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FINAL EXAMINATION PAPER MAELM 210 : Essentials of Management Prepared by: MIGUEL DOMINIQUE A. MARTINEZ MAELM I Submitted to: DR. EDUARDO B. ARDALES Professor

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Being Effective or Efficient

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FINAL EXAMINATIONPAPER

MAELM 210: Essentials of Management

Prepared by:MIGUEL DOMINIQUE A. MARTINEZMAELM I

Submitted to:DR. EDUARDO B. ARDALESProfessor

Bicol UniversityGRADUATE SCHOOLLegazpi City

How do data affect information? What steps would you take to ensure that available data meet the major criteria for useful information (high quality, timeliness, relevance and comprehensiveness)?

Data are plain facts. When data are processed, organized, structured or presented in a given context so as to make them useful, they are called information. It is not enough to have data (such as statistics on research). Data in themselves are fairly useless but when these data are interpreted and processed to determine its true meaning, they become useful and can be called information. According to www.diffen.com, data is the computer's language while information is our translation of this language.For example, a student who conducts research survey might ask a member of the public to complete questionnaires about his specific topic. These completed questionnaires are data; they are processed and analyze in order to prepare a report on the survey. This resulting report is information.The website infoengineering.net cites that data is always correct but information can be wrong. Information captures data at a single point. The data changes over time. The mistake people make is thinking that the information they are looking at is always an accurate reflection of the data. By understanding the differences between them, we can better understand how to make better decisions based on the accurate facts.The first step to ensure that available data meet the major criteria for useful information (high quality, timeliness, relevance and comprehensiveness) is to clearly define the goals and objectives of data collection. A good data collection plan should include: a brief description of the project, the specific data that is needed, the rationale for collecting the data and what will be done with the data once it has been collected. Ensure all personnel are knowledgeable, certified, and trained for their assigned tasks.The next step is to consider if the process was well documented and communicated. Ensure all requirements are available. For example computer hardware, software, network, etc. Also, provide documentation for data providers and data processors.Then, clearly define what data is to be collected and how. We should decide what is to be evaluated and determine how a numerical value will be assigned, so as to facilitate measurement. The factors to consider are: What time interval should be part of the study; whether past, present, and future data will be collected and the methodologies that will be employed to record all the data. Careful attention should be paid to how reliable the data and its source has been, and whether it is advisable to continue using such data. Data that proves to be suspect should be discarded. Comply with professional standards for data collection, analysis, and reporting.Once the data collection process has been planned and defined, it is best to follow through with the process from start to finish, ensuring that the plan is being executed consistently and accurately. Data control is about achieving data accuracy and ensuring the right users have access to the right information, which also means blocking access, as needed. To control your data, you first need to clean it by removing duplicates and errors, and then set up processes and use technologies to keep it clean. We should check to see if the process was well implemented. We should check to see that the results (data and measurements) are reasonable and that they meet the criteria. If the results are not meeting the criteria, then we should determine what to do with any data and or measurements that are suspect. Reviewing the operational definitions and methodology with the participants will help us to clear up any misunderstanding or misinterpretations that may have caused the breakdowns. Finally, determine whether data were appropriately analyzed and reported.