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Quantitative Methods for Decision-Making

Buy custom Quantitative Methods for Decision-Making essay

Buy custom Quantitative Methods for Decision-Making essay

Introduction

Managers utilize various quantitative methods to enhance the decision-making process and make better decisions related to business growth. However, most of these decisions are only applicable in the rational business models. The limitation to their application is not limited to the structural models. Having the perfect knowledge of the organization, competitors, employees and the industry at large is very beneficial to the decision making process. Quantitative business analysis plays a key role in helping managers implement key decisions within an organization using quantitative data thereby eliminating the use of guesswork in decision-making.

Decision Trees

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A decision tree is a picturesque illustration that allows a manager to preempt potential challenges likely to face the organization and draft possible alternatives. Decision trees are extremely useful when it comes to business processes such as purchases, hiring and retrenchment, investment and pricing. Generally, this quantitative method is supposed to enhance decision making particularly in instances where smaller departmental decisions culminate to bigger organizational ones. Such decisions have a higher risk potential regarding their implementation. A decision tree is supposed to map out alternative strategies that are adopted under a condition of risk.

The term decision tree comes from the graphical representation of the quantitative decision making tool. The appearance of a decision tree starts from the bottom detailing the problem area and progresses to offer various alternatives that the organization can implement based on possible future conditions. Hammond et al. (1997) are of the view that decision trees enable managers to analyze organizational decisions taking into consideration future decisions and the way they will affect the organization. Decision trees always have potential payoffs associated with each decision taken and the possible alternatives.

Payback Analysis

Payback analysis is commo in decisions regarding purchases. A practical example of using this quantitative method is the case of a car rental company manager who has to purchase cars used for rental services. The best option is to go for cheaper car models thus saving on the cost. However, there are clients who would prefer luxurious car models meaning that such clients are locked out of the car rental business. In order to arrive at an appropriate decision regarding which cars to buy, the manager must take into account all the factors that will affect decision making. Such factors include: expected life of the car, insurance cost, car rental demand and the emerging trends in the car rental industry. When analyzed from a demand point of view, luxurious cars are a better choice going by their demand and the expected life of the car. On the other hand, the cost-based strategy would favor cheaper cars that would cost less in terms of purchase, insurability and maintenance. As stated by Virine and Trumper (2007), the main assumption under the payback analysis dictates that the benefits from a decision outweigh the cost.

Simulations

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Simulations from a broad perspective replicate the existing systems in an attempt to better understand how something or an operation works. Simulations can be referred to as simplified methods that imitate an existing system. This method works by altering or manipulating the various models in a system trying to find out the overall effect caused by the change. Simulations are very effective when used as decision-making models. Managers often refer to this method when analyzing or developing alternative strategies that are used to tackle certain organizational decisions. Most importantly, simulations remove the aspect of guessing in decision making.

Theory of Constraints

The theory of constraints is a technique that assists managers in decision making by identifying factors that hamper the growth of a business. When applied in decision making, the theory of constraints systematically identifies factors that inhibit growth and suggests possible solutions to overcome the growth iinhibitors. Any business environment is highly unpredictable. The theory of constraints therefore identifies the constraint within a system and examines possible future ones that may affect growth. Managers use this quantitative method to map out future business growth by taking into consideration the current business performance and pairing it with factors such as competition, cost effect, production expenditure and the emerging trends within the specific business sector. The theory of constraints has over the years assisted managers to preempt potential factors that have a direct or an indirect impact on the business.

Budget Variance Analysis

Robert and Reilly (2004) state that budget variance analysis takes into account the cost implication of any decisions made by the organization. This analysis further provides the time-frame in which certain objectives are achieved within the business environment. The budget variance analysis assists a manager to get accurate projections that are compared with the actual business performance. This helps a manager identify business risk and growth opportunities based on the figures from the budget variance analysis. The key components analyzed in budget variance analysis include: operating costs, expenses, debts series, receivables and overheads. In general, all the departmental budgets should have frequent analysis in order to achieve maximum revenues for the business.

For any organization, entrepreneurial skills of either the owner of the business or the employees are the best business assets. Such skills dictate that all organizational decisions ought to be conducted in a manner supported by scientific and arithmetical figures. This further helps pre-empt any uncertainty in the highly unpredictable business environment and thus places quantitative-decision making as a key stage in business process. The more advanced quantitative decision-making techniques have further simplified the management process leading to the optimal use of resources, better interpretation of the business environment and accurate projections relating to the future changes within the business environment.

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