6 Mixed Scanning Decision Making Examples
It might be a very complex concept for those who are not familiar with the term mixed scanning decision making. Although it can be a combination of various ideas that comprise this type of decision making process, it can’t be that hard to understand. The secret is to break down the construction of the thought process of mixed scanning in order to get a better understanding of this whole concept.
There are several examples of mixed scanning decision making that can be expressed once you get the basic definition of this term. This is a technique that can be used to understand problems and be able to make decisions based on a particular situation that you need to take care of. In fact, many believe that mixed scanning type of decision making can provide more opportunities to learn about the different components that constitute its infrastructure.
Incremental and Rational-Comprehensive
Mixed scanning can be expressed at best as a method of decision making that involves both incremental decision making and rational-comprehensive decision making. Rational-comprehensive method of mixed scanning decision making requires a huge amount of information so that it can provide an effective decision making approach. It also believes that it is easier to identify and solve problems using this method. On the other hand, incremental decision making believes on the remedial approach towards decision making.
Development of Mixed Scanning Decision Making
Incremental and rational-comprehensive decision making has been found to have flaws, nonetheless. So sociologist Amitai Etzioni developed mixed scanning decision making, incorporating both incremental and fundamental decisions. Partially, mixed scanning can utilize a broad based analysis, but it can also use in-depth analysis in some instances. One intriguing component of mixed scanning is the method that considers the different capacities of individuals towards decision making.
You can directly consider this term as a combination of things, but it is unlikely to have its definition simplified to some extreme extent. So, even if mixed scanning can be established using straightforward understanding, there are some elements that can define the concept that you just want to keep for yourself. Here are common mixed scanning decision making examples that can enlighten you at certain degree.
1. Mixed Scanning as Adaptive Strategy
In contrast to rationalism that offers deeply optimistic approach that a person can learn all that he or she needs to know, mixed scanning is rather an adaptive strategy. So it acknowledges the inability of a person to know in excess of what he or she needs to make a rational decision.
On the other hand, incrementalism avoids making decisions on the basis of partial knowledge as it is profoundly cautious. However, mixed scanning is able to make the best possible way of using this partial knowledge than simply going without any knowledge at all.
2. Use of Mixed Scanning by Medical Professionals
The medical field is known to have the oldest application of mixed scanning decision making. This is certain because it is how physicians make decisions. In contrast to incremental decision making, doctors know what they need to achieve and what part of the organism they need to focus.
They are also in contrast to what rationalists believe, because physicians will not commit everything based on preliminary diagnosis. They also do not have the luxury of time to wait for anything they conceive about the personal history or scientific finding before performing or initiating treatment.
This is because physicians simply look at the overall health of the patient and begin to assess the complaints that he or she has. Thus, they try an initial treatment, but they alternatively use another method if the tentative solution will fail.
3. Effective Managers Often Use this Approach
For successful managers, this method of decision making often works for them. Since business data are not unequivocal in nature, it is very important to be cautious in making decisions. Thus, being humble yet efficient in making decisions are similar for executives and doctors in this sense.
4. Focused Trial and Error
In order to adapt to partial knowledge effectively, the most widely used method is focused trial and error. This method will have to employ two different parts, namely where to begin searching for effective intervention and modify or adjust the intervention by checking results at intervals.
Basically, this method is different from outright trial and error, assuming no knowledge of the situation at all. In focused trial and error approach, though, searches needs to be fine-tuned. This can happen only when uncertainty is low and knowledge is high.
5. Reversible Decisions
When partial information is only available to make decisions, one method to avoid overcommitting is via reversible decisions. For instance, when there was an energy crisis in the 1970s, a simple response was to raise the thermostat during the summer or turn it down during the winter. It could have been so efficient if the system may have been fully reversible. On the other hand, if energy sources need to be reversed, it will be an expensive and complex crisis reaction and reverse will be costly.
6. Less Detailed and Demanding
Judgment for mixed scanning involves two sets, namely broad and fundamental choices and incremental decisions. The former deals with the basic policy and direction of the organization, while the latter will enable the preparation for new and basic judgments.
Mixed scanning is basically much less demanding and detailed compared to rationalized decision making. However, it is more comprehensive and broader compared to incrementalism. Nevertheless, it is unlikely to be restricted to familiar alternatives.
These are just some basic understanding towards mixed scanning. It can be possible to explore more examples of the concept in a much deeper understanding. For this reason, it will require more knowledge about the basic incremental and rational-comprehensive approach towards decision making. Thus, it will make it a lot easier to appreciate the basics that outline the mixed scanning decision making examples. Without doing so, the term mixed scanning should be thought of as a very complex concept that is difficult to adapt.