IJSSER

Title: An Illustration of Double Counting and Under-Counting in Monitoring and Evaluation Using the Mkulima Project
Authors: Dr Isaack Michael Nguliki, PhD.
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Dr Isaack Michael Nguliki, PhD.1 Managing Director at DERICH Consulting Limited part-time Lecturer in the Master of Arts in Development Evaluation Program at the Dar es Salaam University College of Education (DUCE)
MLA 8 Nguliki, Dr Isaack Michael. "An Illustration of Double Counting and Under-Counting in Monitoring and Evaluation Using the Mkulima Project." Int. j. of Social Science and Economic Research, vol. 9, no. 9, Sept. 2024, pp. 3188-3197, doi.org/10.46609/IJSSER.2024.v09i09.005. Accessed Sept. 2024. APA 6 Nguliki, D. (2024, September). An Illustration of Double Counting and Under-Counting in Monitoring and Evaluation Using the Mkulima Project. Int. j. of Social Science and Economic Research, 9(9), 3188-3197. Retrieved from https://doi.org/10.46609/IJSSER.2024.v09i09.005 Chicago Nguliki, Dr Isaack Michael. "An Illustration of Double Counting and Under-Counting in Monitoring and Evaluation Using the Mkulima Project." Int. j. of Social Science and Economic Research 9, no. 9 (September 2024), 3188-3197. Accessed September, 2024. https://doi.org/10.46609/IJSSER.2024.v09i09.005.
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ABSTRACT: The Mkulima Project serves as a case study to illustrate double-counting and under-counting errors in monitoring and evaluation systems. Double counting occurs when beneficiaries are recorded more than once, inflating the reported numbers, as seen in the post-harvest management (PHM) and small and medium enterprises (SME) training sessions where 730 instances of double counting were identified. Conversely, undercounting happens when not all beneficiaries are recorded, leading to an understatement of the project’s reach; in this case, incorporating both direct and indirect or primary and secondary beneficiaries revealed a total outreach of 720, surpassing the 500 targeted farmers. This example underscores the critical impact of accurate data reporting and the necessity for robust monitoring and evaluation systems to mitigate these errors.

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