1. BUSINESS DRIVEN TECHNOLOGY
Chapter Four:
Measuring the Success of Strategic Initiatives

2. 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

3. 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.

4. 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

5. 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.

6. 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

7. Example of IT BENCHMARKING – BASELINING METRICS
e-government benchmarks for IT efficiency and effectiveness
Canada:
satisfaction of its citizens
CRM practice
Customer service vision
approach to offering e-government 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

8. 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

9. 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

10. 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

11. 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.

12. 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)

13. THE INTERRELATIONSHIPS OF EFFICIENCY AND EFFECTIVENESS IT METRICS
The interrelationships between efficiency and effectiveness
This area is not an ideal for any business
Possible area depends on business strategies

14. DETERMINING IT EFFICIENCY AND EFFECTIVENESS
Customer metrics – assess the management of customer relationships by the organization and include:
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

15. 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.

16. 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 dot-com 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

17. 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:
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

18. Behavioral Metrics
Visitor Web site metrics

19. Behavioral Metrics
Exposure, visit, and hit Web site metrics

20. OPENING CASE STUDY QUESTIONS How Levi’s Got Its Jeans into Wal-Mart
Formulate a strategy for how Levi’s can use efficiency metrics to improve its business
Formulate a strategy for how Levi’s can use effectiveness metrics to improve its business

21. 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

22. CHAPTER FOUR CASE QUESTIONS
How could you use efficiency metrics to help place a value on Friendster?
How could you use effectiveness metrics to help place a value on Friendster?
Explain how a venture capital company can value Friendster at $53 million when the company has yet to generate any revenue
Explain why Google would be interested in buying Friendster for $30 million when the company has yet to generate any revenue