### A. Forecasting & Forecasting Error Techniques

Business forecasting term can be described as a tool or method and techniques which give a prediction about the business functions like developments possible, future profit improvements needed, current face of business sale, expenditures and many other things regarding the company (Tseng et al. 2018). The primary purpose of business forecasting is to evolve better strategies for future of the company based on the current resource information and informed predictions. Forecasting is has many types in it such as time series and projection, qualitative techniques, casual model and many others (He et al. 2017).

In other words, a business forecasting is known as an accurate calculation of all the reasonable probabilities of the business future. These probabilities were calculated based on the analysis done of all the relevant current information which is tested by the logical sound statistical and econometric methods (Kimmel et al. 2018). This information is modified interpreted and also applied in all the terms of an expert’s judgements and his/her social knowledge about the current business trends and market of that particular industry or trade. Its purpose is to provide the management information on the basis of which future planning can be prepared (Weygandt et al. 2020).

###### Error Forecasting Techniques

In the language of statistics, forecasting error is that difference which is seen between the real or actual forecast value and the predicted forecast value of a time series or any other interested phenomenon (Gong et al. 2018). Few of the techniques or methods through which the forecasting errors are detected are as follows-

Mean Absolute Percentage Error- This method is a type of statistical tool to measure the accuracy of a forecasting system. In this technique the accuracy is measure in percentage and it can be calculated an average absolute per cent error for each of the time period subtracted by the actual values and then divided by the same actual value. The formula of this method is

Mean Absolute Deviation- This method is another common method to work out on the forecasting errors and also finding the solutions to that. This technique shows the deviation of the forecasts demand with the actual demand in reality in units (Bennun et al. 2018). This method is also responsible for taking the absolute value of the forecasted errors along with that the averages all those within the granted forecasting time period. The formula of Mean Absolute Deviation is

Cumulative Forecast Error- This error forecasting way says that the sum of all the forecasted errors. As per this method, a huge positive value relatively indicates that the forecasting is probably a consistently lower as compared with the actual demand or may be it is biased low (Levine et al. 2017). This technique gives a large negative value which implies that the forecasting done is consistently higher in value than the actual demand or it can be biased high. The formula of this method is

Mean Percentage Error- The mean percentage error technique from the view of statistics is the value which is computed on the basis of average of all the percentage errors by which the forecasting of a model becomes different from the actual value of the quantity which being forecasted. Here in this method the actual values rather than the absolute values of the forecasting errors are used in the formula because the negative and positive errors can sometimes offset each other (Noothigattu et al. 2018). As a result of this the formula of this method is used as a measure of the bias in the forecasts. The formula of this technique is

##### B. Attitudes towards risks and decision criterion

In recent time, everything seems possible but nothing can be certain. Risks are those elements which are constant in every scenario whether in business operations or in personal life or in any public space. According to Schwartz (2017), nothing can be more certain than prevailing risks in any consequences regarding any everyday economic activities and decisions. Also at the same time, risks in general are a condition for getting success. In economic theories, the focus seems to be on the decisions taken, behaviour and actions on risky circumstances of an ideal person which is termed as – homo oeconomicus (Watts et al. 2018). In this theory the characteristics of a human being simply becomes like-

Fully informed attitude means a strict and limited sense. In this attitude a person is well aware that what situations will occur and which events are possible to happen, which event will occur at which time and also what will be the concrete results of each and every action (De Moura et al. 2020). In case of the extended approach he/she is known about each of the consequences and their results and incidences so there is a surety about the calculation of objectives or a least subjective to associate with a probability of each attitude and its impact.

Infinitely sensitive attitude is that where he/she will be capable of identifying the each and every possible alternative to minimise the risks of uncertain and certain incidents and the person is unaware of how the result will come with what face (Gao et al. 2019). The person’s attitude towards risk could be of any type like he/she might get stressed and fearful or he/she could think and decision what measure can be taken to resolve or minimise the risk effects.

Perfect rationality attitude is that kind of act where the person certainly chooses the most optimal decisive alternative. These choices are consistent as per the hedonic principle which means that the repetition of the same condition will have the same decisions taken and a similar result will be gained (Stenmark et al. 2020).

###### Risks and Uncertainty

Uncertainty is a condition where there is lack of information about the future or it might be possible that no detail is available or whatever available is extremely limited or not trust-worthy. Decisions on such information are highly insecurable and unknown about the future. Future is always free and open and anything can happen. So an action is considered uncertain only when there is more than one result is possible. This result is based on the unknowing subjective or objective probabilities of the occurring of each of the possibilities (Borgonovo et al. 2018). But unlike the uncertainty, risks are characterised with the possible ways to define a set of laws of probability related to the expected result and actions which are economic. Risk can be seen as a quantifiable kind of uncertainty from the view of understandability.

A theory of decision making attitude in risk situations has been prepared and named as Modern Decision Theory. It was name like this because it was developed specially within the economic field which defines mainly three categories of decisions made while at risk (Gong et al. 2018). The three categories are-

• The decisions taken under certainty conditions where in each of the case there is a precise outcome in every situation
• The second is decisions which are taken under risk where it is necessary to identify the al the possible events and set a probability of occurrence. In this category the risk rate is previously determinable for every alternative and event associated with it.
• The last one is decisions made under uncertainty in which the results of each possible alternative and event have frequencies which are not known and cannot be estimated. Here in this category, the risk level is unknown even if it’s probabilistic.
##### C. Decision optimisation

Decision optimisation is such a branch of analytical mathematics of business activities which deals with the maximisation of that outcome which is gathered from a huge number of input variables of the business activities also which exerts their relative influences on the collected output. The decision optimisation analytics is widely used in research operations if it’s applied in engineering and mechanics and economics (Tavana et al. 2018). For instance here an example of an imaginary organisation is taken to understand the utilisation of decision optimisation in business activities. If it’s supposed that AB Trucking company is a logistics and transportation firm which own about 30 trucks in them. These trucks make most of the money for the company to run when they are fully loaded on the roads. The group of entities and variables of AB Trucking are-

Trucks with various types, sizes, age, engine size, towing capacity, fuel capacity, tonnage, hazardous material certification and many more details

Shipment orders with weight, size, type, delivery schedule, invoice amount, parking restrictions, destination and other things

Drivers with their overtime pay grade, salary, route speciality, hazardous material training, license classification and etc. information

Let’s suppose this truck transport company wants to maximise the present utilisation of all their trucks and staff members for getting the highest possible profit margins as compared to their current profit rate. For this target they have to deal with certain things like client schedules, availability of qualified truck drivers, hazardous material requirements, availability of required trucks and trailers cost of delivery and etc. As per Chitsaz & Azarnivand (2017), the company as all the other companies will not like to make their trucks travel half empty, they will also don’t want to pay overtime payment to their drivers, they don’t want the tucks to come back empty and along with all these conditions they also won’t like to miss their delivery schedule time and face any such penalties or dissatisfied customer reactions with them.

This whole process of conditions is somehow complex to tackle. These problems also increases when the incoming shipment orders are not having a fixed pattern or well defined regular routine just like seasonal volumes (Liao et al. 2018). This kind is the problem that every decision optimisation analytical models try to solve at its best possible ways. These types of models suggests the best possible suitable drivers, routing of the trucks and combination of appropriate orders which ensures that the trucks must not be travelling empty, customers’ needs to be fully satisfied and drivers should not overwork. The analysis of decision optimisation model involves a co-relation between the maximisation of profit and the variables of the company (Khair et al. 2017). The outcome of this case if the decision optimisation is applied properly would result in preparing a routing map and shipping schedule should match. These two variables must have to follow plans accordingly during the given time period. This is the scenario where the analytics answers all the questions raised about what should be done. The decision optimisation tool deals in too many things such as from picking up and suggesting the best suitable ways of solution within the target given (Singh et al. 2017).

##### D. Ethical decision making

Ethical decision making is that process where there is an evaluation done among all the possible ethical principles and then a specific option chosen in a consistent manner among all the alternatives. In order to make the business decisions ethical, it is essential to perceive and eliminate the unethical principle options and after that selecting the best possible ethical alternative (Bennun et al. 2018). The process of a good ethical decision making required commitment to do the right thing and take appropriate decision at any cost. Ethical decision making process involves the awareness that there should be consistency in the acts and in daily behaviour there needs to be moral conviction. As Andjelic & Vesic (2017) said another aspect of ethical decision making process is competency which means the capability to gather information required and then evaluate them to develop alternatives and foresee the potential consequences with its risks. A business decision can be said as good only if it follows ethical principles and the results of those principles are effective in nature.

The steps to get an ethical business decision are as follows:

• First step is to collect the facts i.e., the answers to what, who, when, how and why
• Second step is to resolve the ethical questions but one at a time
• Third thing to do is think from the perspective of those people who will get impacted by the decisions such as stakeholder, shareholders, employees and else
• The fourth and last step is to set the rules or codes which will be used to make those ethical business decisions

Among all the activities of a business like operational process, hiring and selection, meeting company targets and others ethics in business may seem like a soft subject and which may wait but if it has been put to backburner then the company can be in trouble (Levine et al. 2017). Much like the other business actions, creating ethics in a business like mission, vision and principles of the company is also essential. Ethical decision making is far than just doing the right thing. Sometimes ethics are tied with legal policies and procedures which if are breached may put the business midst trouble (Noothigattu et al. 2018).

###### Ethical Decision Making Model

An ethical decision making model is a kind of a framework which leaders utilise in their work to bring the set of principles which was decided by the business for the company and also ensure that they must be followed (McNamara et a. 2018).

In the year 2011, a researcher of University of Calgary situated in Calgary of Canada revealed an ethical decision making model after many studies and researches and named it as an Empirical Approach. As stated by Kim & Loewenstein (2020), this research was centered all about the idea and concept of a rational egoism as tool based on which the developing of ethics in the workplaces among the people involved in the decision making and affected people.

The model study is done by formulating a group of 16 CEOs who will come for setting up the ethical principles by combining intuitions and practical reasons for forming the scenario and apply the moral principles of the of the everyday life circumstances where there is a question of ethics is involved. Through this process of research, all the experts settled upon the set of four set of principles namely:

• Rationality
• Justice
• Self-interest
• Honesty

All these above four elements are the normal standards upon which the experts created the decision regarding how people should deal with while downsizing. However it is true that this model is not a standard model for ethical decision making, but this model does reveal that it underlies those business ideas which leaders may use to take ethical decisions. These principles will lead to a set of standards which can be utilised while deciding the ethical decision making processes along with a moral framework (Klein et al. 2017).

#### E. Manager’s note

After all the analysis made in this above assignment, it can be noted that there are few elements which need appropriate focus for achieving the set company target in this rapid expansion of business companies and competition as added substance. In the past few years, there is a growth on the emphasising on the assimilated tools in the business functions which draws and applied various models and techniques in the decision making process in business activities alike marketing, operational, finance, sales and others. Here in this writing few of the aspects are highlighted such as business forecasting and its error detection methods, ethical decision making, risk attitudes and impact of that on the decision making criterion and decision optimisation with the help of some of the models or concepts.

The concepts discussed regarding each of the aspects mentioned here will ultimately help to fill the void which is present in the materials of the current business issues. These various concepts collectively obtain an optimal solution to those issues by understanding and discussing the required techniques and tools according to the decision making surroundings. The process of a good ethical decision making required commitment to do the right thing and take appropriate decision at any cost. The model of ethical decision making says that sometimes ethics are tied with legal policies and procedures. The concept of decision optimisation analytics is widely used in research operations if it’s applied in engineering and mechanics and economics. The decisions taken under certainty conditions where in each of the case there is a precise outcome in every situation. In recent times, nothing can be more certain than prevailing risks in any consequences regarding any everyday economic activities and decisions. Business risks are those elements which are constant in every scenario whether in business operations or in personal life or in any public space. All of these concepts ad models have their own constraints and advantages but still they are useful in different situation in operations of a business organisation and thus can be applied.

##### Conclusion

The conclusion to this assignment says that making business decisions are not that easy as it seems. It involves many specific things which need to be focused to make the decision proper and appropriate without any bias or mistakes. Though there will be a little bit of mistakes remaining in every perfect decision making pan. Ethics is an essential aspect of business decision making which may seem to be less important and quite easy or can be backburned but this thinking is purely wrong since ethics in business decisions are the main part to follow. Ethics is that thing which sets the principles, mission and vision of a company and creates a good image in the market based upon that. Another aspect is decision optimising which as seen above is an analytical tool which finds best ways to resolve the issues in the operational functions of a company. The other two aspects which were also discussed in the above written assignment are business risks and business forecasting. Both of these put great impacts upon the activities of a firm to run properly. Lastly it can be concluded that business decision making needs experts and people who will follow the experts’ advices accordingly to achieve the set target.

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