Manufacturing and asset maintenance: The brave new world of data driven continuous improvement

Many of the businesses that I deal with consider data to be an asset. Most large organisations have C-level roles with overall responsibility for data. Chief data officers and chief information officers have responsibility for maintaining the balance between data governance and data analytics. By this I mean they must secure and manage the data whilst also gleaning insights from it to drive decision making across their business.

You can see that lots of the big names of the digital era have built their success on their clever collection and use of data. Google, Amazon, Facebook – they recognised the value of data from the start and have used it to keep their customers engaged and their advertisers keen to spend money on their sites.

But these are typically B2C businesses, with huge amounts of behavioural data that helps them understand their customers better. To compete in today’s markets, they cannot afford to take a one-size-fits-all approach to customer management. We have all come to expect personalised treatment and will walk away from businesses that fail to treat us as valued individuals.

B2B businesses, such as manufacturers and physical asset operators, have been a little slower to recognise data as an enterprisewide asset. Real value comes from data when you can start integrating disparate data sources. This gives you much broader insight into how to manage your operations and assets.

I think that this is essentially what is meant by Industry 4.0 and “digital twins.” A digital twin is simply data you integrate to understand and model performance of your assets and processes.

Historically, analysts working in physical-asset-rich organisations have struggled to get their hands on data or have not had the tools to effectively analyse all their data. Spreadsheets have often driven their information world. Another challenge has been the integration of many proprietary data sources to be able to get the big picture. Although equipment may have sensors that collect useful data, quite often these have used different networks, systems and communications protocols. This has made it really difficult to glue the data together in a timely fashion.

But that world is changing. And in my data-centric universe, I see two key trends that are helping those in manufacturing and asset management start to harness their data to reduce maintenance costs and improve output quality.

Sensor data can tell you a lot about your assets and production processes. But this data has often been collected on isolated networks into specialist applications. This makes it hard to access.

This is changing.