Why Jabil Is Reining In Tool Sprawl Before Scaling AI Across 100 Factories
The global manufacturing giant is dismantling 25 years of custom technical debt to establish a unified data backbone for predictive automation.
Key highlights · 2 min read
- Global manufacturing contractor Jabil is overhauling its fragmented enterprise software footprint across more than 100 worldwide facilities, betting that standardizing basic data flows must take pr…
- Speaking on the Business Lab podcast hosted by MIT Technology Review, Harish Manohar, SAP IT director at Jabil, detailed how the company is adopting a "simplify-first, then-innovate" mandate.
- "Any innovation without simplification is going to add more complexity," Manohar said, arguing that deploying modern applications on top of fragmented legacy stacks creates operational blind spots.
The Scale ReportGlobal manufacturing contractor Jabil is overhauling its fragmented enterprise software footprint across more than 100 worldwide facilities, betting that standardizing basic data flows must take priority over flashy artificial intelligence rollouts.
Speaking on the Business Lab podcast hosted by MIT Technology Review, Harish Manohar, SAP IT director at Jabil, detailed how the company is adopting a "simplify-first, then-innovate" mandate. The Florida-headquartered company, which employs over 140,000 people across more than 30 countries and manufactures goods for over 400 global brands, is working to dismantle roughly 25 years of accumulated technical debt caused by site-specific tools, bespoke customizations, and spreadsheet workarounds.
"Any innovation without simplification is going to add more complexity," Manohar said, arguing that deploying modern applications on top of fragmented legacy stacks creates operational blind spots. "The backbone of any contemporary or modern organization is data," he added, noting that data must move cleanly across regions before plants can benefit from automation.
To standardize operations, Jabil is consolidating its IT architecture around SAP's Business Technology Platform and Integration Suite, while leveraging SAP Signavio to map consistent process templates across an initial target of 40-plus plants. The group is shifting toward an API-driven, event-based model and adopting SAP's RISE framework to enforce a "clean-core" architecture that strictly limits local site customizations.
The Cost of Moving Fast Without Structure
The initiative reflects a broader reckoning across industrial supply chains. Enterprise leaders face immense pressure to deploy predictive analytics and autonomous systems, yet advanced algorithms reliably fail or propagate mistakes when fed siloed, conflicting plant data. By treating process discipline and system consolidation as prerequisites for machine learning, manufacturers can avoid costly pilot projects that fail in production.
At Jabil, integrating workflows is already yielding tangible results, including faster detection of missing assembly materials and less manual reconciliation for procurement and finance staff. Manohar noted that the unified foundation will serve as the launchpad for predictive supply chain tracking, intelligent exception handling, and automated forecasting.
"Simplicity at scale is a very competitive advantage," Manohar said, emphasizing that IT modernizations must be anchored to verifiable business performance rather than technology upgrades for their own sake.
Reporting based on coverage from Artificial intelligence – MIT Technology Review.




