I often like to say data is like water. The reason for this is that it is constantly flowing, you cannot survive without access to it, and it is constantly being used, cleaned, and recycled. Dirty water, however, is largely unusable – left to stagnate in water tanks or storage, it is quickly forgotten about and thrown away. But when we treat that water with care and make sure it is clean, we allow for the reallocation and consistent use and re-use of it in very different ways in everyday life.
Data is exactly the same. If businesses do not have the right data, which is accessible, clean secure and consistent, AI projects will not survive.
Proof of AI’s increasing integration was highlighted in McKinsey’s 2022 State of AI report. It showed that AI adoption has more than doubled since 2017, with 50% of organisations saying they now use AI in at least one business area.
With innovation at the centre of projects, AI is being increasingly adopted in industries such as retail and utilities. However, AI is having the biggest impact within the manufacturing industry.
AI-based products such as Machine Learning (ML) and Deep Learning (DL) are facilitating smart factories that can optimise increasingly complex, multi-stage processes. These tools are enabling them to become more sustainable, efficient and cost-effective.
But the big question for businesses looking to integrate AI into their manufacturing processes are: where do I start? And how do I ensure clean data is at the heart of the process?
Build a solid foundation for data security
The essential pillar of a high-performing AI solutions in manufacturing is secure and clean data. This is because of the long-standing dependence on out-dated legacy systems which have meant that data storage has dropped down the priority list.
Thankfully, we’re starting to see the beginning of a mindset shift due to digitalisation of the manufacturing industry. CIOs within the industry now understand the importance of not just collecting and inputting data, but storing it in a safe and clean way, especially when it comes to storing industry leading secrets or people’s data.
By prioritising the belief that data needs to be cleaned, and stored in a safe and secure way will enable businesses to plan and deliver successful AI-powered project.
Data and AI as enablers
Currently, data scientists lose around 80% of their working hours on collecting, clearing, and detecting defective data – instead of creating actionable insights. As many leaders in within the manufacturing industry know, how you choose to approach your data management can make or break a project.
Like water, clean data is essential. When it comes to training AI algorithms using un-clean data can be detrimental. However, ensuring the data used is clean can allow businesses to make accurate predictions around priorities across a manufacturing plant, such as breakdowns or machine downtime. Better data hygiene helps businesses seamlessly integrate information into existing software programs. Then they can deploy AI to automate the process – driving better efficiency and productivity.
Success of AI projects in manufacturing of course rests on the quality and quantity of the data it processes – the better the data, the better the results.
Integrate AI into your business operations
When implementing any technology tools into your tech stack, they should bring strategic value and add to the day-to-day functioning of your business. It’s no different for AI.
When looking to bring AI capabilities into your business, leaders should consider what is needed, the costs, challenges and any limitations. But bringing the right partner on board to advise on your AI strategy, should have a immediate, cheaper and more sophisticated impact.
Across manufacturing, AI integration might look like introducing intelligent machine maintenance, improving the efficiency of quality control, becoming more agile with supply chain management or increasing AI-powered automation for running better processes.
Leaders need to ensure they’re leading from the top and showing their employees that these tools are useful in order to ensure the success of the deployment. Implementing sometimes complex technology can be dauting but ensuring your people understand it and are able to use it to their best ability is vital. Leaders need to focus on investing in training so the whole business can embrace the innovation.
As many business leaders across the manufacturing industry know, AI provides a huge competitive advantage – only if it’s set up and used in the right way. Starting with the right data set – which is clean and secure – is essential. Truly transforming a business’ approach to data and technology will prove AI’s potential.
About the author
Kirsty Biddiscombe, UK Head for AI, ML & Analytics at NetApp
She plays a crucial role in driving successful engagement in Artificial Intelligence, Machine Learning, and Data Analytics, supporting organisations to achieve their business objectives around their AI presence. Her expertise in datacentre solution experience, outcome-based engagement, and the wider IT industry are driving NetApp’s transformation, and positioning the company as a leading provider of cutting-edge cloud data solutions.
