Strategic Agility and Sustainable Performance of Manufacturing Firms in Nakuru County, Kenya

Strategic agility is the capacity of a firm to sense changes in its operating environment, anticipate alternative futures and reconfigure its resources and operations in good time. It has become a critical capability for manufacturing firms, which operate in an increasingly uncertain environment characterised by economic instability, supply chain disruptions, climate variability and rising production costs. In Nakuru County, Kenya, many manufacturing firms still respond to such disruptions reactively, and evidence on how agility practices relate to their ability to sustain performance remains limited. Therefore, the purpose of this study was to examine the influence of strategic agility on sustainable performance of manufacturing firms in Nakuru County, Kenya. It explored four practices, namely environmental scanning, scenario planning, strategic flexibility and early warning systems. The study was anchored on Dynamic Capabilities Theory, Complexity Theory, the Resource-Based View and Organizational Learning Theory. The study adopted a descriptive and explanatory research design and targeted the 34 manufacturing firms in the county. A census of the firms was undertaken and four managers, comprising senior, operations and strategy managers, were purposively selected from each firm, giving 136 respondents, of whom 96 returned completed questionnaires. Structured questionnaires were used to collect data. Both descriptive and inferential statistical methods were used to analyse the data, which were presented in tables and discussed. The findings revealed that the four practices jointly explained 43.9% of the variation in sustainable performance. Environmental scanning was the strongest predictor of sustainable performance, followed by scenario planning and early warning systems, while strategic flexibility had a significant but comparatively weaker influence. The study, therefore, recommends that manufacturing firms institutionalise environmental scanning, regularly develop and review alternative scenarios, strengthen decision-making and resource reallocation mechanisms, and integrate predictive risk monitoring, clear reporting channels and predefined response thresholds into their early warning systems.