventory because we could have earned interest revenue from the cash fagged on inventory. However, we kept the order amounts Q high because (1)we want to save ordering cost and (2) we were not concerned with having too much inventory on hand when there was no di rect cost (such as warehousing) associated with holding inventory.Inventory Strategy Final HoursDuring the last 12 simulation days we considered developing a plan to denigrate our inventory at the end of the simulation. However, we were not sure how to calculate this, and the costs associated with running of inventory was too high to risk making a mistake.ResultsThe Honeybadgers team finished the Littlefield simulation in fifth place, posting $1,511,424 in cash. The teams final examination cash position was $104,192 below the first place team, earning 93.5% of their total revenue.Risks and EvaluationsAt the beginning of the simulation, we wanted to maintain a high R and Q because we wanted to avoid high ordering costs. While we considered keeping inventory low to save money for a new machine, we were not sure the meliorate lead time could offset the cost of machines. However, in hindsight we realized that we could have managed R and Q better early in the simulation, so as to mini mize the amount of excess raw inventory. We now know that we could have adjusted R according to the variability of demand, holding that the more demand fluctuates the higher R is and vice versa.We believe that this tactic could have allowed us to pull in enough cash to purchase machines earlier, possibly as early as day 80 or 90. Purchasing a machine earlier could have improved lead times, allowing us to switch to contract 3 earlier so as to generate more revenue. We should have balance between ordering costs during the last 100 days and the cost of having excessive or unnecessary inventory aft(prenominal) last day. In the last day we still had approximately $80k of inventory, which held no value after demand ceased. Managing inventory better would have given more cash on hand.