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Business Intelligence
The quest for so-called "Business Intelligence," or BI for short, has been on the forefront of many organizational priorities in the last decade and it is likely that this trend will continue indefinitely. The attraction to BI is fairly clear. Although collecting and storing large amounts of information has become ubiquitous among modern organizations, there has been a relatively slower development in the ability to harness information to better support organizational goals and meet business objectives. Therefore the emerging BI technologies have promised to deliver better reporting and metrics to help professional spot trends and find insights. However, in spite of the best intentions, the ability to BI to contribute any meaningful assistance in finding opportunities has been somewhat lacking. This paper will look at the current state of BI, some of the best practices, as well as opportunities for the future.
Data does not equal Information
It has been recommended that the BI initiatives be broken down into smaller categories to better define the steps in the process. The three sub-categories are as follows (Staples, 2009):
1. Data Warehouse (DW) -- companies need a place for data to reside and rules on how the data should be structured.
2. Business Intelligence -- companies need a way to slice and dice the data and generate reports.
3. Analytics -- companies need to extract the data, analyze trends, uncover opportunities, find new...
This can include everything from transaction histories to customer information and most organization have large amounts of this type of data that they store.
The next category involves beginning to put the data into good use. Reports generated around various metrics are an example of Business Intelligence. Many of these reports are built into various database platforms and are being marketed by companies such as SAP, IBM, and Oracle (Staples, 2009). However, these metrics are, for the most part, generic reporting mechanisms that handle the basic business metrics; they basically represent the set of data that the user pools from the data warehouse. The most comprehensive BI solution is considered to be in the realm of business analytics. These tools are generally custom built to find the organization and make use of algorithmic functions to try to spot trends in the movements of the data in the data warehouse and actually provide what is considered to be information. It is further argued that BI only really takes place when such "information" is generated.
Analytics in the Modern Environment
In the globalized world, many firms find it challenging, if not impossible, to effectively differentiate their products (Davenport, 2005). Although some products and services are so innovative that there is no available substitute, most products can be easily copied…
Works Cited
Davenport, T. (2005). Competing on Analytics. Havard Business Review, 1-12.
Smild, S. (2011, September 2). Tom Davenport: Why aren't most organisations competing on analytics? Retrieved from Analyst First: http://analystfirst.com/2011/09/02/1001/tom-davenport-why-aren%E2%80%99t-most-organisations-competing-on-analytics/
Staples, S. (2009, April 14). Analytics: Unlocking Value in Business Intelligence (BI) Initiatives. Retrieved from CIO: http://www.cio.com/article/489257/Analytics_Unlocking_Value_in_Business_Intelligence_BI_Initiatives?page=1&taxonomyId=3002
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