Consider some of the examples you have brought up in earlier topics. Describe the key differences between simulation models and the models covered earlier in the course. Outline how the approach to solving this problem would differ in terms of applying and computing/solving the models. Decision tree, Linear optimization, simple regression, multiple regression etc.
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In the business world, we do have what is recognized as the linear optimization. The term linear optimization which is also known as linear programming refers to the process of maximizing or minimizing a linear function with the sole intention of finding the optimum value (maximum or minimum) as far as linear and non-negative constraints are concerned. In other words, this method is a relatively simple technique that is highly used to find realistic solutions for a wide range of optimization problems. In the following paragraphs, we shall talk about workforce scheduling, blending as well as a logistic problem facing my current organization, the things that are being optimized in each and other things revolving around this area.
In the organization of Glanbia Nutritionals, there has been workforce scheduling especially in the departments of Warehouse, Quality, and Production. When it comes to the summer months, they realize that the Production and Warehouse departments work on a full cycle that is, three shifts but in the area to do with Quality department, there is only two shift year round. Efficiency is usually low in the summer months in the Production and Warehouse as the product cannot be checked during the third shift. Over time, the organization’s manager has noticed that the third shift is best used in cleaning the mixers as well as running the big batches of Monster because they took up the entire or whole shift. This has allowed for more products to be mixed and blended. The Glanbia Nutritionals is very much concerned with the classic problem based on blending or mixing its ingredients in order to obtain a satisfying product. The organization has also identified another problem that revolves around the transportation of its nutrition ingredients to the various destinations. This is due to the increased delays in delivery hence a big logistics problem. Working on the workforce scheduling is the means through which efficiency is optimized by dealing properly with negative operational outcomes. Focusing on the blending problem helps the organization to maximize the health benefits of protein supplementation by optimizing the value of its products. Logistics optimization has turned out as a significant component for Glanbia Nutritionals for it improves the business efficiency by minimizing cost.
In the decision tree analysis, there is a schematic representation of several decisions and alongside this are the different chances of occurrence. In other words, a tree-shaped graphical representation of decisions that are connected or related to the investment as well as the chance points that aid in investigating the possible outcome is what is being referred to decision tree analysis. On the other hand, linear optimization techniques are different as we use them to depict complex relationship through the use of linear functions then finally getting the optimum points. With the kind of problems being faced by my organization, linear optimization will work best (Kuester, & Mize, 1973). It will ensure that strategies are put in place that will help the team or employees work efficiently for on-time delivery. With the aid of the linear optimization techniques, the organization would be in the position to see clearly how to blend its ingredient to realize the best quality as it maximizes the profit. This is different from the decision tree analysis that offers several options.
It is very evident that for any organization to prosper and see that the day to day activities are done in the right manner, essential decisions ought to be made. Linear optimization is a great area that we cannot afford to ignore because it helps a lot in making important decisions hence solving a lot of problems encountered.
Strategic decisions are mostly decisions that will affect the company over an extended period. Senior management makes them then they address the same with their team and ensure that they are made aware of the strategy to feel part of the plan. Our company management came up with a decision to increase employee turnover and become the market leader in the retail market for fresh vegetable produce. They did research and came up with a reward strategy that would reward the top performing employees. They also decided to increase our distribution channels. The company could have used different optimization models such as linear programming which would have helped to take into consideration the total cost that would be incurred by the expected promotions and what it would cost to come up with a reward scheme (Plastria, 2001).The long program if used would have reduced the cost by calculating the values of possible outcomes and then calculating the price to come up with the best solution (Pardalos, 2002). Optimization models can give an insight into granular information about the operations of the company, how to actualize the plan within a short span and optimization of their decision
The business world is very dynamic surrounded by many uncertainties. Every forecast/ decision the management makes has to be carefully evaluated to determine its potential benefit or risk to the business. Since forecasts direct future planning, budgeting and business activities (Brooks, 2015), wrong predictions may cripple business to the point of no return.
My previous organization was a dairy plant that depended on its own raw materials to produce its dairy products. According to the management, this was a cheaper option to sourcing from different suppliers. However, they did not account for possible health threats in the livestock industry. The company operated on the basis that they fumigated their animals thoroughly and did not expect disease attacks. As a result, the outbreak of bovine spongiform encephalopathy (mad cow disease) hit hard on the institution. Most of the animals got infected leading to a low supply of raw materials that did not match the normal market demand. The company was forced to outsource raw materials without a proper plan leading to huge expenses that were not compensated in the revenues. More so, several cattle died impacting a loss in assets.
In response, the management decided to construct an annual loss budget to compensate for emergencies as well as monitor potential livestock disease-outbreaks all year round. While the management had appropriate strategies, I would also encourage them to consider outsourcing some raw material to create a diversified supply to stand in during emergencies and enable business continuation