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Forecast and Targeting Techniques for Key Performance Indicators November 11, 2016

Explore the importance of forecasting for KPIs, the reliability required, applications, implications, and functionality of a KPI Forecast Tool using the Linear Method in Excel. Stay ahead of goal achievement with accurate metrics.

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Forecast and Targeting Techniques for Key Performance Indicators November 11, 2016

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  1. Forecast and Targeting Techniquesfor Key Performance IndicatorsNovember 11, 2016

  2. THE NEED TO FORECAST • It is an essential step in planning and organizational management. • Helps in developing process and systems. • Allows detailed feasibility analysis of expected outcomes. • Integrates Monitoring and Evaluation for continuous process.

  3. RELIABILITY OF A FORECAST • Must be scientific. • Based on empirical evidences. • Systematic, as a part of a research or benchmarking process. • Uses reliable source of data.

  4. APPLICATIONS

  5. IMPLICATIONS • Sets standards for benchmarking and quotas. • Disaster prevention. • Resource management. • Estimates time frames and relevance of project/process. • Monitors progress and Evaluates performance.

  6. Key Performance Indicators • A quantifiable metric that reflects how well an organization is achieving its stated goals and objectives. • These are tools that may be used to define, measure, monitor and track its performance over time. • Play an integral part in decision making.

  7. Key Performance Indicators • Some of the KPIs set by the DepEd are: • Enrollment • Net Enrollment Rate • Gross Enrollment Rate • Cohort Survival Rate • Promotion Rate • Repetition Rate

  8. KPI FORECAST TOOL • Developed to provide a statistical analysis of the historical data, identifying its trend and relative changes to determine future values of the identified Key Performance Indicator set according to DepEd standards.

  9. KPI FORECAST TOOL

  10. FUNCTIONS OF THE FORECAST TOOL • The Forecast tool generates forecasted values for the next six years starting from the indicated base year. • It is designed to provide a scientific basis for the forecasted values using the Linear Method.

  11. USING THE FORECAST TOOL • The Forecast tool was designed to be user friendly, compact and compatible with most MS Excel versions. • Forecast values generated can easily be collated on a separate spreadsheet and be used for reporting purposes. Version 0.25 is less than 1mb.

  12. USING THE FORECAST TOOL • Select Region, KPI to Forecast and Base Year • Fill-in required input data • Analyze Forecast Results • Report and Forward Results

  13. THE LINEAR METHOD • Also known as Linear Regression Forecast Method. • Assumes stationarity of data - no seasonality and is not cyclical. • Derived out of the slope and intercept formula. • Measures change of figures based on historical data.

  14. FINAL THOUGHTS • So as not to make the tool complex by using Macros and other add-ins, the tool was developed using the available functions in Excel that are considered component equations of the regression analysis.

  15. FINAL THOUGHTS • This tool is still under development, and is planned to be a part of a broader system of benchmarking and database management. Further communication with regards to this tool’s development is expected. • Nevertheless, this tool is fully functional and can generate forecast values that will aid our respective institutions in planning, monitoring and evaluation.

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