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How to eliminate data silos in the process industry

Having immediate access to up-to-date asset data is crucial to a fully optimized plant process. Let’s say the inspection team found something suspicious in a pipe. This information must be made available to the engineering team to replace the pipe, the operations team to find a temporary alternate pipeline to move production and planning to know which of the assets are available to use for customers. In most cases however, sharing this crucial information is more difficult than it sounds.

With this situation in mind, and all data that is being generated on a daily basis, it’s scary to think that most organizations in the process industry are subconsciously working with departmental data silos. Their asset data are stored in different software applications like a CMMS or EAM system, or in local excel files and reports. They are only available within the departments that created the data.


Data silos_s


You can imagine that these data silos will cause problems. The first problem is time; it takes time to request data from other departments that do not share your priority. Secondly, as there is no access to the same data source, an export or copy is created to share the necessary data.

The problem becomes a real issue when one of the departments starts making changes to the data which are not shared with others. The copy or export floating around the other departments is suddenly outdated without them knowing it. If you do not eliminate your data silos, it will continue to dictate your daily activities with outdated data. This will not only increase the number of mistakes you make but also money spent on solving errors or delayed operations.


Solution: data-centric approach to integrate your data sources

To solve the problem of departmental data silos, you must adapt a data-centric approach to manage your asset data. It relies on using a shared data model, which is an architecture to integrate all data generated by all software applications in an organization, ensuring your asset data are always available.

If we apply this concept to the process industry, the best approach to structure the data model is by basing it on the physical layout of the assets of your plant site and using the unique asset location of each asset to identify and locate it. Any new data generated will be referenced back to this asset location to be stored in accordance with the data model.

Storing your asset data in this structured way permits the use of independent applications. As long as there is a reference to a unique asset location, a connection can be made with the data. Simply put: using a data-centric approach ensures that all essential asset data are stored in a consistent way, making it possible for everything and everyone to use these data.


Data silos_s


How the data-centric approach eliminates data silos

The following are two elements of the data-centric approach that can help you eliminate the data silos completely:

1. All data are shared
As mentioned earlier, the data model allows different applications to tap into the same data.
Even if there are multiple systems used to generate data from different departments, they will all be stored and shared in one common database. This makes it easier for one department to have instant access to the most up-to-date asset data created by another.

2. All data are synchronized
Now that all asset data are integrated and synchronized, when changes are made, any outdated data will be flagged. This notifies others in the organization to make proper edits to ensure that all asset information in the database remains as-built.


Data silos are a real problem in the process industry, but the solution is available. The time to eliminate them is now, as more and more data are being generated. Instead of letting them pile up in one silo, we must make optimal use of the data by making them available company-wide at anytime and anywhere. Adopting a data-centric approach is the only way to effectively futureproof the management of your asset data.


User Case Study  - Heinen & Hopman

Connecting with asset data at sea:

  • Various EAM systems and standards merged into one standardized and shared source of information.
  • Asset data legacies and deltas interlinked throughout the database for quick updates on all asset statuses.
  • Instant access to every asset information on all on-the-move global vessels.


Download Case Study


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Heinen & Hopman wanted a software solution that could provide them with the necessary tools to access and manage asset information, all from one shared database.