CASE STUDY
The biggest impact has been speed to market and flexibility.
SnapLogic also supports Elida’ s data fabric and analytics strategy. Near-real-time operational information is delivered to cloud platforms used for forecasting, inventory visibility, trade promotion management and executive reporting. The governed flow creates what the companies describe as an AI-ready foundation for intelligent automation and agentic workflows.
Nick Pike, Vice President for EMEA, SnapLogic, said Elida’ s project showed that corporate separation, modernisation and scaling could be pursued simultaneously. Making integration central to the digital core had converted a potentially complex disentanglement into a streamlined architecture, he said, while the unified data layer gave the business greater agility.
With its core systems operating independently, Elida is moving from foundational work towards simplification and automation. It aims to reduce manual processing while retaining a clean, lowcode architecture that can respond to changing commercial demands without accumulating another generation of technical complexity.
The company is now examining how SnapLogic’ s agentic capabilities could identify issues earlier, improve exception handling and automate processes including supplier onboarding. The intended result is not simply more automation, but fewer occasions when employees must chase information across disconnected systems before making operational decisions.
Bates said employees were not asked to buy into the technology itself. The programme was presented in terms of outcomes: completing the separation quickly, lowering development costs and adapting to changing requirements without rewriting thousands of lines of code. Confidence grew once teams saw the Pace developers identify problems and make changes to established pipelines within minutes.
“ The biggest impact has been speed to market and flexibility,” Bates said.“ Using SnapLogic, a relatively lean team was able to deploy integrations from fairly loose initial requirements and then evolve them as the business took shape.”
Future capacity was considered during the initial design. According to Peach, the integration layer can handle higher data volumes, support additional automation and introduce new capabilities without requiring fundamental re-architecture. It was also structured to protect security, performance and operational stability as more intelligent, AI-driven workflows are introduced.
For Elida, separation was therefore a starting point rather than the project’ s final objective. The company now has a platform through which it can simplify core processes and extend automation across its international operation. Its exploration of AI agents is focused on allowing teams to spend less time locating and reconciling data and more time managing brands, partners and supply chain performance.
That flexibility is becoming increasingly important as consumer markets change. •
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