Transcript chapter_04

BUSINESS DRIVEN
TECHNOLOGY
Chapter Four:
Measuring the Success of
Strategic Initiatives
LEARNING OUTCOMES
4.1
Compare efficiency IT metrics and effectiveness IT
metrics
4.2
List and describe five common types of efficiency IT
metrics
4.3
List and describe four types of effectiveness IT metrics
4.4
Explain customer metrics and their importance to an
organization
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General Electric Co. (GE)
• An effort to offer detailed information to all layers of management.
• They invested 1.5 billion in employee time, hardware, software, and
other technologies to implement a real-time operations monitoring
system.
• GE’s executive use the new system to monitor sales, inventory, and
savings across its 13 different global business operations every 15
minutes.
• This allows GE to respond to changes, reduce cycle times, and
improve risk management on an hourly basis instead of waiting for
month-end or quarter-end reports.
• GE estimates that the 1.5 billion investment will provide a 33 percent
return on investment over the five years of the project.
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Organizations’ spending on IT
• Some organizations spend up to 50 percent of their
total capital expenditures on IT to remain
competitive.
• To justify expenditures on IT, an organization must
measure the payoff of these investments
their impact on business performance
the overall business value gained
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CHAPTER FOUR OVERVIEW
• Efficiency (Do things right: getting the most of each
resource) and effectiveness (Do the right things: setting
the right goals and objectives) IT metrics are two ways to
measure the success of IT strategic initiatives
• The two – efficiency and effectiveness – are definitely
interrelated. However, success in one area does not
necessarily imply success in the other.
– Efficiency IT metrics – measure the performance of the IT
system itself including throughput, speed, availability, etc.
– Effectiveness IT metrics – measure the impact IT has on
business processes and activities including customer
satisfaction, conversion rates, sell-through increases, etc.
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BENCHMARKING –
BASELINING METRICS
• Benchmarks – baseline values the system seeks
to attain
• Benchmarking – a process of continuously
measuring system results, comparing those results
to optimal system performance (benchmark
values), and identifying steps and procedures to
improve system performance
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Example of IT BENCHMARKING –
BASELINING METRICS
• e-government benchmarks for IT efficiency and
Canada:
effectiveness
•satisfaction of its citizens
• CRM practice
• Customer service vision
• approach to offering egovernment service
through multiple-service
delivery channels
• initiatives for identifying
services for individual
citizen segment
USA:
• the number of computers
per 100 citizens,
•the number of Internet
hosts per 10,000 citizens,
• the percentage of the
citizen population on line
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THE INTERRELATIONSHIPS OF
EFFICIENCY AND EFFECTIVENESS IT METRICS
• Efficiency IT metrics focus on technology and
include:
– Throughput – amount of information that can travel
through a system at any point in time
– Speed – amount of time to perform a transaction
– Availability – number of hours a system is available
– Accuracy – extent to which a system generates correct
results
– Response time – time to respond to user interactions
– Web traffic – includes number of pageviews, number of
unique visitors, and time spent on a Web page
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THE INTERRELATIONSHIPS OF
EFFICIENCY AND EFFECTIVENESS IT METRICS
• Effectiveness IT metrics focus on an organization’s goals,
strategies, and objectives (e.g. broad cost leadership,
increasing customers by 10%, reducing new product
development cycle times to 6 months) and include:
– Usability – the ease with which people perform transactions
and/or find information
– Customer satisfaction – such as satisfaction surveys, the
percentage of existing customers retained, increases in revenue
per customer
– Conversion rates – the number of customers an organization
“touches” for the first time and convinces to purchase its
products or services. This is a popular metric for evaluating the
effectiveness of banner and pop-up.
– Financial – such as return on investment, cost-benefit analysis,
and break-even analysis
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Example IT Metrics on Private Sector
• e-Bay: an example of private sector that constantly
benchmarks it information technology efficiency
and effectiveness – revenue increase 78%, earning grew
135%
• Maintaining constant Web site availability and
optimal throughput performance is critical to
eBay’s success.
• Highest visitor volume (efficiency): 4.5 million
unique visitors per week
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THE INTERRELATIONSHIPS OF
EFFICIENCY AND EFFECTIVENESS IT METRICS
• Security is an issue for any organization offering
products or services over the Internet.
• It is inefficient for an organization to implement
Internet security, since it slows down processing
time. However, to be effective it must implement
Internet security.
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Security Issues on
EFFICIENCY AND EFFECTIVENESS
• From an efficiency IT metric point of view, security
generates some inefficiency.
• From an organization’s business strategy point of
view, however, security should lead to increases in
effective metrics.
Secure Internet connections must offer encryption and
Secure Sockets Layers (SSL denoted by the lock
symbol in the lower right corner of a browser and/or
“s” in https)
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THE INTERRELATIONSHIPS OF
EFFICIENCY AND EFFECTIVENESS IT METRICS
• The interrelationships between efficiency and
effectiveness
Possible area
depends on
business
strategies
This area is not
an ideal for any
business
Possible area
depends on
business
strategies
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DETERMINING IT
EFFICIENCY AND EFFECTIVENESS
• Customer metrics – assess the management of
customer relationships by the organization and
include:
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Market share
Customer acquisition
Customer satisfaction
Customer profitability
• Wal-Mart’s retail site has grown 66%, 500,000 visitors daily, 2
million web pages downloaded daily, 6.5 million visitors per week,
and 60,000 users logged on simultaneously
• Problems: congestion caused by capacity too small to handle
large amount of traffic  company must monitor throughput, speed,
availability to determine if the system is operating above or below
customer expectations
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Web Traffic Analysis
• Most companies measure the traffic on a Web site as the
primary determinant of the Web site’s success.
• However, a large amount of Web site traffic does not
necessarily equate to large sales.
• Many organizations with high Web site traffic have low
sales volumes.
• A company can go further and use Web Traffic analysis to
determine the revenue generated by Web Traffic, the
number of new customers acquired by Web Traffic, any
reductions in customer service calls resulting from Web
Traffic, or to understand the effectiveness of Web
advertising.
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Web Traffic Analysis
• Web site traffic analysis can include:
– Cookie – a small file deposited on a hard drive by a Web site
containing information about customers and their Web activities
without their consent
– Click-through – a count of the number of people who visit one
site and click on an advertisement that takes them to the site of
the advertiser
– Banner ad – a small ad on one Web site that advertises the
products and services of another business, usually another dotcom business. Advertisers can track how often customers click
on banner ads resulting in a click-through to their Web site.
– Interactivity – measure the visitor interactions with the target ad.
Such interactions i.e. duration of time spends viewing the ad.,
no. of pages viewed, no. of repeat visits  measure actual
consumer activities, something that was impossible to do in the
past
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Behavioral Metrics
• Click-stream data tracks the exact pattern of a consumer’s
navigation through a Web site and can reveal a number of
basic data points on how customers interact with Web
sites.
• Metrics based on Click-stream data include:
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Number of pageviews
Pattern of Web sites visited i.e. exit page, prior web sites
Length of stay on a Web site
Date and time visited
Number of customers with shopping carts
Number of abandoned shopping carts
Number of registration filled out per 100 visitors
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Behavioral Metrics
• Visitor Web site metrics
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Behavioral Metrics
• Exposure, visit, and hit Web site metrics
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OPENING CASE STUDY QUESTIONS
How Levi’s Got Its Jeans into Wal-Mart
1. Formulate a strategy for how Levi’s can use
efficiency metrics to improve its business
2. Formulate a strategy for how Levi’s can use
effectiveness metrics to improve its business
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CHAPTER FOUR CASE
How Do You Value Friendster?
• Friendster specializes in social networking developed by
Canadian software developer: 33-year-old Jonathan
Abrams, laid off by Netscape
• 5 Million users and 50,000 page-views per day
• Friendster received over $13 million in VC capital
• A venture capital company recently valued Friendster at
$53 million
• Friendster has yet to generate any revenue; no
subscription fee but charge for customize profile, plus job
referrals and classmate searches
• Google recently offered to buy Friendster for $30 million
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CHAPTER FOUR CASE QUESTIONS
1.
How could you use efficiency metrics to help place a
value on Friendster?
2.
How could you use effectiveness metrics to help place a
value on Friendster?
3.
Explain how a venture capital company can value
Friendster at $53 million when the company has yet to
generate any revenue
4.
Explain why Google would be interested in buying
Friendster for $30 million when the company has yet to
generate any revenue
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