• Victor Genin

The Secrets Of Successful Cross-Departmental Collaboration



Imagine an industrial company, for instance, a mining company before the Internet. Those underground had no reliable methods of communicating with the people above ground, and operators had no simple method of sending data to the business and engineering teams. Basic communication was extraordinarily complicated, and this, in turn, led to significant lapses in efficiency, safety, and sustainability.


Now, everything is different. There has truly never been a better time to be part of an industrial company: whereas in the past, getting members of different departments to work together was almost as difficult as the industrial processes themselves, today it can happen seamlessly.


The kind of cross-departmental collaboration that modern technology allows for is far more advanced than a simple video conference or document-sharing platform. Thanks to industrial AI knowledge and IoT technology, departments can work together better than they could if they were sitting in the same room.


One major way in which modern technology is allowing for more efficient cross-departmental collaboration is by collecting and uploading data in real-time using industrial IoT. While it used to be necessary to manually record equipment data, type it into a computer, and then send it to whoever required access, nowadays not only can this entire process occur automatically, it also collects data that is more accurate and precise than before. This means that supervisors, operators, and remote experts can look at the same data and make adjustments in real-time, ensuring that operations are always running at peak levels.


However, IoT is far from the only technology allowing organizations to grow more interconnected. Industrial AI knowledge is also playing a major role in improving cross-departmental collaboration. Using the same data collected by industrial IoT, AI-powered algorithms are capable of providing recommendations to operators in order to optimise production. Remote experts can, in turn, review these recommendations and tweak them as they see fit, with the AI knowledge taking this remote expert feedback into account in the future. This means that when operators implement AI-generated scenarios and produce measurable results, remote experts can now review this data and change the scenarios accordingly. Not only is company data being used to make improvements over time, but people from all parts of the organization are able to make changes to ensure that production is consistent with company goals and expertise.


This is not to mention the increased ability of corporate teams at industrial organizations to stay informed about what is happening in the field and make decisions accordingly. For example, if AI knowledge uses predictive maintenance to warn a staff member that a machine is about to break down, someone responsible for the company budget can easily consider when it makes the most sense to fix it. Anyone within an organization can now have a fully transparent view of the entire operation, allowing for more effective decision-making than ever before.


The recent developments that have occurred in cross-departmental collaboration will undoubtedly make industrial organizations more efficient and profitable. As markets across the world grow more competitive and mining becomes more of international business, collaboration between departments located worldwide will separate the companies that grow from those that are overtaken. And as industrial AI and IoT technology continue to advance at an astounding rate, the number of benefits companies who embrace them will see will only continue to grow.

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