Strategic Business Intelligence
As the name suggests predictive, analysis involves the ability to make assumptions about future behavior and outcomes. Given the limits of human experience, good predictions have to come from good data. The requisite data is derived as a consequence of effective business intelligence. Therefore predictive analysis is a consequence of business intelligence. In this article I will attempt to describe the various elements that come into play when trying to make predictions.
The ability to make accurate and defendable predictions will depend also on the ability to use mathematical computations methods such as data mining in order to collate relevant transactional and situational information. This is collectively known as business intelligence. Without the essential elements of information gathering, information processing and finally transferring that information to the decision makes, predictive analysis will not be effective.
There are some industries which virtually rely on predictive analysis to carry out their business. This normally occurs where risk is a fundamental aspect of the products that they sell. Examples include the insurance industry and credit facilities. In any given market segment, there will be quite a high number of potential applicants and business opportunities. Such businesses will need to make fairly accurate decisions about their potential customer if they are not to suffer significant loss.
A case in point is the application for car insurance where the insurer will use business intelligence to work out which particular customers are less likely to overburden the insurance company based on behavior patterns within their characteristic group as well as their own past conduct. If the insurance company gets it wrong, they will be exposed to high risk or even face law suits for discrimination. In this case business intelligence is being used to make day to business decisions even outside the strategic lines of management.
Generally speaking, the type of business intelligence that organization use will fall into the 3 main categories.
- The 1st category includes the ones that predict customer behavior based on existing data about them and their peer groups.
- The 2nd category includes the ones that describe customer behavior and preferences.
- The 3rd category involves making a final decision about the customer based on both the predictive and descriptive elements of the model.
These classifications are just summaries of what can be an exhaustive analysis of data from a very wide spectrum of information both from within the firm and from industry resource centers. The companies that can consistently balance out these three elements will make good decisions most of the time and will consequently improve their bottom line. Once can then see that if senior executives neglect to streamline the quality of their business intelligence, they will be outperformed by more diligent competitors.
In conclusion it is evidently clear that many businesses rely on the ability to predict the behavior of both their customers and their computers. In order to make accurate predictions, they need to access accurate raw data and process it into meaningful messages for the decision makers. Market intelligence enables the organization to streamline data patterns and disseminate them in a useful format.
Accurate Decisions, analyzing data, Behavior Patterns, Business Intelligence, Market Segment, Predictive Analysis, Strategic Management
