Business decision making

Customer Service: We can set a strong customer service through getting help from any published Journal on the sector of customer service. Local Competitive Set: This can be found on articles, Journals, local magazines, research papers indicating the competition in the seafood field. 1 1 1 Presenting survey Methodology Ana sampling Trade uses The survey methodology is presented below: Random sampling The selection of a random sample, each element of the population has an equal chance of been selected.

In general we do not assume that the underlying data follows a normal distribution, but in order to calculate bounds and confidence intervals from single samples it may be useful to assume that the estimates follow a normal distribution. This assumption will be appropriate for large sample sizes but will be problematic for small sample sizes drawn from highly skewed data. Example: At first, we assume that there are 30 companies in 3 markets. Moreover, the first market has 12 companies, second and third has 9 companies respectively. If we take 12 companies to investigate then we need to calculate the percentage of each group.

Calculate market share: First, % of companies that are in the first market are = 40%. So the rest woo markets’ percentage will be 30% for each. Now, our sample companies will be distributed in the 3 markets in the following way: First market: = around 5 companies. So, second and third market will get 4 and 3 companies respectively. Now, we can choose 5 companies from first market, 4 from second market and 3 from third market to conduct our survey methods. Then we need to choose companies based on our requirement. As The Shark Spin survey on reduction in sales, the companies which have increased their sales in this sector must be selected.

Thus we can conduct a survey on the selected companies Black, 2009). 1. 2 Designing a Questionnaire for a given business problem Our next task is to design a questionnaire. Precise information can be found through questionnaire. In order to do so, targeting respondent should be identified. Our focus should be on the causes of decrease in sales and profit forecasting. So, we need to know about the cost structure, profit margin, and quality, market price, sales offer, sale service, complain of customers, probability of dissatisfaction etc.

Through this questionnaire we are going to find out about the causes in decrease of sales in firm. Normally some of the questions are MAC types and some are open ended types. In this case, we should follow MAC and open ended questions as well. So, Macs will be asked very precisely to get the targeted response and open ended types of questions need to be asked to get the views of the customers. As we need primary data for the given problem of the business, the structure of questionnaire may look like below: The Questionnaire for Shark Spin Do you work with any restaurant or retail shop? 1. Yes 2.

NO Do you like seafood? Are you a vegetarian or non-Vega? 1. Vegetarian 2. Non-vegetarian How often do you shop seafood in a week 1. Once 2. Twice 3. Thrice 4. More than 3 times Are there all types of sea foods available in your local shops? 1 . Yes Do you prefer frozen or fresh fish? 2. No Have you shopped at Shark Spin? 3. If yes, when did you shop last time Open ended types of questions: What are the types of foods do you eat in daily basis? What are the types of fish you expect to see in a shop? How do you think the customers can be satisfied more? If you have visited shark spin, what changes do you expect to see? . 1 Relating information for decision making by summarizing data using preventative values The representative values include mean, mode and median. We have conducted a survey on expected sales of Shark Spin. By using formula in Excel we have this histogram: Sales of Shark Spin in previous Year: Mean EYE,OHO Average expected sales In can year Mode Most occurring sales in previous years Median EYE,OHO Average occurring sale. First Quartile ?¬30,000 25% of sales were less or equal to EYE,OHO/year Third Quartile EYE,OHO 75% of sales were less or equal to EYE,OHO/year Result 8. 6 It is negative indicating that distribution is negatively slopped From the above table, we see that the mode and median are same but the mean is different. Mean is the mid value and is considered as the base value. It is the average of all the values. The problem arises when there are extreme values which we call outlier. If there is extreme value in the data set, the mean is affected by the extreme values. As a result, the founded result becomes biased and inappropriate. So, in that situation we prefer to use mode or median.

In case of quantitative data, it is use to find out the mean, mode or median. But in case of qualitative data, it cannot be possible. We can only conclude about the most occurring events from those qualitative data. For Shark Spin, this data will help to know the actual average sale and the most occurring sales in the past years. From this they can analyze the strategy they have taken in those years when the sale was at high point. Although the mean and median differs from each other, we can use this data to predict the actual amount of sale, average sale and the most occurring sale.

This can help in building future strategies, because they can easily follow the same strategy they followed when the sales where boosting upward. 2. Analyzing data using measures of dispersion to inform a given business scenario Distribution of data is given in the following table: Sales expected Targeted sales sector(in thousands/month) Range of sales expected c Other 10 2 TOTAL 26 35 18 17 3 7 15 The overall targeted sale scenario can be depicted from the above table. Sales in the sector are more at less range. Area B is expected to have the maximum sales then all other sector.

Whereas area B and C are expected to makes same amount of sale. From the above data we can predict that the area B might be highly populated place with more income. On the other hand, some of the areas are expected to make very low sales as they might me remote areas or may be high competition area. So Due to higher dispersion there doesn’t exist that much relationship between the variables. From the above given data, we can see the sales distribution of shark spin around its local areas. The above table shows us the extreme and small values.

To improve the sales we should work on balancing the big numbers with small numbers. In the case of sales, the extreme values above the average range doesn’t affect the business in fact it is a positive aspect for the business. But the small numbers shows that Shark Spin are lagging behind in those areas and need to improve their sales by any mean. Some of the sales are below the average range and this should be improved to increase the sale of shark spin. 2. 2 Use of correlation to predict future outcomes with present data.

If any sample of data is divided into hundred parts, each part is called percentile (McCollum, 2010). Percentile is normally expressed in per level form. For example, we may say that 40% of the teachers’ expected salary lies below the 40th percentile. Correlation co-efficient helps to measure how close the data is to being along a trait line (Kop, 2006). It is helpful to measure the spread of data set. It is calculated as dividing the sample standard deviation by the sample mean. It is sometimes expressed in percentage form, sometimes in the decimal form (Kop, 2006).

Business Decision Making

Abstract Contemporary managers are constantly faced with business-related decisions. However, the making of such decisions In the real world Is often unstructured. The term ‘rational decision making’ epitomizes the confusion and widely varying interpretations surrounding this phenomenon. A process-oriented approach may, therefore, seem different from traditional ways of arriving at a choice. Nevertheless, the benefits of adopting such an approach are significant, and its use seems certain to improve managerial decision making in organizations.

The purpose of this essay is o discuss how a managerial decision maker’s rationality may be impacted by perceptual processes. Several perceptual errors such as stereotyping, perceptual defense and halo effect will be examined. In addition, it is also suggested that unethical decisions may be linked to errors in perception. This essay concludes with the discussion on the notion of rationality and the part It plays in linking perceptual processes with decision making. Despite Its detractors, the notion of rationality should subsist as an exemplary model acting as a gulled for managers In making sound decisions.

Influence of rationality and perceptual processes on managerial decision making’ Managerial decision making and rationality are impacted and influenced by perceptual processes. This essay seeks to critically analyses and discuss perceptual processes as pivotal in any decision making endeavourer. Its importance are briefly discussed with particular emphasis placed on ways in which certain differences or biases in perception may have on individuals’ understanding of reality as well as how it impinges on the decision making process within a business environment where there are numerous variables.

Furthermore, this essay looks at what happens when there are perceptual errors In decision making within the business sphere. It also addresses the notion of rationality and Its conflicting attainability with Its application in a modern setting. Perceptual processes are fundamental in understanding the impact perception has on decision making. Managers make decisions every day, hour and minute based on the perceptions they interpret. As with management, the importance of understanding the influence of perceptual errors and improving perceptual accuracy are also addressed in the study of social psychology (Tagging, 1969).

Perception causes people to make wrong choices based on false information. In an organization, incorrect decisions result in a great deal of negative effects. Hence, it is important to delve deeper Into the area of perceptual processes so as to Identify and avoid the causes of such errors and biases In the decision making process. The characteristics of the decision maker lay the basic foundation in understanding characteristics of the perceiver will shape how he or she responds and select a course of action.

Research has shown that personal characteristics, and especially a arson’s self-concept, can affect perception of the social world and of others in it (Green & Skidded, 2001). For example, an individual with high self-esteem might be confident in making decisions and perceive himself as superior compared to one with a low self-esteem. Such characteristics are usually expressed when the perceiver forms impressions of others. Few decisions are made void of preconceived impression or Judgment. As such, this may be the spark that leads to distortion in the perceptual process which might in turn affect decision making.

When it comes to forming Judgments and interpreting information, the decision Akers may respond to irrelevant cues to arrive at a Judgment. Failure to avoid inaccuracies in forming impressions is influenced by a few important factors; the first of which is stereotyping. Stereotyping is a common process which most of us are guilty of committing at least a few times in our lives. The definition that ‘stereotyping’ is to ‘attribute to that person some characteristics which are seen to be shared by all or most of his or her fellow group members’ was coined by Brown (1995).

It can be a powerful tool which influences and impels how a manager makes decisions. An example of stereotyping is the glass ceiling phenomenon in the working world. It is an invisible barrier that prevents women from rising up to the upper echelons of the corporate ladder. In 2008, the COED found that the median earnings of female full- time workers were 17% lower than the earnings of their male counterparts. From this, we might infer that biases and prejudices exists which prevents women from rising to the top, hence the lower pay.

It also shows that Judgment might be clouded when decisions to promote women to higher positions are made regardless of their experience or qualification. Another type of perceptual distortion is perceptual defense. It affects decision making by creating Judgment about things which might not be true. Although it is normal for people to want to defend the way they perceive things, it is hard to change once established. Cash (1946) states that ‘perceptual defense occurs when a person’s value orientations act as a barrier to stimuli that are threatening.

When this happens, the perceiver might not be able to accept the new fact and rejects it by making inaccurate perceptions. A real life example would be the current situation within the Officer Corps of the Singapore Armed Forces. There is a line drawn between officers who are granted scholarships and those who do not have a basic degree. Those who are offered scholarships to study at prestigious universities overseas are termed as ‘scholars’ and those who do not have degrees are known as farmers’.

This distinction is accentuated as ‘scholars’ have accelerated careers promoting them faster to senior ranks in comparison with farmers’. As such, the SAFE has been criticized for “using a promotion system that is based more on education and scholarships than on proven competence”. As the majority of the military rent top brass are ‘scholars’, there might be perceptual defense when it comes to deciding who gets promoted. ‘Farmers’ might be perceived as less competent in promotion to senior ranks more difficult and fulfilling the existence of perceptual defense.

The halo effect is the third major distortion of the perceptual process. It is a form of bias which influences how one perceives an individual or object. It is used to describe a process in which a general impression that is favorable or unfavorable is used to evaluate specific traits (Harrison, 1999). The halo effect can be considered omnipresent in the workplace. One such area is during performance appraisals. When a subordinate is highly proficient in some areas, a laid-back manager might perceive him or her to be proficient in all areas and appraise highly as a result. Another area is Job tasks.

When a person does something well out of his specified Job scope, he or she might also be deemed as an expert in that particular task. An interesting feature’ of the halo effect is that it not only influences decisions within the organization but outside of it as well which in turn affects organizational performance. An example would be Apple Inc. Hereby the positive perception of its features or services extends to the entire corporation. The pod halo effect meant that customers who had a great experience with it would buy a Mac computer simply because it is made by Apple Inc. Thus boosting its sales figures. There is also a clear nexus between perceptual error and ethical decision making. When confronted with making ethical choices, managers might make decisions solely on the basis of their outcome or consequence. In this instance, the majority might stand to gain albeit the decision not being most objective. Decisions might also be dad based on the manager’s own sense of impartiality. The underlying problem is that not everyone will conform to this standard as they might feel the decision is flawed or biased.

T. M. Jones (1991) and Terrine (1986) affirms by stating that perceptual errors may affect an individual’s ethical Judgment by influencing later stages of individual planning and implementation of intentions when responding to ethical dilemmas. From this, it is evident that perceptual errors play a significant role when unethical workplace decisions are made. A classic example would be Enron Corporation’s bankruptcy in 2001. Former CEO Jeffrey Killings objective was profit at all costs.

His perception that profits should be the primary objective meant little regard for ethics and this led to the use of a reward system that only retains those who achieved profit targets (Sims, 2003). Such unrelenting push for profits ultimately led to the company’s downfall as there were charges of financial fraud and corruption within the organization. Perceptual errors are not only linked with decision making; it influences the ethical standards of a decision which may in turn translate into extensive consequences for an organization.

Prescriptive and normative models of decision making assume that managerial decision makers can process information and form Judgment on the basis of rationality. Rationality is defined as a self-conscious process of using explicit reasoned arguments to make and defend knowledge claims (Nonionic and Robert; 1993). Although widely used, there have been criticisms regarding the rational model choice rather than the whole process of decision making. Managers most often do not operate under conditions of perfect information. Landfill (1968) supports this by asserting that decision makers are not faced with concrete, clearly defined robbers.

Rather, they first have to identify and formulate the problems on which they make decisions. Simon (1957) emphasized that a completely rational decision making process demands too much of those making the decision. In a business context, we can consider the rise in the price of goods as an example. When there is an increase in price, it is easy for managers to blame it on inflation. Conversely, there are many causes to inflation such as high demand or low supply. The rational model is therefore hard to achieve as such causes are not clearly defined and are difficult or managers to determine.

The model of bounded rationality also seems to oppose this perfect rationality in decision making. Bounded rationality happens when decision makers simply avoid the effort to be rational and comprehensive at the same time. According to Simon (1979), the rational manager does not always have complete information, and that optimal decisions are not always required. In other words, as managers do not have the time or ability to process complete information about complex decisions, they must select some alternative that promises to meet the objective.

As such, it conflicts tit rationality as it would mean that rational decision making can now be made under risk, uncertainty and imperfect information. Despite such challenges, the notion of rationality does not dissipate once we have considered the perceptual processes of the decision maker. It must be noted that not all critics of the rational model have the aim of invalidating it. In fact, they largely contribute to the further modification and development of the model. It is extremely challenging to try and achieve rationality in every decision. Therefore, rationality should be archetypal of an ideal benchmark for sound decision making.

The value of the ‘rational’ model is that it prescribes procedures for decision making that will lead to the choice of the most efficient means of achieving goals and objectives. It should be used as a core concept to evaluate decision making. It is argued that the use of the term ‘rationality in managerial decision making is extremely useful as it creates a dialogue between philosophical and psychological perspectives of ethics and morality (Baseman, Max, Missies, David; 1998). From this, we can visualize the various theories and model through a simple illustration.