Viewport.ai’s Radboud Grijpma explains how proper data management can optimise terminal efficiency
In the tank storage business, working with the right documents and data is very important. Searching for data and documents can be frustrating for employees. Finding wrong versions or outdated versions, not finding documents at all, or spending too much time on work preparation are clear examples that can be frustrating. Plus, making decisions based on wrong or incomplete data can result in longer project times, higher costs and even to incidents.
How Are Companies Dealing With Data Availability?
Experienced employees have found their way in a variety of systems and have found nifty ways to combine data and find what they are looking for. But for, the average employee, finding information can be a source of frustration.
Some companies are implementing a state-of-the art document management system (DMS). These systems store documents in a centralised location. Oftentimes this means getting rid of older document management systems, shared drives or folders on computers and laptops of employees. When implementing a DMS it’s also a good idea to add meta data (authors, date, keywords) and tags to categorise and label documents.
Implementing a document management system requires a culture change to let employees comply with all the new rules that apply to structuring data. Adding metadata to documents can be a lengthy exercise. It’s also challenging to make sure that the mess that has been created with having a multitude of versions of a document will end up in the new source system as just one or a few relevant versions. Migrating to one new system might impose security risks and there is a strong need to manage access that used to be in place when the original source systems were in use. In practice, migrating to a new DMS can oftentimes lead to disappointing results.
DMS vs Digital Twin
Companies with even more ambition like to work on the concept of a digital twin. A digital twin is the digital representation of an asset like a whole tank storage facility. This can be a 3D scan of the actual site, exposing real time data that could give a lot of insights and even insights for things like predictive maintenance. Although the concept of a digital twin is very promising, it does not solve certain issues. Employees need to work with existing source systems and documents to manage today’s processes. Although the scope of the output of a digital twin may expand over time, the output is not sufficient to help employees with their task today. It is very hard to get to a level of quality data. The high quality of data is essential to live up to the promise of getting the value of a digital twin. Also the implementation of a digital twin is a complex process that can take many years. Plus, the technology involved in creating a digital twin can be very costly.
A Digital Solution
Wouldn’t it be nice if there was a solution that can help create one view of all the data and documents available in the underlying source systems about an asset? A solution that doesn’t require any changes to your existing landscape of applications that you have? Viewport.ai has a variety of customers in the oil and gas industry that use its solutions. With Viewport.ai you can help employees today with finding documents without having to think where they are, find different versions in maybe different source systems, get alerts on missing data or documents. With this information the employee can work faster, prevent issues and contribute to a better quality of data. Plus, insights that can be used to create a successful DMS or be used to improve data quality for digital initiatives like a digital twin.
