The Littlefield simulation is a business simulation game that allows players to run a simulated manufacturing company and make decisions about production, inventory, and staffing. The game is designed to teach players about the principles of operations management, including concepts such as capacity planning, inventory control, and the trade-offs involved in decision-making.
One of the key features of the Littlefield simulation is its realistic representation of a manufacturing company. Players are able to make decisions about a variety of factors that affect the operation of the company, including the level of production, the amount of inventory, and the number of employees. The game also includes variables such as demand for the product, the cost of raw materials, and the price of the finished product, which can change over time.
One of the key challenges in the Littlefield simulation is balancing the need to meet customer demand with the constraints of the production process. Players must carefully consider their production and inventory levels in order to meet demand without running out of raw materials or incurring excess inventory costs. They must also consider the impact of their decisions on the overall efficiency of the operation, as well as the financial performance of the company.
One way to approach the Littlefield simulation is to focus on maximizing the efficiency of the production process. This might involve investing in new equipment or increasing the number of employees in order to increase the capacity of the operation. It could also involve making changes to the production process itself, such as optimizing the flow of materials through the factory or introducing new techniques to reduce waste.
Another approach to the Littlefield simulation is to focus on managing inventory levels. This might involve setting up an effective system for forecasting demand and adjusting production levels accordingly, or implementing strategies to minimize the amount of raw materials or finished goods held in inventory. It could also involve setting up systems to monitor inventory levels and identify any problems that arise, such as shortages or excesses.
Ultimately, the key to success in the Littlefield simulation is to find a balance between efficiency and inventory management. Players who are able to strike this balance will be able to achieve strong financial performance and meet customer demand, while those who focus too much on one aspect at the expense of the other may struggle to meet their goals. By carefully analyzing the data provided by the simulation and making informed decisions based on that analysis, players can learn valuable lessons about the principles of operations management and apply them to real-world business situations.
Littlefield Report 2
Firstly, the introduction is written. Changing lot size : We changed lot size for 3 times. In our case, we had to decide which process capacity to increase first, as there were budget constraints. Lessons learned Although we are pleased with our final results compared to the rest of the class, we see there is still a room for improvement. A huge spike in demand caused a very large queue at station 3 and caused our revenues to drop significantly. The initial observation made it evident that Board Stuffing machine 1 and Tuning machine 3 processes on the shop floor were touching a hundred per cent utilisation during the peak demand. However, the problem should be concisely define in no more than a paragraph.
Also, manipulating different data and combining with other information available will give a new insight. In addition, we also tracked team rankings from time to time, and noticed that our speed to make money is faster compared with teams above us which are 1, 2, 3, 4. We made many mistakes, but most importantly we have learned from. However, we waited until the lead times become so long that we are making little revenue before we buy machines. The regression report showed that demand level and it became higher compared with initial forecast.
We then set the reorder quantity and reorder point to 0. Since we already had 61 units at the clip of telling, we subtracted that figure from the 552 and came up with a concluding order value of 491. Large batches lead to large inventory; small batches lead to losses in capacity. The buyer power is high if there are too many alternatives available. It is clearly observed in the demand graph, there was an increasing trend of demand till around day 180. So, we conclude that we should have increased the order quantity sooner in the simulation, in order to get a higher growth rate.
Our lead time was up to almost 2 days to complete a job. The queue for station one had over 1000 items waiting and it has been running at 100% utilization for days. Thus our inventory would often increase to a point between our two calculated optimal purchase quantities. This strategies hinges to a great extent on the lab non being in being past twenty-four hours 268, if that were non the instance, we would non urge this program. Initially we set the lot size to 3x20, attempting to take advantage of what we had learned from the goal about reducing the lead-time and WIP. In this simulation we decided to take the message of The Goal and apply it as fast as we could. CONTRACT: We chose to use contract 2 for a little while so that the factory can get rid of the queues with the extra machines we purchased.
But the lack of data about interest over cash in hand and money growth data prevented us from changing it before. STEP 4: SWOT Analysis of the Littlefield Simulation HBR Case Solution: SWOT analysis helps the business to identify its strengths and weaknesses, as well as understanding of opportunity that can be availed and the threat that the company is facing. . We did less messing around with the lot size and priority since these were definitely less important to the overall success of your factory than the number of machines you had. The day it was purchased it was being utilized 100%.
Writing a instance analysis on the Manzana Insurance reading, we recalled the important battles and constriction caused by prioritising one type of policy over the other. . We also changed the priority of station 2 from FIFO to step 4. Our primary concern was to cut down the overall lead clip of the system and prioritising station two or four over the other was traveling to increase the clip at that station doing lower efficiencies. This same approach was used until our lead times dropped enough to consistently fulfill contact 3.
Faculty can choose between two settings: a high-tech factory named Littlefield Technologies or a blood testing service named Littlefield Labs. And then, we identify the bottleneck based on utilization. From this calculation, we got a hint that large inventory can be stored, but the only restriction here would be the cash available. The challenging diagnosis for Littlefield Simulation and the management of information is needed to be provided. Based on this day-to-day ingestion, we found what twenty-four hours the following reorder point would be which was twenty-four hours 222.
Therefore to select the best alternative, there are many factors that is needed to be kept in mind. Moreover, it is also called Internal-External Analysis. In addition, the quantitative data in case, and its relations with other quantitative or qualitative variables should be given more importance. Executive Summary To be successful in the simulation, we tried to develop a strategic plan that will be more profitable. The gap was decreasing enormously; by this comparison, we already knew which team had how many machines, which contract they are using, how much they are growing and when they bought or sold the machine. The four components of VRIO analysis are described below: VALUABLE: the company must have some resources or strategies that can exploit opportunities and defend the company from major threats.
Littlefield Technologies Simulation: Batch Sizes Analysis Essay Example
The goal of our company was to make money, so we needed to upgrade to contract 3 as quickly as possible. Given the average demand and an order lead time of 4 days we were able to calculate an approximate reorder point. We reviewed the use and waiting lines of the other Stationss in the system but were hesitating to do in immediate alterations since we were non wholly certain the effects of rectifying the stock list policy. Once the alternatives have been generated, student should evaluate the options and select the appropriate and viable solution for the company. In addition, it also identifies the weaknesses of the organization that will help to be eliminated and manage the threats that would catch the attention of the management. STEP 10: Evaluation Of Alternatives For Littlefield Simulation Case Solution: If the selected alternative is fulfilling the above criteria, the decision should be taken straightforwardly. We attributed the difference to daily compounding interest butwere unsure.
At station two, we decided non to alter the ordination policy from FIFO. After defining the problems and constraints, analysis of the case study is begin. This proved to be the most beneficial contract as long as we made sure that we had the machines necessary to accommodate the increasing demand through day 150. . We noticed the demand fluctuated a lot. This will help the manager to take the decision and drawing conclusion about the forces that would create a big impact on company and its resources.