Competitive Intelligence
It takes a simple mind to run a simple machine, but a shrewd mind is needed to run an organization, association, or business. Business intelligence has become a big principle in industries throughout the years. “During the second half of the 20th century, the United States and Canada, Western Europe, as well as Japan and a number of other countries, have evolved from primarily manufacturing-based economies to more information-based societies” (Kara). A business needs to have a mission to be successful. To help accomplish missions for businesses, business intelligence is utilized. To run a productive organization effectively and efficiently, certain things need to be accomplished.
To start the process of applying business intelligence, as many possible sources of information must be gathered. After the information has been collected, it must be sorted into different categories. These categories are either valuable or non-valuable information, otherwise known as intelligence. Since the intelligence is derived by businesses for businesses, it is considered business intelligence. Business intelligence has a direct effect on how well its organization does in the marketplace. This intelligence is used to identify forewarnings of disasters as well as opportunities that may occur. After the intelligence needs have been identified for a business, the information is then collected by an all source fusion. After analyzing the data that has been collected, it can be determined which information can be used, and what can be discarded. The results are then passed to the bosses of an organization, who in turn, make a decision. This completes the four-phased intelligence cycle.
After you establish your business goals, various techniques are used to attain and surpass the organization’s goals. One technique is through competitive intelligence. Competitive intelligence can be considered a subsidiary of business intelligence. The purpose for competitive intelligence is to keep businesses on the cutting edge, abreast of their competitors, ahead in the global markets, and to establish better quality products and services. Competitive intelligence can be defined as “A formalized, yet continuously evolving process by which the management team assesses the evolution of its industry and the capabilities and behavior of ...
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...ded and comprehend it differently, depending on the needs of their businesses. “Never equate paper with competitive intelligence. Unfortunately, many managers think that by spending countless hours on computer-generated slides, charts and graphs, and footnoted reports, they have delivered intelligence. All they have managed to do is to slow down the delivery of critical intelligence” (Fuld).
Due to time constraints, limitations of resources, financial constraints, manpower issues, enormous amounts of data, and the expertise of analysts, competitive intelligence needs to be determined by relevance. Many illegitimate sources are disguised as truths, or facts. These illegitimate sources, along with rumors, are difficult to control and can be used as deception intelligence. There is not a single method of intelligence that can be considered better than another as a general rule. Even though, competitive intelligence can help your business during a recession, it is not a cure all medicine.
Works Cited
1. (http://www.brint.com/papers/ciover.htm)
2. (http://www.fuld.com/whatCI.html)
3. Kara, Dan “The New Face of Business Intelligence.” Software Magazine, November 2000
However, in a utopian business the business intelligence tool deployed would provide all the features and meet the needs perfectly. Today's businesses are anything but utopian. When an organization looks at deploying a business intelligence tool there can be many factors that will complicate its deployment. Often times challenges such as whether or not the application is intuitive or not will play the largest role in deployment.
Information is a key component, which is virtual source in all aspects of business. Information helps create a well balance between analytics, business information, customers, vendors, and sales. Without proper use of information, businesses may struggle to understand components of their business, such as monitoring information, validated decision making, performance measuring, and the ability to identify new business opportunities. In this text, there will dialogue on how a Laboratory Corporation of America, also known as LabCorp, uses each one of these functions, to ensure better business practices, and proper regulatory control of the business components, that make this business strive.
Intelligence analysts face complex problems, usually involving incomplete and ambiguous information, often under pressing time
Daniel, D. (2007, October 22). 10 Keys to a Successful Business Intelligence Strategy. CIO. Retrieved May 11, 2014, from http://www.cio.com/article/148000/10_Keys_to_a_Successful_Business_Intelligence_Strategy?page=2&taxonomyId=3002
In today’s organizational structure many of the organizations realize that business intelligence (BI) can provide solutions and important competitive advantages and thus want to evolve their BI strategies beyond spreadsheets.
The business intelligence (BI) marketplace is teaming with new innovations and struggles for market share. With new technologies and more companies entering the business intelligence landscape pricing for BI processes and tools are decreasing. “The relational database market is around 30 years old. It should be mature by now, but every year there seem to be new innovations in the relational database space. I’m always astounded that there continue to be new entrants” (Beckerle, p. 281, 2008).
The information can be made into categories which can be outputted to make choices for the future of the company. Information will be kept in the database and the database will contain tools to help process the information in multiple ways.
Companies are able to become analytic competitors through various activities. One of the first steps to becoming a competitor is the widespread use of modeling and optimization. Instead of following basic statistical information, it is wise to look for ways to enhance profitability. To become successful at this, organizations use both internal and external information retrieved from outside sources for a vivid understanding of their consumers. Secondly, an enterprise approach is necessary. Through this approach, employees become proactive at finding out what items or processes are effective. A good example would be of how the article talks about UPS’s approach for assessing problems,” The UPS Customer Intelligence G...
If you had that one piece of the puzzle that would have prevented the bombings of the twin towers in New York and the Pentagon on September 11 2001 would you know it? If you saw someone do something weird or suspicious before the attack on September 11 2001, would you have called the police? If someone had walked into a United States Embassy in a foreign country and said that they know someone was going to use a plane to destroy New York in two days, could this have stopped the attack? Intelligence Analysis puts the raw sources of information together, make predictions based on the data, and finally publish the results.
industry were given a scenario that sales have fallen. They were then given plans of actions to take and were to then list them in order from “least important to do first” to “most important to do first”. They were then compared to 50 of the industries experts. In conclusion, higher growth was associated with greater practical intelligence when leaders wanted their company to grow.
It is not uncommon for the online competition to be different from the brick-and-mortar competition. We believe that competitive intelligence (CI) should have a single-minded objective -- to develop the strategies and tactics necessary to transfer market share profitably and consistently from specific competitors to our clients. CI can help position a business to maximize the value of the capabilities that distinguish it from its competitors. A company that does not monitor and analyze their primary competitors will be at a disadvantage leaving its markets vulnerable.
To conclude, trade show intelligence is a sub-concept of competitive intelligence that allows organizations to use actionable information to change their position in the market, maintain it or make strategic decisions. A dedicated CI team made up of CI agents that understand the full context of the information needs derived from Key intelligence topics is required to collect the data and bring it back to the organization for analysis.
First of all, business intelligence analysis requires the capturing of information and storing in a single location for effective data analysis. Currently, data analysis is supported by transactional systems, business specific data marts, and other ad-hoc processes. Information is distributed making it difficult and time-consuming to access. Business teams have adapted to this environment by creating user maintained databases and manual “work-arounds” to support new types of reporting and analysis. This has resulted in inconsistent data, redundant data storage, significant resource use for maintenance, and inefficient response to changing business needs.
Computers and the use of internet allow for data mining. Data mining gives the business a better idea of what people want. With data mining you can get a better look at how the world views something and what is popular. Data mining allows for better ideas on what to do next with your company. Data mining also allows you to see what people think of your company and what you can change to make things better (Feigenbaum online).
Business intelligence, or BI, is an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. BI as a discipline is made up of several related activities, including data mining, online analytical processing, querying and reporting. Data mining is the process of sorting through large amounts of data and picking out relevant information. It is usually used by business intelligence organizations, and financial analysts, but is increasingly being used in the sciences to extract information from the enormous data sets generated by modern experimental and observational methods.