Adoption Of Big Data Analytics For Supply Chain Performance In Saudi Arabia’s Private Hospitals: A TOE–SCOR Synthesis

Abstract

Background: Private hospitals in the Kingdom of Saudi Arabia (KSA) face persistent supply chain challenges—stockouts, expiry losses, and long replenishment cycles—despite accelerating digital transformation. Big Data Analytics (BDA) can strengthen planning, sourcing, delivery, and returns; however, adoption pathways and performance effects remain fragmented across studies.

Objective: To develop a practical framework for BDA adoption in healthcare supply chains in KSA by synthesizing determinants using the Technology–Organization–Environment (TOE) lens and mapping value mechanisms onto SCOR processes.

Methods: We conducted a narrative synthesis of peer-reviewed and policy/industry literature (2013–2025); determinants were coded to TOE domains, and mechanisms were mapped to SCOR (Plan–Source–Make–Deliver–Return).

Results: Relative advantage and compatibility emerged as the strongest technological drivers; top-management support and organizational readiness (including skills, data, and integration) were decisive organizational drivers; competitive pressure, group purchasing, unified procurement mechanisms, and supportive national policy acted as environmental catalysts. Illustrative mechanisms included improved demand forecasting (Plan), supplier scoring and traceability (Source), compounding data integrity (Make), cold-chain exception management (Deliver), and recall/returns analytics (Return).

Conclusions: We propose a staged roadmap for KSA private hospitals: (1) foundational readiness and master data quality, (2) pilots in forecasting and supplier scorecards, (3) Deliver scale-up with cold-chain IoT and exception management, and (4) enterprise rollout with ROI governance. This approach aligns with national initiatives and can reduce stockouts and waste while improving service levels [1–8].