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Principles of Effective Reporting
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The key to effective reporting is to present information of interest to the intended audience in a quick, simple, and intuitive manner. The following are some of underlying principles of effective reporting: Report early, report often Report visually Report intuitively Use the right statistics Consolidate data correctly Summarize data effectively Customize reports for the intended audience Use concise verbal summaries Make the data available
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Report Early, Report Often
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Continual sharing of information and data is critical to the efficiency and overall success of a performance-testing project. However, not all of the information and data to be shared needs to take the form of a formal or semiformal report. One effective approach is to send stakeholders summary charts and tables every day or two in an e-mail message that contains a concise statement of key points. Use the feedback and questions you receive from those stakeholders when deciding what to put in the next formal or semiformal report. In this way you can gauge the needs of your audience before writing what is intended to be a stand-alone or final document. Sharing information and data with the technical team can be an even more straightforward process. It may be as simple as posting the location of the new results files to a team wiki before you begin analyzing them, and then posting links to any charts and graphs that derive from your analysis.
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Report Visually
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Most people find that data and statistics reported in a graphical format are easier to digest. This is especially true of performance results data, where the volume of data is frequently very large and most significant findings result from detecting patterns in the data. It is possible to find these patterns by scanning through tables or by using complex mathematical algorithms, but the human eye is far quicker and more accurate in the vast majority of cases. Once a pattern or point of interest has been identified visually, you will typically want to isolate that pattern by removing the remaining chart noise. In this context, chart noise includes all of the data points representing activities and time slices that contain no points of interest (that is, the ones that look like you expect them to). Removing the chart noise enables you to more clearly evaluate the pattern you are interested in, and makes reports more clear.
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Report Intuitively
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Whether formal or informal, reports should be able to stand on their own. If a report leaves the reader with questions as to why the information is important, the report has failed. While reports do not need to provide the answers to issues to be effective, the issues should be quickly and intuitively clear from the presentation. One method to validate the intuitiveness of a report is to remove all labels or identifiers from charts and graphs and all identifying information from narratives and then present the report to someone unfamiliar with the project. If that person is able to quickly and correctly point to the issue of concern in the chart or graph, or identify why the issue discussed in the narrative is relevant, then you have created an intuitive report.
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Use the Right Statistics
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Even though there is a widespread need to understand many statistical concepts, many software developers, testers, and managers either do not have strong backgrounds in or
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do not enjoy statistics. This can lead to significant misrepresentations of performance test results when reporting. If you are not sure what statistics to use to highlight a particular issue, do not hesitate to ask for assistance.
Consolidate Data Correctly
While it is not strictly necessary to consolidate results, it tends to be much easier to demonstrate patterns in results when those results are consolidated into one or two graphs rather than distributed over dozens. That said, it is important to remember that only results from identical test executions that are statistically similar can be consolidated into performance report output tables and charts.
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