ElectrifAi | Identified $50M – 100M potential annual savings for a top-tier global coffee chain through predictive and prescriptive maintenance using IoT data

Food & Beverages

Identified $50M – 100M potential annual savings for a top-tier global coffee chain through predictive and prescriptive maintenance using IoT data

Key Challenges

A top-tier global chain of coffeehouses wanted predictive maintenance to improve uptime and enhance customer experience. The volume and complexity of IoT data from thousands of stores with different types and age of equipment rendered predictive maintenance insights nearly unattainable. The client also wanted to explore new use cases with IoT data that could enhance their business operations and create new monetization avenues.

Our Products in Action

The product leveraged historical log and issue data to predict maintenance issues and prevent unexpected service interruptions. It also helped in analyzing IoT data for new anomalies and issues (some potentially due to operator errors), thus mitigating expensive repairs or replacements. The product will support new equipment and emerging use cases and offers the flexibility of deploying on-premises or via the cloud.

Business Impact

$50M

savings identified in the first year with the possibility of $100M if all equipment were included

94%

precision on a narrow observation window with a recall rate of 26%

Enhanced CX with near-zero downtime to help maintain and grow brand reputation

$50M

savings identified in the first year with the possibility of $100M if all equipment were included

94%

precision on a narrow observation window with a recall rate of 26%

Enhanced CX with near-zero downtime to help maintain and grow brand reputation

Identified $50M – 100M potential annual savings for a top-tier global coffee chain through predictive and prescriptive maintenance using IoT data

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