Performance measurement is a necessary exercise for transparency and accountability in governance and the Result Based Management (RBM) remains the most practical tool for achieving this. While result reporting is no longer an option across government departments, data is in the centre of it all. For instance, creating a data path to help policy makers collect, organize, analyse and use evidences to make decisions is a big challenge. This presentation is intended to discuss the challenges of measuring vertical and horizontal results and how data-based technologies are used nowadays to ameliorate these conditions.
Since the advent of Big Data – its concept and practices have attracted governments’ curiosity. The presentation will highlight the significance of Big Data technology in RBM.
Furthermore, the presentation is intended to raise the interests of monitoring and evaluation frontline managers, bureaucrats, data management departments and Non-for-Profit agencies to Big Data resources. The presentation hopes to sensitize, departments and agencies to improve the techniques for collecting and processing difficult data whether at federal, regional or municipalities levels. Projects and program managers may also find this presentation useful.
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Dr. Diana Gimba is the Principal Partner of iRadar Data, an information technology company specialised in managing government and Non -for-Profit data. With over 2 decades of designing and implementing Result Based Management (RBM) framework, Diana supports governments departments (at Federal, regional and municipality levels) to create the environment necessary for using data to measure performance and improve evidenced based decision making. These include setting targets, defining performance indicators, designing data collection tools and developing strategies to engage stakeholders in the processes of measuring outcomes. Her work in iRadar helps to simplify complex data issue; deploying Artificial Intelligence (Ai) based solutions to collect, automate and analyse result based data for policy decision.