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

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.

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

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.

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

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

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

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

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

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.

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)

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

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

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.

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

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

Behavioral Metrics Visitor Web site metrics

Behavioral Metrics Exposure, visit, and hit Web site metrics

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

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

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