Cases Better Data Management

MyMISLab Visit mymislab.com for simulations, tutorials, and end-of-chapter problems. Chapter Cases Better Data Management Helps the Toronto Globe and Mail Reach Its Customers Driving ARI Fleet Management with Real Time Analytics American Water Keeps Data Flowing Does Big Data Bring Big Rewards? Video Cases Dubuque Uses Cloud Computing and Sensors to Build a Smarter City Data Warehousing at REI: Understanding the Customer Maruti Suzuki Business Intelligence and Enterprise Databases 1. What are the problems of managing data resources in a traditional file environment? 2. What are the major capabilities of database management systems (DBMS) and why is a relational DBMS so powerful? 3. What are the principal tools and technologies for accessing information from databases to improve business performance and decision making? 4. Why are information policy, data administration, and data quality assurance essential for managing the firm’s data resources?

6 Learning Objectives after reading this chapter, you will be able to answer the following questions: Foundations of business intelligence: Databases and information Management C H A P T E R

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Have you ever received a new subscription offer from a newspaper or anmagazine to which you already subscribed? In addition to being annoyance, sending a superfluous offer to customers increases
marketing costs. So why is this happening? The answer is probably
because of poor data management. The newspaper most likely was unable to
match its existing subscriber list, which it maintained in one place, with
another file containing its list of marketing prospects.
The Globe and Mail, based in Toronto, Canada, was one of those publications that had these problems. In print for 167 years, it is Canada’s largest
newspaper, with a cumulative six-day readership of nearly 3.3 million. The
paper has a very ambitious marketing program, viewing every Canadian
household that does not already subscribe as a prospect. But it has had trouble
housing and managing the data on these prospects.
Running a major newspaper requires managing huge amounts of data,
including circulation data, advertising revenue data, marketing prospect and
“do not contact” data, and data on logistics and deliveries. Add to that the data
required to run any business, including finance and human resources data.
For many years The Globe and Mail housed much of its data in a mainframe
system where the data were not easy to access and analyze. If users needed
any information, they had to extract the data from the mainframe and bring it
to one of a number of local databases for analysis, including those maintained
in Microsoft Access, Foxbase Pro, and Microsoft Excel. This practice created
numerous pockets of data maintained in isolated databases for specific
purposes but no central repository where the most up-to-date data could be
Better Data ManageMent Helps tHe toronto
gloBe anD Mail reacH its custoMers
accessed from a single place. With data scattered in so many different systems
throughout the company, it was very difficult to cross-reference subscribers
with prospects when developing the mailing list for a marketing campaign.
There were also security issues: The Globe and Mail collects and stores customer
payment information, and housing this confidential data in multiple places
makes it more difficult to ensure that proper data security controls are in place.
In 2002, the newspaper began addressing these problems by implementing a
SAP enterprise system with a SAP NetWeaver BW data warehouse that would
contain all of the company’s data from its various data sources in a single
location where the data could be easily accessed and analyzed by business
users.
The first data to populate the data warehouse was advertising sales data,
which is a major source of revenue. In 2007, The Globe and Mail added circulation data to the warehouse, including delivery data details such as how much
time is left on a customer’s subscription and data on marketing prospects from
third-party sources. Data on prospects were added to the warehouse as well.
With all these data in a single place, the paper can easily match prospect and
customer data to avoid targeting existing customers with subscription promotions. It can also match the data to “do not contact” and delivery area data to
determine if a newspaper can be delivered or whether a customer should be
targeted with a promotion for a digital subscription.
Despite the obvious benefits of the new data warehouse, not all of The Globe
and Mail’s business users immediately came on board. People who were used to
extracting data from the mainframe system and manipulating it in their own
local databases or file continued to do the same thing after the data warehouse
went live. They did not understand the concept of a data warehouse or the need
to work towards enterprise-wide data management. The Globe and Mail’s management decided to tackle this new problem by educating its users, especially its
marketing professionals, with the value of having all the organization’s data in a
data warehouse and the tools available for accessing and analyzing these data.
The Globe and Mail’s new data analysis capabilities produced savings from
efficiencies and streamlined processes that paid for the investment in one year.
Marketing campaigns that previously took two weeks to complete now only
take one day. The newspaper can determine its saturation rates in a given area
to guide its marketing plans. And there are fewer complaints from subscribers
and potential subscribers about being contacted unnecessarily.
To capitalize further on data management and analytics, The Globe and Mail
turned to the cloud. A key business goal for the company was to beef up online
content and increase the paper’s digital subscriber base. The Globe and Mail
devoted more resources to digital online content, with different subscription rates
for online-only customers and print customers. To aggressively court digital subscribers, The Globe and Mail had to mine its clickstream data logging user actions
on the Web to target potential digital subscribers based not only on their specific
interests but also their interests on a particular day. The volume of data was too
large to be handled by the company’s conventional Oracle database. The solution
was to use SAP HANA ONE in-memory computing software running on the
Amazon Web Services cloud computing platform, which accelerates data analysis
and processing by storing data in the computer’s main memory (RAM) rather
than on external storage devices. This cloud solution lets The Globe and Mail pay
for only what capabilities it uses on an hourly basis.
Sources: www.theglobeandmail.com, accessed March 1, 2014; “The Globe and Mail Uses SAP
HANA in the Cloud to row Its Digital Audience,” SAP Insider Profiles, April 1, 2013; and
David Hannon, “Spread the News,” SAP Insider Profiles, October-December 2012.
216 part two Information Technology Infrastructure
The experience of The Globe and Mail illustrates the importance of data management. Business performance depends on what a firm can or
cannot do with its data. The Globe and Mail was a large and thriving business,
but both operational efficiency and management decision making were
hampered by fragmented data stored in multiple systems that were difficult to
access. How businesses store, organize, and manage their data has an enormous
impact on organizational effectiveness.
The chapter-opening diagram calls attention to important points raised by
this case and this chapter. The Globe and Mail’s business users were maintaining their own local databases because the company’s data were so difficult to
access in the newspaper’s traditional mainframe system. Marketing campaigns
took much longer than necessary because the required data took so long to
assemble. The solution was to consolidate organizational data in an enterprisewide data warehouse that provided a single source of data for reporting and
analysis. The newspaper had to reorganize its data into a standard companywide format, establish rules, responsibilities, and procedures for accessing and
using the data, provide tools for making the data accessible to users for querying and reporting, and educate its users about the benefits of the warehouse.
The data warehouse boosted efficiency by making the Globe’s data easier to
locate and assemble for reporting. The data warehouse integrated company
data from all of its disparate sources into a single comprehensive database that
could be queried directly. The data were reconciled to prevent errors such as
contacting existing subscribers with subscription offers. The solution improved
customer service while reducing costs. The Globe and Mail increased its ability
to quickly analyze vast quantities of data by using SAP HANA running on
Amazon’s cloud service.
Here are some questions to think about: What was the business impact of
The Globe and Mail’s data management problems? What work had to be done
by both business and technical staff to make sure that the data warehouse
produced the results envisioned by management?
Chapter 6 Foundations of Business Intelligence: Databases and Information Management 217
6.1 What are the problems of managing data
resources in a traditional file
environment?
An effective information system provides users with accurate, timely, and relevant information. Accurate information is free of errors. Information is timely when it is available to decision makers when it
is needed. Information is relevant when it is useful and appropriate
for the types of work and decisions that require it.
You might be surprised to learn that many businesses don’t have timely,
accurate, or relevant information because the data in their information systems
have been poorly organized and maintained. That’s why data management is
so essential. To understand the problem, let’s look at how information systems
arrange data in computer files and traditional methods of file management.
File organization terMs anD concepts
A computer system organizes data in a hierarchy that starts with bits and
bytes and progresses to fields, records, files, and databases (see Figure 6.1).
A bit represents the smallest unit of data a computer can handle. A group
of bits, called a byte, represents a single character, which can be a letter, a
number, or another symbol. A grouping of characters into a word, a group
of words, or a complete number (such as a person’s name or age) is called a
field. A group of related fields, such as the student’s name, the course taken,
the date, and the grade, comprises a record; a group of records of the same
type is called a file.
For example, the records in Figure 6.1 could constitute a student course file.
A group of related files makes up a database. The student course file illustrated
in Figure 6.1 could be grouped with files on students’ personal histories and
financial backgrounds to create a student database.
A record describes an entity. An entity is a person, place, thing, or event on
which we store and maintain information. Each characteristic or quality describing a particular entity is called an attribute. For example, Student_ID, Course,
Date, and Grade are attributes of the entity COURSE. The specific values that
these attributes can have are found in the fields of the record describing the
entity COURSE.
proBleMs witH tHe traDitional File
environMent
In most organizations, systems tended to grow independently without a
company-wide plan. Accounting, finance, manufacturing, human resources,
and sales and marketing all developed their own systems and data files.
Figure 6.2 illustrates the traditional approach to information processing.
Each application, of course, required its own files and its own computer
program to operate. For example, the human resources functional area might
have a personnel master file, a payroll file, a medical insurance file, a pension
file, a mailing list file, and so forth until tens, perhaps hundreds, of files and
programs existed. In the company as a whole, this process led to multiple
master files created, maintained, and operated by separate divisions or departments. As this process goes on for 5 or 10 years, the organization is saddled
with hundreds of programs and applications that are very difficult to maintain
218 part two Information Technology Infrastructure
and manage. The resulting problems are data redundancy and inconsistency,
program-data dependence, inflexibility, poor data security, and an inability to
share data among applications.