By Cindy Maike, Vice President of Business and Product Solutions at Cloudera.
Ongoing margin pressures, shifting trade patterns and supply chain uncertainty mean that manufacturers are always looking to make their operations more efficient. Data and analytics are increasingly a catalyst driving change.
Data holds the key to finding efficiencies and optimising processes that manufacturers are looking for, with a broad range of use cases. However, this is only possible if manufacturers have the capabilities to utilize the data available to them.
Predictive downtime reduction
One area where data can help to improve manufacturers’ margins is within factories. Sensors and other assembly line equipment produce vast amounts of data. Much of this data is overlooked or discarded if it doesn’t help to solve an immediate problem. But, when aggregated and analysed over time, this data holds significant potential for operational cost reduction.
Here, predictive or condition-based maintenance can anticipate the likelihood of failures in machinery. Manufacturers can use historical data about equipment performance in two ways: firstly, using sensor data to monitor for indications of future equipment faults, such as excessive vibration or heat. And secondly, looking across past or similar situations to pinpoint when equipment is in perfect health and doesn’t need scheduled maintenance, therefore reducing unnecessary intervention. By combining data from thousands of machines and sensors, manufacturers can predict machine downtime, which costs huge amounts of money, and take action.
Customer-centric data benefits
Predictive analytics can also be used to improve customer service once products are out the door, helping to strengthen a manufacturer’s bonds with customers. For example, manufacturers of factory equipment can use insights to predict future failures and alert customers early so they can apply preventive maintenance. On top of this, software updates delivered automatically can also save buyers of cars, security cameras, and other smart devices from having to make time-consuming trips to solve issues.
Enhancing safety protocols and compliance
Another use case for data helping to optimise manufacturers’ operations is safety and compliance. This is a huge concern for manufacturers, particularly in industries like pharmaceuticals and food. Here, the stakes are high, as undetected quality issues not only threaten public health but also carry substantial regulatory penalties.
Pharmaceutical manufacturers must have the right security, governance, and data lineage tracking to take a drug to market. Here, accurate and reliable data can help ensure the safety, efficacy and quality of products. But this also extends across the entire spectrum of operations – from R&D and clinical trials to yield optimisation. By combining their own data with other unstructured and structured sources, pharmaceutical companies can derive fresh clinical insights, which not only bolster operational efficiency but also enrich clinical reporting.
Additionally, sensors – such as smart thermometers – have become invaluable tools for monitoring product status and quality throughout the supply chain for food producers. These sensors enable manufacturers to gather data in real time, which they can leverage to safeguard their products from exposure to hazardous temperature conditions. However, many businesses are still grappling with the optimal way to harness and integrate the abundance of data generated by sensors. To be truly effective, organizations must combine sensor data with their existing enterprise data sources – like ERP and supply chain systems. This enables food producers to proactively identify potential security and compliance issues. In the pursuit of safety and compliance, data plays a pivotal role.
Unifying data
These innovations are only possible if analytics tools are able to access the full data set. In today’s complex landscape, that might mean both structured and unstructured data, which resides in both on-premises data centres or in the cloud – possibly even across multiple cloud environments. In fact, our recent research shows that 74% of manufacturers across EMEA store data across both cloud and on-premises, with 81% of these working with at least two hyperscalers. But concerningly, 77% of manufacturing data leaders say this makes extracting value from their data more complex. It’s this complexity in extracting value that is leaving manufacturers unable to deploy innovations such as predictive maintenance or enhancing safety and compliance.
Manufacturers need to unify their data on a single platform that enables them to drive value from their data, no matter what format it comes in or where it resides. Without this, they’ll be unable to unlock the full potential of their data.
Unlocking new value
Data provides the foundations for understanding supply chains and increasing margins. Combined with analytics, these insights can enable manufacturers to take a more proactive approach that’ll not only improve their own operations, but their customers’ too.
In today’s increasingly competitive manufacturing landscape, these fine margins could be the difference between success and failure. By unifying data, manufacturers can differentiate themselves from competitors and thrive.
