In the framework of an increasingly competitive and challenging business environment, organizations have the need to generate competitive advantages within the so-called information age and knowledge age in which we are immersed; as they are increasingly concerned about how to manage and get the most out of this capital. Thus, as a result of the development of information and communication technologies, organizations take greater relevance to the collection, analysis and transformation of data into strategic decisions that allow them to design successful action plans.
For this reason, data, information and the generation of knowledge, not only constitute a key factor within the company, but also represents a differentiating element compared to the competition, since today organizations manage an impressive flow of information, which after Its correct analysis supports decision-making and facilitates the discovery of new business opportunities in the market.
Unfortunately, the reality is that for many companies due to the large volume of information that is currently available, far from being useful, it represents a difficult process to deal with in their attempt to put it to proper use. In this context, it is really important for companies to develop their skills and increase their capacities to acquire information, transform it into knowledge, incorporate it into learning, share it quickly and put it into practice.
Evolution of the concept "intelligence in business" (Acevedo, 2015)
In this context, the concept of business or business intelligence , also known as business intelligence or advanced business analytics, refers to the optimal use of data for business decision-making , the purpose of which encompasses the understanding of the operation of various circuits and processes of the company, past, present and future, to form the knowledge base necessary to support the decisions and actions that are implemented. (Teruel, 2014)
Evolution of the Business Intelligence concept
The notions of the concept of intelligence in business were first presented in 1965, with the firm intention of collaborating in business decision-making; for which support systems emerged such as OLAP1 and other data mining tools that provided information and internal support. Thus, business intelligence was based on computer systems used as an information processing tool, rather than on the automation of the decision-making process.
Later, in the decade of the 70's, these models and tools for decision-making were integrated quantitative and qualitative data regarding the preferences and expectations of customers and consumers. For the next decade, the use of databases increased considerably, which gave way to the emergence of the second generation of management systems, developing what is now known as Oracle2 and SQL, 3 or query and access languages to relational databases that allow you to retrieve information of interest from a database and make modifications on them in a simple way; in addition to analyzing large amounts of information.
In the 90's, the Data Warehouse or data warehouses, were used only by large corporations, since they handled large amounts of data. Thus, access to information was allowed for analysis in real time and at the same time it was possible for the information to be modified or enter new data without the need for waiting time. At this time, the contributions were personalized and therefore, decision-making was speeded up, since current information was available in a timely manner.
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1 O L AP: It is the acronym in English for On-Line Analytical Processing.
2 O racle: It is basically a client / server tool for managing databases. It is a product sold worldwide, although its great power and its high price mean that it is only used by large companies and multinationals.
3 SQL (Structured Query Language): It is a standard and interactive programming language for obtaining information from a database and for updating it.
For the year 2000 CRM or customer relationship management is used, which combines computer systems to support the management of customer relationships, sales and marketing, that is, it allows organizational management through decision-making based on oriented to consumer satisfaction.
According to (Acevedo, 2015), a company that turns to its customers is a company that uses information to obtain a competitive advantage and achieve growth and profitability.
Finally, the term business intelligence or business intelligence was born, which refers to the set of products and services that allow users to access and analyze information quickly and easily, propose future scenarios and enable appropriate decision-making at the level operational, tactical and strategic. (Acevedo, 2015)
General
Business intelligence is defined as the ability of an organization to convert daily transactions into models of information, knowledge and strategic and predictive intelligence. (Martín del Campo, 2015) It is a process supported by technology that analyzes information and presents it in such a way that it helps directors, managers and operational personnel to make informed decisions.
Business intelligence comprises a series of tools, applications, and methodologies that allow organizations to collect information from internal and external data sources, prepare it for analysis, and present it in the form of graphs, dashboards, and reports that support decision-making. decisions. Therefore, business intelligence is a process that includes two main activities:
- Collect data from different sources Deliver valuable information
This first activity of collecting data from different sources is known as creating a data warehouse or data warehouse. However, this process only acquires value when the users or the applications intended for this purpose, process the stored data, converting them into information to support decision-making. That is, they deliver valuable information to the organization.
In this sense, the information available is useful to detect business opportunities, reveal market niches or segments to be developed, identify and understand cycles and seasonality, plan and control commercial actions, measure results, adapt strategies to detected market opportunities, reduce the risk percentage of an investment, generate added value for the organization and recognize latent threats in the environment, among many other applications.
Benefits of intelligence in business (Martín del Campo, 2015)
Reduce operating costs: Save time and effort compared to manual reporting and graphing required by the organization.
Reduce information bottlenecks: Business intelligence tools allow end users to generate reports at the required time, thereby reducing or eliminating dependency on a specific unit. That is, the business units begin to be self-sufficient.
P e rmite the feasibility of information: Because otherwise regularly receiving too much information, too little information, irrelevant information, or lag time, wasted time, effort and resources.
Improves decision-making: Every day decisions are made that have a positive or negative impact on the company, affecting profitability. And in this sense, decision-making does not only refer to management levels, but to any employee whose measures affect the entire organization.
L a s decisions are made more quickly: Since decisions can be taken at the right time because it has all the relevant information at any time. In this way, the organization can adapt faster to the threats and opportunities of the environment, since it shortens the time between thought and action.
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In the current era, the value of companies lies in their ability to innovate, manage information and generate knowledge; thus the companies that guarantee their permanence in the market are those that anticipate the events in their environment. However, most organizations still remain in a state of constant vigilance or alert against volatile markets and economic forces, adapting their strategies only reactively.
In recent years, information and communication technologies have increased their relevance due to the strategic role they play in corporations; In the face of the integration and generation of information, however, it is the way in which this information is obtained, manipulated and applied, which can define the success or failure of certain initiatives.
Therefore, in the so-called knowledge society, the use and access to information constitutes a transcendental factor from the economic and intellectual point of view, since having quick and timely information collaborates in the development and sustainability of organizations by facilitating the decision-making process, which is why proper data management is essential, allowing actions to be based on objective and scientific arguments, and not only on intuition, as is generally observed in SMEs.
Nowadays companies generate such a quantity of data that it is not possible to sort, classify and manage them easily, therefore, business intelligence tools are based on the use of complex information systems that use data extracted from three sources: production, information related to the company and its external and internal areas and economic data. (Teruel, 2014)
Business intelligence as a business strategy
As they explain (Ahumada & Perusquia, 2015), all organizations as they interact with their environments, absorb information and convert it into knowledge, since they implement actions based on the experiences, values and norms they possess.
In such circumstances and from the interest in managing knowledge, the concept of business intelligence arises as the set of strategies, actions and tools focused on the administration and creation of knowledge through the analysis of existing data in an organization.
Therefore, business intelligence can be understood as a business strategy that aims to increase the performance and competitiveness of the company, through the intelligent management of all the historical data of its daily transactions or operations, and which are stored in databases in real time. Therefore, it is precisely in knowledge management that the strategies that allow the intelligent company to operate and that give it advantages over its competitors are sustained. (Ahumada & Perusquia, 2015)
Predictive analytics
However, it should be noted that traditional business intelligence applications initially generated reports with historical information, in such a way that an X-ray of the organization's past was obtained, and not an overview of what could happen when certain assumptions were presented.
While the true utility of intelligence in business is to provide the organization with the ability to predict scenarios, therefore, business intelligence tools have evolved from being just databases, to data mining analysis applications and texts through statistical models. (Ruelas, sf)
From this perspective, the tool used to store data loses relevance on the mechanisms that are implemented to produce the results that allow decisions to be made more quickly and effectively, in search of meeting the objectives set by the organization. For as the Greek philosopher Aristotle put it, intelligence consists not only in knowledge, but also in the ability to apply knowledge in practice. (González, 2012)
In today's markets, for organizations to discover hidden patterns in data that the human expert does not easily perceive is the result of applied mathematics using predictive analytics, to literally take advantage of the future.
Business intelligence applied to small and medium companies
As discussed, business intelligence includes the generation of queries and the production of corporate reports from databases, the creation of dashboards, predictive analysis and the use of technology or online analytical processing, to facilitate decision making.
That is why in the first instance it could be considered that this type of tool is exclusively applicable to large corporations; Well, although it is true that its implementation requires a certain budget, SMEs can benefit in the same way. In this regard, small and medium-sized companies by not exploiting management tools such as those that involve business intelligence, for example, tend to act reactively in various problematic situations such as: excess in established budgets, non-compliance with deadlines for payment or delivery, or the destination of resources to areas that do not report important benefits for the organization, among many other cases that are mostly catastrophic for its operations.
In this vein, business intelligence is of utmost importance for SMEs that, although they do not have vast resources, have the possibility of implementing meaningful business decisions in a quicker and relatively easier way than large companies. (Business intelligence for SMEs, 2015)
Thus, the effect that can be observed after the study of historical data so far dispersed, provides the ability to exploit the information for benefit, directly feeding the company's planning systems and processes, and collaborating in the definition of goals, to later make decisions to really sustain themselves.
There are tools aimed at SMEs that contemplate the full power of analysis, reporting and planning of business intelligence solutions, but, thanks to their pre-programmed and non-personalized nature, they can be implemented in a faster way and at a much higher cost. low. (Peace, 2010)
Elements of Business Intelligence (Rosso, 2011)
In short, many companies have great potential that has not been exploited, however, when implementing a business intelligence infrastructure, the data stored in an organization over time represents the possibility of detecting areas of opportunity, of optimizing the allocation of resources, to provide the necessary information to respond to changes in the environment at the right time, and above all, to support effective decisions.
conclusion
Business intelligence seeks to increase organizational efficiency, based on effective decision-making, streamlining the flow of data within the organization. Therefore, business intelligence tools can represent great benefits after implementation; however, business intelligence also depends on adequate organizational communication systems, innovation mechanisms, and interest in knowledge management. Since, on the other hand, if adequate tools are implemented that are nevertheless manipulated by inadequate personnel or untrained collaborators, the company runs the risk of making wrong decisions, based on the misuse and waste of information and technology.
Meanwhile, the diversity of areas involved within the organization, the extensive and complex information crossings, the large number of personnel involved, the duplication of sources, the lack of quality in the information, the diversity of databases, etc., are just some obstacles that arise for this type of projects in the daily life of companies, therefore, in addition to technology and analysis tools, the strategic alignment of the entire organization is required, to modify forms of work that do not produce results and thus obtain sustainable competitive advantages and greater benefits for the organization.
References
- Acevedo, A. (2015). Business intelligence fundamentals. Caracas, Venezuela: Central University of Venezuela, Ahumada, E., & Perusquia, JM (2015). Business intelligence: strategy for developing competitiveness in technology-based companies. Baja California, Mexico: Autonomous University of Baja California González, P. (July 19, 2012). G2 Spain. Business intelligence for SMEs. (2015). Obtained from: http://interwebs.com.mx/soluciones-de-tecnologias-de-informacion/inteligencia-de-negocios/Martín del Campo, F. (October 29, 2015). Strategy and business. Obtained from http://www.estrategiaynegocios.net/opinion/895572-345/inteligencia-de-negociosPaz, J. (December 30, 2010). IMB DeveloperWorks. Retrieved from http://www.ibm.com/developerworks/ssa/local/data/dm-bi-pymes/Rosso, D. (February 18, 2011).Intelligence systems in SMEs. Obtained from: http://www.sistemasinteligentespyme.com/2011/02/18-adecuando-la-inteligencia-de.html Ruelas, M. (sf). SG Buzz: Knowledge to create software. Retrieved from https://sg.com.mx/content/view/418Teruel, S. (June 1, 2014). Captio: Revolutionizing business travel. Obtained from: http://www.captio.net/blog/inteligencia-empresarial-la-transformacion-de-los-datos-en-decisiones-optimasnet / blog / business-intelligence-the-transformation-of-data-into-optimal-decisionsnet / blog / business-intelligence-the-transformation-of-data-into-optimal-decisions
Table of Figures
Figure 1. Evolution of the concept “business intelligence” ……………………………………..4
Figure 2. Elements of business intelligence ………………………………………………………….11
Thanks
Special thanks to the research professor Fernando Aguirre y Hernández, professor of the master's degree in administrative engineering attached to the Orizaba Technological Institute, for the technical contribution to the construction of this article and its direction in the process of learning systemic thinking. Likewise, to the National Council of Science and Technology (Conacyt) dedicated to promoting and stimulating the development of science and technology in Mexico, for financial support for postgraduate studies.
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