When talking about building an intelligent enterprise, you hear words like IoT, smart devices, digital transformation. In reality, it's usually taking “dumb” infrastructure and making things “smarter,” by adding technologies like sensors, transmitters, digital meters and so on, without actually changing the infrastructure itself.
But even the smartest technology is not useful if it cannot help predict assets’ maintenance needs, reliability, and how they should function in conjunction with other equipment. That means that master data loaded into any system of record as a digital representation of those physical assets needs to be reliable, real-time and integrated across every system that maintains a digital twin of that asset.
Challenges Resulting from Poor Asset Master Data Quality
- Inadequate preventive maintenance, protracted maintenance schedules and poor visibility into an asset’s lifecycle
- Operational inefficiencies, leading to high inventory and operations costs and increased downtime from equipment failure
- Process disruptions which require more manual rework and lead to decreased asset utilization
- Safety issues caused by equipment failure and poor product quality.
- Greater risk of non-compliance, which creates legal liability and raises the specter of regulatory crackdown
- Higher IT costs due to integration of disparate information sources; inaccurate IT resource planning; and business inflexibility
Data is Key for IoT
In the simplest terms, EAM-focused data governance solutions get data clean and keep it clean across all systems of record. It enforces structure for the data entering the system in a standardized manner, ensuring consistency with how the data is entered according to prescribed taxonomies and rules. The cleansed data is then replicated across every other system and integrated into all workflows, allowing an organization to make complex changes in a unified fashion that all are supported be the assurance of high-quality master data.
Additionally, when someone makes a change to an asset in the physical world, the asset’s digital twin is immediately updated and made consistent, and vice versa – across an entire ecosystem in real time. The data stays clean and consistent across multiple organizations and for countless assets.
To connect what Gartner calls “systems of record” – “dumb” infrastructure (equipment, buildings and assets) with “systems of innovation” (sensors, chips, transmitters, etc.) providing automation and analytics, the integrity of the underlying asset master data driving the smart technology is critical.
Organization's cannot recognize ROI from their investment in smart technologies without governing the master data behind them effectively.
What is your asset master data strategy for your IoT initiatives?