Satisficing

Revision as of 20:19, 8 April 2023

Developed by Aleksander Moczko

Abstract

This article investigates the satisficing strategy for decision-making processes in a project, programme and portfolio management perspective. The name of this strategy comes from merging two words: satisfy and suffice, with the main purpose being to speed-up the decision-making process by picking the first acceptable solution that meets the objectives ‎^[1]. In this article, both efficiency and accuracy of the satisficing strategy are taken into account to provide a more comprehensive view of the theory. Additionally, two examples of its application are presented. Finally, the limitations of satisficing are described.

Definition

Satisficing is a strategy for a decision-making process. It was first defined by Herbert Simon in 1947 by merging two words together: satisfy and suffice ‎^[2]. At its core, using this strategy leads to making choices that are good enough, rather than the best ones. It is a tangible solution for administrators (project, programs and/or portfolio managers for the context of this article) who can see the complexity of the world, noticing that it is impossible to objectively make the best decision. Humans’ perception allows to consider only a couple of situations and concepts at the same time, meaning that plenty of aspects will be left out anyway. As Herbert states: “One can leave out of account those aspects of reality and that means most aspects that appear irrelevant at a given time.” (p.119, 1947 ^[1] )This marks a great limitation that is imposed within human nature. Phrases such as ‘fair price’ or ‘reasonable profit’ mirror the satisficing theory ^[1]. , as they suggest that a certain amount is good enough, but do not depict the whole scale of potentially maximised outcomes and use an ambiguous reference system. In short, satisficing is a strategy that allows its users to balance the trade-off between finding the optimal solution and the limitations of resources and time.

Satisficing comes in many different forms, depending on the study and business branches where it is used and discussed. For the purpose of this article, a 3-step model with aspirational level is presented based on Artinger interpretation ^[2]. This form ensures high transparency of the satisficing concept and provide structured and easy to follow directions when managing project, programmes and portfolios.

Step 1: Set an aspirational level and deadline to reach it.

Step 2: Search until aspirational level is exceeded or met for the first time.

Step 3: If aspirational level is not reached within the fixed deadline defined in Step 1, decrease the aspirational level and reflect on the past available options or continue the search until the new lowered aspirational level is exceeded or met.

Historical context and development

In order to fully understand the concept of satisficing theory it is critical to acknowledge the context in which it was first developed. Simon Herbert with his theory has opposed the underlying principles of neoclassical economists. Herbert contended that people have bounded rationality and use heuristics to facilitate decision-making, in contrast to neoclassical economics, which presumes people have perfect information and always make rational decisions ^[1]. Herbert also emphasized the need to consider social norms, cultural values, and institutional structures in addition to individual preferences and self-interest when making decisions. In that sense, Herbert’s theory was grounded and applicable in real-world contexts. The most essential expansion of satisficing strategy was done by Kahneman ^[3], who demonstrated how cognitive biases influence decision-making. Through his research he added a new dimension to the theory. Both approaches recognise that decision-makers often relies on heuristics and shortcuts when making decisions, rather than a fully rational and deliberate process ^[4]. Since then, the satisficing theory has developed from economics to other branches, such us management or psychology. Different approaches to satisficing were proposed, from static to dynamic, defined by decision environment ^[2] and other factors dependent on the context and industry.

Balancing efficiency and accuracy: Illusion of validity in Satisficing

One of the key advantages of satisficing is its efficiency, as it allows to make decisions faster, as soon as aspirational level is reached, rather than striving for maximized and the best result. It is efficient approach to decision-making, as it minimizes the time to make the decision and ensures that the outcome is good enough to continue the project. Yet, there is another dimension that it is critical for satisficing strategy to be successful - an accuracy. Aspirational levels set have to be accurate, as well as judgement of qualitative data should remain unbiased to ensure success. Both of these can be challenging to achieve in real world application, since satisficing is considered to be a quick decision-making strategy that pushes things forward. In this context, accuracy can easily be omitted which might lead to unwanted end results.

To account for this hindrance, it is useful to become familiar with theory of Illusion of Validity. Defined by Kahneman and Tversky, as cognitive bias that occurs when people overestimate the accuracy of judgement based on intuition and subjective perception of the world ^[5]. work in progress…

Application of satisficing

Satisficing strategy is not limited to one model that has to be strictly followed. Depending on practitioner needs, different models can be chosen and followed. There are plenty of comprehensive dynamic mathematical models ^[6] that require extensive data inputs and calculations. However, those models usually require distinct expertise to use them, while being excessive for majority of the cases ^[7]. Therefore, focus of this article is limited to descriptive models, that can be easily understood and applied to any project. First, example of using satisficing strategy linked with scheduled performance index is described. Then, examples of potential applications in context of project, programme and portfolio are described.

Satisficing strategy using SPI

To showcase how satisficing strategy can be applied, Schedule Performance Index (SPI) is considered. SPI is an index that measures the schedule performance of given project. If SPI equals 1, project is exactly on schedule. Any value above 1 indicates that project is ahead of the schedule, whereas value dropping below that number means that project is behind the schedule. This index is dynamic and changes throughout the lifetime of the project and therefore creates great value for project managers interested in applying satisficing strategy in decision-making process. In the most simple terms, satisficing strategy can be plotted on two axis chart (See figure below), one reflecting the aspirational level that can be adjusted, based on time measure (in this case SPI index). The core principles for applying satisficing strategy can be determined as setting an aspirational level and trying to reach it. If no solution is found at the aspiration level in the time period t, the aspiration level should be lowered appropriately to ensure responsible allocation of resources.

To apply satisficing strategy using Schedule Performance Index, let’s assume that there is a need to hire a person to become a head for internal anti-doping testing in the project of organising tennis tournament in Spain. Since project is new and not part of the ATP tour yet, the testing is run internally. Lets consider six relevant characteristics for person to work at this position:

a1 - fluency in Spanish

a2 - previous experience in IDTM or other anti-doping agency recognised worldwide

a3 - master degree in biology, chemistry or similar

a4 - minimum 5 years of experience in running anti-doping tests

a5 - minimum 8 years of experience in running anti-doping test

a6 - friendly and approachable personality, as well calm and organised person

Now, depending on the value of SPI the project manager can hire the right candidate, while ensuring that this decision will be taken in a timely manner and with responsible allocation of resources. If project is well ahead of the schedule (eg. SPI = 1.3), a candidate must fulfil all points from a1 to a5, whereas a6 is optional and lacking this factor will not impact decision on hiring the candidate. With the SPI decreasing from 1.3 to 1.2, and then 1.1 the requirement of 8 years of experience is reduced to 5 years of experience. Eventually, if project is on the schedule (SPI = 1), or behind it (SPI < 1) the experience restrictions are dropped and candidate that is fluent in Spanish, has experience in anti-doping agency and got master degree in biology, chemistry or similar will be hired. Note, how those restriction will never be dropped as all of them are critical and regardless of the value of SPI, those conditions must be met.

Outsourcing

- short introduction to outsourcing and its role in projects - 4 main stages: initiation, evaluation, management, outcome - outsourcing considered on individual basis - difference in outsourcing for project vs portfolio

Illusion of validity in the context of satisficing strategy

- article main and core theme is satisficing, this section will expand the concept of satisficing and address its hindrances

Relevance of satisficing in program and portfolio management

- as main sections and examples focus on project managment, this short chapter will provide short description of satisficing for program and portfolio management - emphasis will be placed on main differences compared to project management - core idea is to finish up the article showcasing how universal satisficing strategy can be - table with examples

Limitations

- article focuses on descriptive models only - using purely satisficing strategy for decision-making process is not recommended, it should be considered more as additional dimension to toolbox of project manager

References

1. ↑ ^{1.0 1.1 1.2 1.3} Simon Herbert A and Chester I Barnard. Administrative Behavior : A Study of Decision-Making Processes in Administrative Organization. Macmillan 1947.
2. ↑ ^{2.0 2.1 2.2} Artinger, Florian M. Gigerenzer, Gerd Jacobs, Perke Satisficing: Integrating Two Traditions Journal of Economic Literature 60 2 598-635 2022 10.1257/jel.20201396 [1](https://www.aeaweb.org/articles?id=10.1257/jel.20201396) ****
3. ↑ Daniel Kahneman. Thinking, fast and slow. Farrar, Straus and Giroux. 2011
4. ↑ Gary Klein. A naturalistic decision-making perspective on studying intuitive decision making. Journal of Applied Research in Memory and Cognition, 1(4), 226-227. 2011.
5. ↑ Daniel Kahnemann and Amos Tversky. On the psychology of prediction. 1973.
6. ↑ Wall, Kent D. A Model of Decision Making under Bounded Rationality. Journal of Economic Behavior and Organization. 1993.
7. ↑ Simon, Herbert A. 1955. A Behavioral Model of Rational Choice. Quarterly Journal of Economics 69 (1): 99–118. 1955.