Original Research

Evaluating operationalisation of integrated monitoring and evaluation system in Kisumu County: Implications for policy makers

Enock Warinda
African Evaluation Journal | Vol 7, No 1 | a385 | DOI: https://doi.org/10.4102/aej.v7i1.385 | © 2019 Enock Warinda | This work is licensed under CC Attribution 4.0
Submitted: 28 February 2019 | Published: 20 June 2019

About the author(s)

Enock Warinda, Association for Strengthening Agricultural Research in Eastern and Central Africa, Entebbe, Uganda, Uganda


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Abstract

Background: Evaluation findings are increasingly becoming valuable for policy makers in Kenya. The Directorate of Monitoring and Evaluation is responsible for providing reliable data findings for decision-makers. They are in turn expected to access the data and information through the National Integrated Monitoring and Evaluation System (NIMES). Unfortunately, the directorate hardly receives timely data as required, thus is unable to make timely decision within the ministry of agriculture, livestock and irrigation in Kisumu County.

Objectives: The aim of this study was to assess the extent of operationalisation of NIMES through utilisation of the electronic project management information system (e-ProMIS) within the three agricultural departments.

Methods: Through single-point face-to-face interviews using semi-structured questionnaires, mixed methods approach and Likert scale were applied to assess the level of operationalisation of, staff competences in, and satisfaction with NIMES. Both random and purposive sampling was used. Using mixed methods approach, primary and secondary data were collected from 10 key indicators and fitted in a binary logistic regression model to assess the level of operationalisation of NIMES.

Results: This article shows that operationalisation of NIMES is unsatisfactory, and data collected are incorrectly formatted. None of the departmental personnel charged with uploading relevant data in e-ProMIS neither accessed nor utilised the platform. There were no champions supporting NIMES, thus no reports generated from the system.

Conclusions: Factors hindering operationalisation of NIMES were: dysfunctional monitoring and evaluation (M&E) systems, limited human capacity on M&E, lack of NIMES champions, limited availability of data, unclear information flow to decision makers and inadequate integration of NIMES in planning and budgeting.


Keywords

NIMES; operationalisation; e-ProMIS; evaluation; agriculture; policy; capacity

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Crossref Citations

1. Editorial – 2019: Omniscience of monitoring and evaluation
Mark A. Abrahams
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doi: 10.4102/aej.v7i1.433