Implement your organization's data strategy
Be a data-driven organization with Acentrik.
0
%
of organizations lack an enterprise data strategy to fully capitalize on their data assets.
Accenture
Maximize the value of your data chain
In today’s data-driven landscape, a strong data strategy is essential for organizations to leverage the most out of their data value chain. Organizations who are focusing on the tail-end of the chain by embracing data exchange platforms, thrive more than others.
Central to executing this strategy is the ability to effectively analyze and share data.
Acentrik being the integral part to an organizations’ data strategy, helps unlock greater value from data with privacy-preserving features that enable secure data exchanges, while ensuring full data privacy.
Why Acentrik?
Our platform’s architecture is designed to connect directly to existing data infrastructures, enabling interoperability.
Driving Smart Maintenance for Automotive Manufacturers
Case Study
Predictive maintenance can increase labor productivity by up to 20% and reduce inventory levels and carrying costs by up to 10-30%.
Deloitte, 2022
Deloitte, 2022
Business benefits
Maximizing equipment efficiency and lifespan through data-driven predictive maintenance.
Enhanced labor productivity: Optimizing maintenance schedules and reducing downtime, allowing maintenance teams to focus on preventative measures rather than reactive fixes.
Inventory optimization: Accurately predicting when parts and materials are needed, thus streamlining inventory management and reducing excess stock and associated costs.
Enhanced labor productivity: Optimizing maintenance schedules and reducing downtime, allowing maintenance teams to focus on preventative measures rather than reactive fixes.
Inventory optimization: Accurately predicting when parts and materials are needed, thus streamlining inventory management and reducing excess stock and associated costs.
Our impact
Secure computation at source
Computation of equipment sensor data across data hubs, while keeping data at source. This optimizes maintenance schedules and enhances labor productivity without compromising data privacy.
Data aggregation across silos
Aggregation of maintenance data across markets in APAC and EU without moving data. This provides greater predictive insights in cost efficiencies and inventory forecasting.
Greater cross-region data sharing across data hubs
Data hub A
Equipment operation data
Data hub B
Maintenance history data
Data hub C
Sensor feedback data
Data hub D
Environment data
Unified data platform - Connecting global data hubs
Use case 1
Downtime reduction planning
Use case 2
Resource allocation optimization
Use case 3
Equipment lifestyle management
Greater cross-region data sharing across data hubs
Different data hubs
Equipment operation data, Maintenance history data, Sensor feedback data, Environment data
Unified data platform - Connecting global data hubs
Various use cases
Downtime reduction planning, resource allocation optimization, equipment lifestyle management
Start your data journey today
