Decision Making Theories

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Theories of decision making

 No organization can survives without making decision. Decision making is a key element of every organization operation.   Companies have to make decision in regard to   which customer to serve, which technology to invest in, which employee to hire, which product to buy and so for.  However, decisions are not made using a standardized procedure. There are several theories which explain how organizations do make decision. These theories are the rational model, the administrative model and the political model of decision making.

  Rational model

  According to the rational model, decision making is a step-by-step process for making choice between alternative (Boundless 2017).  This model is based on the logic of optimal choice. In other words, this model advocates for selection of choice that would maximizes value for the organizations. The model view managers as objectives and totally informed persons who would selected the alternatives that would maximize value for their organization (Chand 2017). For instance, in a case where manager who intends to sell a car on behalf of their organization will definitely chose to sell the car at the highest bidder since the aims here is to maximize value for their organization. As mentioned earlier, this model view decision making as step-by steps process of choosing the best alternative among the available.  These processes includes

  • Setting Goals
  • Identify criteria for making decision
  • Identifying alternatives
  • Performing analysis
  • Making Final decision (Leovanu 2013)

Generally, the rational decision making model assumes that when people are making decision, they make choice that maximize benefits or minimizes cost (Chand 2017).  The model is also based on other assumption which includes;

  • Decision makers have full and accurate information   to inform their choice
  • It easy to find a measuring criterion as well as collected and analyze data to support it
  • The decision makers have cognitive ability, time and resources to evaluate each alternative they have (Boundless 2017)

 Administrative model

 According to this model,   decision makers  are people with varying degree of motivation  and who  faces   three constraints namely  Cognitive limitation , Limited information and  time constraint and as such they  seek shortcut to  find acceptable  choice (Chand 2017).   According to this model, decision maker do not try   optimize value for their organization when making decision but they tries to look for and chose an alternative that is satisfying (Chand 2017).   Back to our example as used earlier, under administrative model a manager disposing off car on their behalf is likely not to sell it to the highest bidder as in the case of Rational decision making model. Instead they are likely to accept the first offer that satisfies their criteria for example the lowest acceptable price. Although the administrative model look like it may lead to poor quality decision especially when compared to rational decision making model, it saves time and effort in the decision making process (Chand 2017).   

It has also been hailed as the appropriate framework to use when the cost of delaying a decision or the process of searching for   alternatives is extremely high in relation to the expected payoff.  Administrative model have also been found to be a sure ways of determining organizations’ operating standards. When a decision is made under this model and the solution implemented and found to be acceptable, then most of the organizations  adopt the procedure used to reach to the solution into their standard operating procedures.  Standards operating procedures makes it  easier for  decision makers to  find a solution to a similar problem whenever it arise without spending much effort and time looking for a way to solves it (Griffin 2007).

Political Model (also incremental Model)

The political model emerged to reject the rational model. According to this model, decision makers do not follow a rational procedure when making decision.  Instead, decisions are made through small analytical incremental processes. In every step, the decision makers use their intuition, experience and knowledge to   find solution to a problem.   According to this theory, the best ways to make a decision is to find short-term solution to an issues or problem and then afterward  continuously review it  based on the prevailing event   and that way  better decision are made (Griffin 2007). The best thing with this approach to decision making is that it is flexible.  As mentioned earlier this approach argues that the best way to make a decision is not to make choice for once and for all.   Situation and circumstance changes frequently and therefore decision maker should make decision in a way that will allow amendment to be made otherwise the decision may fails to serve it purpose.   In additional this approach has been hailed   less risky since Decision   are made and implemented step by step and such   there is little room for making big mistake (Natisha 2017).

 Data driven decision making

  Data driven decision making refer to the decision maker’s ongoing process of collecting and analyzing different types of data from different sources to guide them in decision making (McElharen and Brynjolfsson 2016).  Data driven decision making is an approach to decision making that is totally different from the traditional one. Traditionally, most managers used intuition to make their decision. However, Data driven decision making   is an approach to decision making that emphasis the use of relevant, valid and accurate data to make decision in organizations.   With the growing of digital information, data driven decision making has become even more common.    Digital information  such as those collected  through  organization website, social media etc has so far proved to be  useful in helping organization understand their consumers as well as accurately predict their  behaviours (MAcfee  and Brynjolfsson 2012).  It is therefore logical for decision maker in organizations to use them to make   better   and quality decision.

 Changing organization culture to data driven decision making paradigm  

Many organization stills rely on the intuition of their manager to make decision in their organization.   While   intuition-based decision making have   be useful to some extent, organizations that continue to rely on this decision making approach   are missing a lot.  As pointed out by McElharen and Brynjolfsson  (2016),   organizations are currently operating in an environment characterised by growing   quantity of digital Information generated from websites, social media, and peer-to-peer site among others.  Such digital information has so far proved to be credible, reliable and accurate predictor of consumer behaviours.   They are therefore good input for decision making. So far, they are organizations that have already shifted from traditional approach to data driven decision making process and this transition has paid if recent surveys is anything to go by.  In one of recent study which involved 330 public companies, companies that used data and data analytic to inform the process of decision making   enjoy   improved organization performance. Specifically the study found out that  companies that had embraced  data driven decision making  were  5 percent Productive and 5 percent  profitable that their competitors.  It is therefore important for companies to shift from tradition approaches to data drive decision making approaches if they   want to improve productivity and their organization performance in general.

References 

Boundless (2017). Rational Decision Making." Boundless Management. Available at https://www.boundless.com/management/textbooks/boundless-management-textbook/decision-making-10/rational-and-nonrational-decision-making-76/rational-decision-making-369-8376/ (accessed on 25/4/2017)
 Chand, S. (2017). Models of Decision Making: Rational, Administrative and Retrospective Decision Making Models Available at; http://www.yourarticlelibrary.com/decision-making/models-of-decision-making-rational-administrative-and-retrospective-decision-making-models/25658/ (accessed on 4/26/2017)
Griffin, R. (2007). Fundamentals of Management. Cengage Learning
Leovanu,. A. (2013). Rationalist model in public decision making. Journal of Public Administration, Finance and Law 4, 43-55
McElharen, K., and Brynjolfsson, E. (2016). The Rise of Data-Driven Decision Making Is Real but Uneven. Harvard Business review
MAcfee , A., and Brynjolfsson, E. (2012). Big Data: The Management Revolution. Harvard Business Review
Natisha (2017). Decision-Making Theory: Definition, Nature and Theories. Available at; http://www.politicalsciencenotes.com/articles/decision-making-theory-definition-nature-and-theories/743 (accessed on 26/4/2017)
Olavsrud, T. (2013). Data-Driven Companies Outperform Competitors Financially. available at; http://www.cio.com/article/2387460/business-intelligence/data-driven-companies-outperform-competitors-financially.html (accessed on 26/4/2017)
 
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Essays Stock (2023). Decision Making Theories. Essays Stock. https://essays-stock.com/blog/decision-making-theories

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