For LNG and petrochemical companies, a robust data foundation is not an end in itself. Rather, it is a beginning point for many transformative initiatives. A solid data foundation is essential as it acts as a springboard for a large number of digital transformation activities. As the possible usages and applications of data increase in number and nuance, companies will have to have a data preparation strategy in place to prepare their data for the next-gen digital transformation initiatives. 

It is common to build data for short term needs such as preparing a functional Bill of Material or creating a basic repository of assets. While this data may serve its intended purpose, it may not be suitable for future initiatives. If data is not built with long term goals in mind, companies may need to repeatedly rebuild  the same data, which can result in unreliable information, duplicates, and other issues. 

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In this article, we will be talking about some simple considerations one should be aware of when building asset and maintenance data. If incorporated, these considerations will ensure that your data is ready not just for your immediate needs but also long-term initiatives that harness the data. 

Build data as per recognized standards: For the LNG and petrochemical industry, a large number of standards are already in place for building data repositories. Before beginning any data building activity, studying these standards, selecting appropriate ones and developing a template accordingly will immensely help. Let it be a Bill of Material or an Asset Master, one can always refer to existing standards. Data standardization is also equally important especially when the data is being created and maintained by multiple facilities/user groups. 

Set up robust data quality checks and processes: Implement data quality checks and validation processes to ensure that when data is created, it is free of any discrepancies and inconsistencies. It is much easier to prevent these discrepancies from creeping into the data in the first place rather than eliminating them later on. 

Keep your data system agnostic: Often, companies build their data for a particular software or ERP system. In such cases, the data becomes absolutely unusable when it needs to be migrated to other software or ERP systems. In the fast changing world of softwares and solutions, this is one mistake companies should avoid at any cost. Try to build your data in a holistic and comprehensive manner so that it can be easily transformed for other systems. 

Incorporate solid data governance: When many people work on the same data, keeping track of changes and maintaining truthfulness of the data becomes challenging.  Establish clear data governance policies and procedures to ensure data quality, consistency, and security. It also helps to define roles and responsibilities for data management, including data stewards who are responsible for overseeing data quality and integrity.

Scalability: A task seems  easy during its infancy but can  become unmanageable when it scales. The quantum of data that LNG and petrochemical companies would need will grow exponentially. Therefore, it is imprortant to design data preparation processes with scalability in mind to handle growing data volumes as operations expand.

Metadata management: A very simple thing that companies often miss is proper usage of metadata. Metadata can be used to document and track the origin, meaning, and usage of data. Ensure that metadata is kept up-to-date as data sources and structures evolve.

Following these five simple steps will ensure that data that you create once will be usable for your future initiatives provided it is updated periodically. Reach out to us to know more about data building best practices. 

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