Diagnostic Supply Chain Analytics and Performance of Large Manufacturing Firms in Kenya

Purpose: This study investigates the influence of diagnostic analytics on the performance of large manufacturing firms in Kenya, focusing on spend root-cause analysis, logistics analytical processing, and capacity planning what-if queries. Methodology: The study adopted a mixed-methods research design. Mixed-methods research design integrates both qualitative and quantitative research approaches in the processes of data collection, analysis, and presentation. The target population for this study was 461 large manufacturing firms. Data was collected from a sample of 210 respondents out of a sample of 222, representing a (94.5%) response rate. Instrument reliability and validity were confirmed through Cronbach's alpha (> 0.70), KMO, and Bartlett's tests. Results: Findings indicate moderate to widespread adoption of diagnostic analytics, with logistics analytical processing most prevalent. Approximately 45.7% of respondents rated diagnostic analytics as effective. Regression results reveal a positive, statistically significant relationship between diagnostic analytics and firm performance (R = 0.680, R² = 0.462, β = 0.718, p < 0.001), explaining 46.2% of performance variation. Unique Contribution to Theory, Policy and Practice: The study examines the application of diagnostic, prescriptive; this sstudy underscores a critical realization: operational performance is fundamentally contingent upon the sophistication and integration of an organization's analytical framework. Policy makers and regulatory agencies must mandate that firms establish rigorous guidelines for the selection and utilization of analytic tools. Regulatory bodies should mandate that firms implement comprehensive spend root-cause analysis and logistics analytical processing. The study establishes that sustainable performance is contingent upon the synergistic application of the four analytical pillars, which should be institutionalized as follows: Diagnostic analytics: deploying rigorous root-cause analysis to identify and rectify inefficiencies in logistics and procurement workflows.