Disruption to existing processes

For many manufacturers, leveraging data-driven decision making and automating processes can come with some disruption. It is a transformation that needs to be driven from the core outwards, but it can leave many manufacturers confused as to what they should do with the existing systems and how to integrate the new ones into their infrastructure. In order to prevent this from occurring, it is fundamental to prepare for the shift by assessing the value of your projects before embarking on a digital transformation. By conducting short sprints of activity to establish a plan of action, you can mitigate potential risks in the development and adapt them to your new solution. This can ensure a smoother transition for your solutions and benefit your employees as they will be then able to establish a level of familiarity with the features of the legacy systems that have been transferred to your latest solution.

Adapting to changes in organisational infrastructure

Routines and standardised ways of working are what make employees comfortable at work, which can make it difficult for them to adapt to changes in company culture and infrastructure. Uncertainty is usually the catalyst for pushback when it comes to changes, and this can definitely be the case during a digital transformation. Having said that, digital transformation is vital to ensuring the progression of your manufacturing organisation, as it will help your business stay current with a competitive edge over non-adopters.

Analysing data

At this stage, manufacturers have realised the benefits of going digital, especially when it comes to the efficiency that IoT devices and machines can bring to manufacturing processes. These devices can aid organisations in gathering data that can help them boost efficiency, improve productivity, and optimise workflow across the whole infrastructure.


By considering the challenge they are trying to solve or metrics they are trying to influence, manufacturers can leverage data science and advanced analytics to move from a reactive operations, repairing and replacing components to predicting events and fixing the component or machine.



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The Data Analysis Bureau

The Data Analysis Bureau

We are a Data Science and Data Engineering Innovation Agency specialising in Machine Learning.