Page 387 - Using MIS

Q4 How Do Organizations Use Reporting Applications? 355

train salespeople on the best way to up-sell to customers. The third data mart is used to analyze
customer order data for the purpose of reducing labor for item picking from the warehouse. A
company like Amazon, for example, goes to great lengths to organize its warehouses to reduce
picking expenses.
As you can imagine, it is expensive to create, staff, and operate data warehouses and data
marts. Only large organizations with deep pockets can afford to operate a system like that shown
in Figure 9-12. Smaller organizations like AllRoad operate subsets of this system, but they
must find ways to solve the basic problems that data warehouses solve, even if those ways are
informal.

Q4 How Do Organizations Use Reporting
Applications?

A reporting application is a BI application that inputs data from one or more sources and ap-
plies reporting operations to that data to produce business intelligence. We will first summarize
reporting operations and then illustrate two important reporting applications: RFM analysis
and OLAP.

Basic Reporting Operations

Reporting applications produce business intelligence using five basic operations:
• Sorting
• Filtering
• Grouping
• Calculating
• Formatting
None of these operations is particularly sophisticated; they can all be accomplished using
SQL and basic HTML or a simple report writing tool.
Addison at AllRoad used Access to apply all five of these operations. Examine, for example,
Figure 9-11 (page 350). The results are sorted by Total Revenue, filtered for particular parts, sales
are grouped by PartNumber, Total Orders and Total Revenue are calculated, and the calculations
for Total Revenue are formatted correctly as dollar currency.
These simple operations can be used to produce complex and highly useful reports.
Consider RFM analysis and Online Analytical Processing as two prime examples.
RFM Analysis

RFM analysis, a technique readily implemented with basic reporting operations, is used to ana-
10
lyze and rank customers according to their purchasing patterns. RFM considers how recently
(R) a customer has ordered, how frequently (F) a customer ordered, and how much money (M)
the customer has spent.
To produce an RFM score, the RFM reporting tool first sorts customer purchase records by
the date of their most recent (R) purchase. In a common form of this analysis, the tool then di-
vides the customers into five groups and gives customers in each group a score of 1 to 5. The 20
percent of the customers having the most recent orders are given an R score of 1, the 20 percent

10 Arthur Middleton Hughes, “Boosting Response with RFM,” Marketing Tools, May 1996. See also http://
dbmarketing.com.