Download Business Intelligence

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Business Intelligence
Content
T4.1
T4.2
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The Importance of Business Intelligence and Data Mining
Improving Intelligence with Widgets
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T4.1 The Importance of Business Intelligence and Data Mining
T4.1
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The Importance of Business Intelligence and Data Mining
Business intelligence (BI) is a broad term that refers to a collection of processes, tools,
and technologies that help an enterprise to ultimately increase performance (or profitability) by improving sales, service, or the productivity of one or more business functions. BI is a competency that an enterprise may develop to leverage knowledge
management and data mining capabilities for the purpose of business performance
improvement. With the help of BI methods, an enterprise’s data is organized, analyzed, and then formatted into useful knowledge or actionable information to support profitable business actions.
DATA MINING
BI typically involves some type of data mining to make sense of the data. Data mining is a combination of artificial intelligence (AI) and statistical analysis to discover
information that is “hidden” in the data, such as the following:
• Associations: e.g., linking purchase of diapers with beer
• Sequences: e.g., linking events in order or together, such as graduating from college and buying a new car
• Classifications: e.g., recognizing patterns, such as the signs of customers who are
most likely to leave the company for a competitor
• Forecasting: e.g., predicting buying habits of customers based on past patterns
Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. Data mining
applications include credit rating, fraud detection, database marketing, customer relationship management, and stock market investments. Business uses of data mining
include the following:
Classification
• Classify the riskiness of credit applicants as low, medium, or high risk.
• Classify the nature of insurance claims as normal or suspicious.
Estimation
• Estimate the probability of positive response to a direct mail campaign.
• Estimate customers’ lifetime value to the enterprise.
Prediction
• Predict customers who are likely to attrite.
• Predict the number of customers who will accept an introductory zero interest
credit card offer and not repay within the time limit of the offer.
Data that have relevance for managerial decisions are accumulating at an incredible rate because of e-commerce, electronic banking, point-of-sale devices, bar-code
readers, and so forth. Such data are often stored in data warehouses and data marts
specifically intended for management decision support.
BUSINESS PERFORMANCE
IMPROVEMENTS
It is important to recognize that BI techniques, such as data mining, are only a means
to an end. That is, the goal of BI is not to mine stored data and then create reports,
but to generate intelligence that helps improve performance. Business performance
improvements can stem from two types of improvements:
1. Procedural improvements. Procedural tasks or processes are relatively well defined,
structured, and/or repeatable. For example, a manufacturing company may estimate that
an $80 million investment in a robotic system will increase production output by at least
50 units per hour. The impact on the bottom line for an estimated number of years is
relatively easy to calculate—although other critical issues also need to be considered
that are not well defined (those issues require knowledge, as discussed in #2).This example illustrates that procedural improvements are reasonably straightforward using
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Tutorial 4 Business Intelligence
optimization methods or other management science models. Optimization methods can
determine an optimal allocation of resources or investments for a firm that produces
multiple goods with limited resources.
2. Knowledge-based improvements. Knowledge work deals with more complex and
less structured relationships than procedures. Knowledge involves experience and
collaboration with others to determine what should be done next; for example, deciding how to increase sales in a particular market segment. Compared to procedural
improvements, knowledge-based improvements are more challenging. That is, it is a
much greater challenge to estimate how a small price adjustment to a product in a
particular market segment might affect all of the following:
a. Unit sales and availability
b. Plant utilization
c. Overall profitability
Consider that the decision to invest in robotics, which would increase the number of units produced, is related to the decision related to increasing sales. Increasing
the quantity of units produced will not improve profitability if those units are not
sold, and reducing prices to increase demand will fail if an adequate supply is not
available. These examples illustrate the importance of intelligence to improve decision making that can result from the use of BI. BI can help marketing and financial
managers make informed decisions, such as how to best position the business or how
best to increase demand.
T4.2
Improving Intelligence with Widgets
In 2008, MicroStrategy Inc. (microstrategy.com), a major provider of BI software,
introduced advanced visualization widgets for improved data comprehension and
decision making. The widgets add to the capabilities of its Dynamic Enterprise
Dashboards. These dashboards enable large volumes of data to be displayed and
understood in ways that cannot be accomplished with standard graph or table formats. Visualization widgets present data in an interactive manner to augment data
comprehension and enhance decision making.
MicroStrategy leveraged Adobe Flash to incorporate visualization, interactivity,
and animation into its widgets. For example, the Interactive Bubble Graph widget
allows time series data to be displayed as a data-driven movie, showing how data
change over time. Managers can use Adobe Flex 2 and Flex 3 to create their own
visualization widgets to include in dashboards and reports. Some of the advanced
visualization widgets include
• The Bubble Grid widget, which enables users to plot metric values as bubbles of
different colors and sizes within a grid
• The Funnel widget, a variation of a stacked percent bar chart in a funnel shape,
which is well-suited for a variety of business purposes, including pipeline analyses
for sales forecasts and sales process analysis
• The Waterfall widget, which displays a series of increments and decrements that
users can modify to perform a scenario analysis on the data and identify causes for
fluctuations in the business
To see a demonstration of MicroStrategy’s Dynamic Enterprise Dashboards and
the advanced visualization capabilities, visit microstrategy.com/digital-dashboard/
demos.asp.
Reference
“MicroStrategy Announces New Visualization Widgets,” B-Eye Network,
August 27, 2008, b-eye-network.com/view/8407 (accessed August 2008).