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Types and Implementation of Decision Models

Table of Contents

Abstract

Decision models.

Model 1: The Rational Decision Model

Model 2: Bounded Rationality:

Case Study: The Use of Discounted Cash Flow in Perigon.

Conclusions.

References.

Abstract

A decision model is a template or a given model for the process of recognition, organization and management of the logic and rationale by which a business comes to a conclusion and makes decisions based on facts. A decision model lets businesses and leaders take the crucial decisions properly in a systematic process, without undue emphasis or negligence on any part. 

The report aims to discuss and analyze the two decision making models in marketing. For the profound understanding of the effectiveness and implication of the decision-making models, the use of the discounted cash flow model of financing, as used by most businesses over the world.

Decision Models

A decision model is a template or a given model for the process of recognition, organization and management of the logic and rationale by which a business comes to a conclusion and makes decisions based on facts. A decision model lets businesses and leaders take the crucial decisions properly in a systematic process, without undue emphasis or negligence on any part. 

The report aims to discuss and analyses the two decision making models in marketing. For the profound understanding of the effectiveness and implication of the decision-making models, the use of the discounted cash flow model of financing, as used by most businesses over the world.

Model 1: The Rational Decision Model

  • It is a structured, logical process of thinking for a proper decision. If the decision is clear and specific to the problem, the implementation is likely to be efficient as the personnel understand and support the decision (Farhi, and Werning, 2019). This is extremely important for a high-stakes decision, where the input of several persons with the requisite knowledge and expertise may be required.

This model is characterized by:

  • the organized, orderly process followed from the identification of the problem to its solution;

  • the selection of a single perceivably best solution, usually ones with the maximum usefulness;

  • The singularity of the values of the decision maker and the ones reflected in the decision itself

  • The choice is always consistent and logically sound

  • The process of the decision is unbiased and factual, based on objective information.

  • The consequences of the decision are considered.

  • The risks and uncertainty are prepared for.

In this scenario, all persons applying the process should come to the same decision for the same problem, when given the same information (Lilien, and Rangaswamy, 2006). This, however, is not practically demonstrated. Rational decision making is limited by the human factor, as well as the limits of information and time. Decision making in groups and meetings often follows this structure.

Model 2: Bounded Rationality:

The decision maker is bound to their environment and its related constraints. This often means that while, during the decision process, the decision maker identifies the best solution to the problem, but finds it impossible to implement dur to a lack of finance, personnel or other problems. This leads to the choice of a different alternative, which, while not best, can attempt to solve the problem in question and while it does not optimise the situation, it can certainly make it better. (Jones, and McGee, 2018)

Bounded rationality model follows the same principles and steps as the rational models, except that it acknowledges that not all ideas are feasible or even plausible in a given environment, and the people involved have to work around these constraints, such as:

  • Time limits:

Looking for the perfect solution takes time, which the problem may not allow for, or even hinder the perfect solution. Many problems are acerbated and changed with time.

  • The human factor

The people involved, the culture, finances, the decision maker’s understanding of an issue, human bias and other such factors heavily influence the decisions taken and their outcomes. The human limit of understanding complexity leads to a limit in the decision making. (Shannon, McGee, and Jones, 2019)

  • Limited information:

The rational model assumes that all of the information gathered are sufficient and accurate, and that the decision maker has the wisdom and knowledge to understand it. This is not always the case in reality.

Case Study: The Use of Discounted Cash Flow in Perigon

The discounted cash flow analysis method of financing is a method of estimating the valuation of a project, company, or asset using the base concepts of time value of money, that is, the idea that the money earned it the present is worth more than the same money earned in the future. This is widely used by firms and businesses in the field of investment finance, real estate development, corporate financial management and patents.

The Perigon Group of investment analysts in Sydney, in particular, are known for their detailed and accurate analysis with the DCF systems. The model of analysis and prediction needs to be fed with data, especially for certain key fields. In DCF, that involves some significant prediction of future events and market cycles. The agent filling in the details usually has an incomplete theoretical understanding of the phenomena and the reasons for it, but is trained and uses predictions based on past events. This, added with opinions from several other experts, gives them an understanding of the future enough to predict. The gaps in the data are basically filled with comprehension and conclusions derived from the data gathered, as well as imagination. The field of financial prediction is a greatly uncertain field, and the entire process is based on bounded rationality.

Use of Decision Models in DCF Model:

In order to represent the above models, with their rigid structure or theory, this report seeks to represent the business of investment analysis as is most common – the minutely detailed cash flow models as used in DCF. Rationally, the DCF model is extremely complex for a layperson to understand and evaluate. Yet, Perigon finds DCF is useful in several ways:

  • The models used are minute and give importance to detail, which makes possible to keep log of and communicate the different steps, results and procedures in the company. This help the accountability of the personnel and departments.

  • The companies with complex hierarchy and leadership structures need details before a decision on investment is made and implemented. DCF is a standardised model with specific keywords used extensively over the world, so it looks clean and reflects on the company’s reputation.

  • The standardised model also gives the decision process a theoretical structure to build on and transfer to and from departments and other organisations without loss of consistency.

  • The decision maker can deal with complex problems on the basis of the information provided in the DCF model. The decision maker can also break the information into parts to tackle different aspects of the problem, giving the whole process a greater amount of order.

  • The ability of the DCF to be broken into parts also lends it a template for the evaluation of investments, and ultimately helps manage the work better. Even the complex task of investment decisions can be undertaken by this method with relative ease.

  • It also makes task allocation among departments or personnel easy, and the personnel can follow a set of identified common procedure to facilitate understanding.

  • Although many aspects of this model may not be accurate, this model helps establish the basic information required to proceed ideally with a financial decision.

“The lack of accuracy and complexity of the process are drawbacks, which make it a high non-ideal solution and definitely not the best. But, in accordance with the principles of Bounded Reality, these aspects are worked around in favor of the fragmentation, standardization and the condensation of information.” (Pless et al, 2016)

Therefore, it is evidenced that while DCF’s principle of information collection stems from the idea of rational decision model, its implementation is grounded in bounded rationality.

Disadvantages:

The chosen model has its own biases and conditions that stem the accuracy and objectivity of it. This is factored in its understanding, analysis, fragmentation and recombination. The model data is input by human individuals and within the departments of an organisation, so is subject to human error – especially as their beliefs and expectations of the future severely impact the predictions. (Rasmussen, and Thormann, 2019). Decisions or predictions based on widely different and unique premises, as is usual for Perigon, cannot be compared posteriori to appraise a business. The accuracy of the data used in Perigon is attributed to the intensive training and extensive checking of the data before it is communicated. In case of economic, sales or other similar forecasts, the evidence is replaced by conclusions drawn from it.

The aspects of uncertainty and unevenness of information distribution as more people become part of the decision chain, also becomes an important reason for the division and allocation of a power structure (Schumacher and Klönne, 2018). Perigon’s customers often do not understand how accurate or inaccurate each batch of information is, but the company sails on due to its brand name.

Advantages:

The Structured model of the Bounded rationality in Perigon allows for several advantages:

  • Managers receive detailed reports of every personnel involved, even though they are heavily influenced by several factors and volatility. The manager can test and review different scenarios in different conditions the different scenarios their agents are in, and compare them for an analysis for several companies.

  • The abundance and detailed models help unify assumptions and increase the objectivity of the forecast, the scientific method.

  • The model allows for a discipline inherent to it, which is necessary for the greater accuracy of any forecast of the decision.

  • The data can be derived in this scenario for a long time, and even for the entire time that Perigon stays in business. So, the accuracy of the model increases over time, enabling Perigon to better predict and invest in the necessary fields.

  • The high volatility of the markets and the fickle nature of investors is not subject to rationality, or objectivity. Even analysts and the final reports are based on the bounded rationality model of decision making.

Perigon and other, similar firms are able to act consistently as they separate themselves from the day-to-day volatile nature of the markets. This is where the quantitative nature of DCF and the assumption for the constraints in bounded rationality comes into play. With its monitoring and measuring templates, the discipline quintessential to it, and standardization, the DCF system is able to greatly help the entire process of analysis and prediction of investment factors (Chandra, 2017). The DCF follows certain recommendations and normative rules that optimise the entire process of the situation, but ignores the practical aspects of data collection.

Nonetheless, firms running on bounded rationality still prefer the rational model of DCF due to its positive aspects and communicative abilities. In order to remain rational in the field of financial investment in the long term, the rational model of decision making, with its aspects of review and reconsideration of all aspects to maintain accuracy must be lost. The idea of rationality remains ideal. Bounded rationality encompasses the impacts and influences of decision sciences, neuropsychology, cognitive thinking, and philosophy.

The lens model, the linear models use the human judgment and decision making. The bounded rational decision making could be inverted to the fully rational decision by widening the scope of the aspects of choices, to which it could be seen as response. It is assumed that after widening the choice, there are the commentators who suggest the optimal decision making models acceptable in terms of the social scientific persistence. It could be assumed that the limitation of the companies in brain storming could result to the barrier of rational decision making and bound the scopes of decision making. However, it is temporary; it is impacted by the cost imitations. Eventually, the bounded rationality could be affected and the quality of decisions might degrade. 

Conclusions

Both the decision models are used in their own premises. However, the model of bounded rationality is for more common among the different business and fields, simply due to the nature of its premise, and its acceptance of the fallibility of humans and situations beyond our control. The model of Discounted Cash Flow is in itself modeled around the rational model of decisions, but the implementation of it is faced with the ineffability of human nature. Therefore, its usage at Perigon Group for investment prediction, and their quality of investment and job search predictions is severely affected by their training and repeated checking process.

References

Chandra, P., 2017. Investment analysis and portfolio management. McGraw-hill education.

 Farhi, E. and Werning, I., 2019. Monetary policy, bounded rationality, and incomplete markets. American Economic Review, 109(11), pp.3887-3928.

Jones, B.D. and McGee, Z.A., 2018. Agenda setting and bounded rationality. In The Oxford Handbook of Behavioral Political Science.

Lilien, G & Rangaswamy, A 2006, 'Marketing decision support models: the marketing engineering approach', in The handbook of marketing research, SAGE Publications, Inc., Thousand Oaks, CA, pp. 230-254, [Accessed 5 May 2020], doi: 10.4135/9781412973380.

Pless, J., Arent, D.J., Logan, J., Cochran, J. and Zinaman, O., 2016. Quantifying the value of investing in distributed natural gas and renewable electricity systems as complements: Applications of discounted cash flow and real options analysis with stochastic inputs. Energy Policy, 97, pp.378-390.

Rasmussen, H. and Thormann, A., 2019. The Discounted Cash Flow Terminal Value Model As an Investment Strategy. Available at SSRN 3396505.

Schumacher, K.F. and Klönne, H., 2018. Discounted Cash Flow Method. In Contemporary and Emerging Issues on the Law of Damages and Valuation in International Investment Arbitration (pp. 205-230). Brill Nijhoff.

Shannon, B.N., McGee, Z.A. and Jones, B.D., 2019. Bounded Rationality and Cognitive Limits in Political Decision Making. In Oxford Research Encyclopedia of Politics.

Simon, H. (1979). Rational Decision Making in Business Organizations. The American Economic Review, 69(4), 493-513. Retrieved May 5, 2020, from www.jstor.org/stable/1808698

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