People Analytics and Performance of Deposit-Taking Micro Finance Institutions in Nyeri County, Kenya

People analytics is a data-driven approach to improving people-related decisions for advancing both individual and organizational success. While people have always been critical to the success of organizations, many business leaders still make key decisions about their workforce based on intuition, experience, advice, and guesswork. However, today leaders can improve their people decision-making based on the collection and systematic analysis of data. A closer look at the operations of many deposit taking micro-finance institutions reveals that they all face challenges related to human resources management. These firms invest in human development, only for the human capital to leave for greener pastures within a short period, impacting negatively and heavily on performance, survival and growth. It is therefore imperative that they undertake serious human resource evaluation, and people analytics can be a crucial tool for the success of this process. The aim of the study was thus to evaluate the effect of people analytics on the performance of Deposit Taking Micro Finance Institutions in Nyeri County, Kenya. The specific objectives guiding the study were: to determine the influence of technology adoption on the performance of deposit taking micro-finance institutions, effect of human resource data access on the performance of deposit taking micro-finance institutions, effect of data management capacity on the performance of deposit taking micro-finance institutions, and the effect of stewardship for people analytics on the performance of deposit taking micro-finance institutions in Nyeri County, Kenya. The study adopted the descriptive research design while targeting173 respondents comprising 8 human resource managers and 165 staff in the human resource department of 8 registered deposit taking micro-finance institutions in Nyeri County. Through stratified sampling method, all managers (8) and 30% (50) of the 165 staff comprised the sample size of 58 respondents. The selected respondents were considered key informants in the study area. Data was collected from primary sources using a semi-structured questionnaire. Data was analyzed with the aid of Statistical Package for Social Studies and excel computer software through descriptive (percentages, means, standard deviation), as well as inferential statistical methods (correlation and regression techniques). Tables and graphs were used for data presentation. Results showed that the micro finance institutions had established infrastructure for the application of technology. Descriptive and inferential analysis results indicated that technology adoption, human resource data access, data management and stewardship had a positive relationship with the performance of MFIs. Findings further indicated that out of the four independent variables, only three were significant: human resource data access, data management and stewardship. The study thus concluded that HR data access, data management and stewardship aspects of people analytics had significant effect on the performance of Microfinance Institutions. Technology adoption lowly affected people analytics and performance of micro finance institutions. To enhance data access and management, the study recommended that managers need to invest in new apps that are platforms for people analytics including cloud computing and artificial intelligence. They must also re-evaluate the techniques for human resource anaytics  as well as capacity development in people analytics for managers and staff.