Thu thập dữ liệu là trung tâm của phương pháp thu nhập từ đầu. Cả hai dữ liệu cứng (đại diện cho sản lượng, chất lượng, chi phí, và thời gian) và dữ liệu mềm (bao gồm cả sự hài lòng công việc và sự hài lòng của khách hàng) được thu thập. | 44 ROI METHODOLOGY BASICS Collecting Data Data collection is central to the ROI methodology. Both hard data representing output quality cost and time and soft data including job satisfaction and customer satisfaction are collected. Data are collected using a variety of methods including Surveys Questionnaires Tests Observations Interviews Focus groups Action plans Performance contracts Business performance monitoring The important challenge in data collection is to select the method or methods appropriate for the setting and the specific project within the time and budget constraints of the organization. Data collection methods are covered in more detail in Chapters 5 through 7. Isolating the Effects of the Project An often overlooked issue in evaluations is the process of isolating the effects of the project. In this step specific strategies are explored that determine the amount of output performance directly related to the project. This step is essential because many factors will influence performance data. The specific strategies of this step pinpoint the amount of improvement directly related to the project resulting in increased accuracy and credibility of ROI calculations. The following techniques have been used by organizations to tackle this important issue Control groups Trend line analysis Forecasting models Participant estimates Managers estimates Senior management estimates Experts input Customer input The ROI Process Model 45 Collectively these techniques provide a comprehensive set of tools to handle the important and critical issue of isolating the effects of projects. Chapter 8 is devoted to this important step in the ROI methodology. Converting Data to Monetary Values To calculate the return on investment Level 4 impact data are converted to monetary values and compared with project costs. This requires that a value be placed on each unit of data connected with the project. Many techniques are available to convert data to monetary values. The .
