Organizations are complex entities because they are a system that aims to meet the same goals, its operation is determined by the interaction and work of different internal and external factors. The organization can be and is studied every day from different perspectives and disciplines such as the sociology or psychology of the company.
In order to carry out the study of an organization in whatever field it is necessary to carry out an exhaustive collection of information in order to have a strong foundation and knowledge of what is happening inside or outside the organization. Depending on the area to be studied, is how we are going to obtain the information, but many times this information is not exact or precise and we discard it, but is this information useful in any way? The answer is, Yes, when the information is inaccurate or confusing, although it becomes a problem to be able to carry out its analysis successfully, it is very useful to analyze and make different conclusions through it that helps to complement the precise information.
The organization needs to better understand its behavior, this has caused researchers to find research methods that adapt to the need for analysis of new approaches through information, whether accurate or inaccurate.
"The reason that natural language is expressed in fuzzy terms is not because human thought is fuzzy, but because the world is fuzzy" John F. Sowa 1940
WHAT IS DIFFUSE LOGIC?
In order to understand the term of fuzzy information, we are going to analyze and explain the concept of fuzzy logic. From there, the quantity and variety of applications of fuzzy logic have been growing, fuzzy logic is an alternative logic and different from classical logic. Fuzzy logic was designed precisely to mimic human behavior.
Fuzzy logic had its beginnings in 1965 and emerged as an important tool for the control of complex industrial systems and processes as well as for home and entertainment electronics, diagnostic systems and other systems. It was proposed by the professor of the University of California Lotfi A Zadeh (Rosas, 2012).
What is the difference between fuzzy logic and conventional logic? Fuzzy logic allows working with information that is not exact to be able to define conventional evaluations, on the contrary traditional logic allows working with information that is already defined and precise.
WHAT CAN WE APPLY DIFFUSE LOGIC FOR?
This can be applied in complex processes, when there is no simple solution model or mathematical model that is precise. It is also useful when you need to use the knowledge of an expert who uses ambiguous concepts that are not very precise.
On the other hand, fuzzy logic is not applicable when the problem can be solved with a linear mathematical model or when it has no solution (López, 2011).
Currently with the development of this tool there are many applications that affect our daily life in some way, since it has been developed in different areas such as:
- Systems control: traffic control, vehicle control, control of washing machines, meters and many more. A control of systems that we see daily is vehicular traffic, traffic lights, one by one, etc. Prediction of earthquakes, optimization of schedules Pattern recognition and computer vision, such as object tracking with a camera, object recognition, focus systems Systems of information, databases and expert systems for example.
We are going to delve into the concept of information applied to this topic, for example , what information do we need to solve fuzzy logic problems? We will say that diffuse information ; As mentioned before, classical logic is based on data and precise information, in this case fuzzy logic is based on knowledge and information that is not precise, we will call this type of information fuzzy information (UDLAP, 2011).
INFORMATION CONCEPT
To have a better clarity of this concept we are going to define the word information.
According to the Royal Spanish Academy, information is the communication or acquisition of knowledge that allows expanding or specifying what is possessed on a given subject (RAE, 2015).
Based on this concept we can say that the information is made up of a group of data already supervised and ordered, which serve to build a message based on a certain phenomenon or entity depending on what you want to know. Information allows solving problems and making decisions, since its use is the basis of knowledge.
DIFFUSE INFORMATION
It is unclear information, imprecise for an ideal understanding. Diffuse information blocks organizations from understanding the meaning of the information.
Information can be fuzzy in situations where interrelated data cannot be measured for analysis. We have as an example the source of internal information, in this the data obtained on the sales record are measured, therefore the information is clear for understanding and analysis but in the primary sources such as a market study there may be different variables for measure since it has the subjective aspects of the product becoming a diffuse information.
The fuzzy information is: The organized set of data that constitutes a message about a certain phenomenon or entity but that has the characteristic of being unclear, exact or concrete.
INFORMATION DIFFUSED IN ORGANIZATIONS
For most organizations, information is a vital element in their daily activities. At present, the correct handling of information allows us to face the future and business competition with much more probability of success.
The process to reach the point where the information available to the company is reliable enough for decision-making is very complex and can be carried out with the help of the following elements:
The diffuse information most of the time blocks the organizations to be able to understand the true value or meaning of the information, as a desired objective of informing what makes the organizations decide to eliminate this information.
Information can be fuzzy in cases where interrelated data cannot be measurable for analysis. For example, by analyzing the internal information of an organization, data on sales, production or inventory can easily be obtained, this data is measured quantitatively, which is why it becomes clear information for understanding and analysis (Cancino, 2012).
On the other hand, the information can become diffuse. In a market study, taking into account people's tastes regarding the taste of a certain product, in this case there may be variables that are difficult to measure, for example subjective aspects of the product, qualifiers, or emotions, assuming that the information is collected by means of surveys, later this information becomes difficult to measure, it becomes diffuse information, which is clear for your good understanding.
ANALYSIS OF DIFFUSE INFORMATION IN ORGANIZATIONS
Here are some tools that can be useful for handling fuzzy information:
One of the most used tools to analyze this type of information is the one already mentioned above "Fuzzy logic" since it is one of the most recent methods for the analysis of fuzzy information, however there is a great variety of tools such as the simple analysis of quantitative data.
CONCLUSION
Information is a fundamental part of companies, if we do not know how to use it we cannot make the correct use of it, there are different types of information in this article we divide them into classic or precise information and diffuse information, and we say diffuse information to those data that are not precise or clear, but they have real importance in decision-making in companies.
This can be used in the resolution of complex processes, when there is no simple solution model or mathematical model that is precise. When you need to use the knowledge of an expert who uses ambiguous concepts that are not very precise, that is fuzzy information.
REFERENCES
- Cancino, VJ (2012). Communication and management of diffuse information.. Obtained from Gestiopolis: http://www.gestiopolis.com/comunicacion-manejo-de-informacion-difusa/López, J. (2011). Obtained from Fuzzy Logic: http://members.tripod.com/jesus_alfonso_lopez/FuzzyIntro.htmlRAE. (2015). Definition of information. Obtained from the Royal Spanish Academy: http://www.rae.es/Rosas, s. L. (2012). Gestiópolis. Obtained from www.gestiopolis.com/el-uso-de-informacion-difusaen-la-toma-de-decisiones-empresarialesUDLAP. (2011). Collection of digital theses.
THESIS TOPIC
DIFFUSE INFORMATION ANALYSIS MODEL APPLIED TO DECISION MAKING IN THE AREA OF SALES AND MKT
OBJECTIVES
- PERFORM THE COLLECTION OF INFORMATION ON THE SALES OF THE COMPANY CLASSIFICATION OF INFORMATION IN CLASSIC AND DIFFUSE ANALYZE THE MISTAKEN INFORMATION, AND ITS POSSIBLE USE FOR THE MOST COMPLEX DECISION MAKING
