How to Use Data to Streamline Manufacturing Operations
The COVID pandemic has disrupted businesses and operations globally. It has also delivered a powerful reminder that and industries, together with their eco-systems, are of huge importance to the global economy.
Prior to COVID-19, many people in developed countries believed that digital connectivity had us covered. What the pandemic has demonstrated repeatedly, is when simple necessities like toilet paper, soap, handwash, canned foods were rushed off the shelves in panic buying, collectively the world realised how critical having resilient supply chains is to everyday life.
The acceleration of data analytics technologies that automate, increase efficiencies and performance of , cloud computing analytics and predictive can, and will be greatly beneficial.
But not if they aren’t fully integrated into your existing .
don’t cut it any more. Harnessing the power of the data from your systems is becoming more and more critical for any who is looking to streamline their and gain a competitive edge. Big data is defined by large volumes of data that flood a business on a day-to-day basis.
Manufacturers are under renewed pressure to optimise any so they can lower costs. Analysing big data with an helps manufacturers collect key analytics and insights that lead to smarter business decisions, and better profitability. Big data is ultimately about making better use of the operational data within a organisation.
Use Product Development and Improvements to Anticipate Customer Demands
Manufacturers can mine data they already have to help identify future customer demands and use those insights for product development and improvements. Anticipating , while challenging, is more important than ever.
Big data can help transform valuable operational data into actionable insights for new product developments and improve existing products. By mining data that they already have, manufacturers can identify customer needs that they might not otherwise have captured.
Provide a Better Experience for Customers
Innovative manufacturers are using big data to collect, analyse and act on information to improve data from R&D, engineering, and units, can reduce time to market and improve the quality of their products. and experience. Customer experience is becoming a significant focus area for manufacturers who are for a competitive edge. Manufacturers who incorporate
If the can make faster, more perceptive projections about and behaviours and adjust their accordingly. wants to keep the customers they have and attract new ones, they need to identify the individual needs of each customer. With the ability to collect and analyse all their operational data in realtime,
Enhance Fraud and Compliance Monitoring and Reporting
Evolving security landscapes and compliance requirements have meant manufacturers need to ensure their data remains secure at all times. The Financial Cost of Fraud 2018 report found that fraud is costing the world economy nearly $6 trillion (AUD) every year. With big data, manufacturers can identify patterns in their data that could indicate fraud is occurring and streamline the collection of large quantities of information to make regulatory reporting much easier.
Big data allows compliance teams to data in real-time to recognise and address any risks before they become harmful to the company.
Fraudulent billing is one of the biggest issues manufacturers face and can have a major impact on their bottom line. As manufacturers continue to operate on tight margins big data can help protect those margins by identifying suspicious activities like:
- inflated invoices
- invoices for personal purchases
- invoices submitted for fictitious goods or services
Boost Operational Efficiency and Supply Chain Management
It’s not a hot topic but is an area in which big data has a huge impact. Manufacturers can analyse and assess , customer orders and other factors to reduce downtime, improve and anticipate future demand by harnessing the power of big data.
Suppliers are also looking to take advantage of the benefits of big data by sharing their own data with manufacturers to provide more transparency, improve communication and lift within the . With more visibility into quality levels and performance data, manufacturers can evaluate, manage and negotiate risk management issues. For example, a can identify delays and respond appropriately to reduce waiting times and the flow on effect of those delays.
Implement Predictive Maintenance
Countless secrets lie within data collection that can significantly improve the lives of manufacturers everywhere.
information that helps predict mechanical failures is buried deep with the mountain of operational data and includes data such as equipment model details, log entries, sensor data and error messages. By examining this type of data, manufacturers can identify potential issues before they arise and deploy more cost-effectively to where it’s needed the most.
Increasingly turning to predictive algorithms that are based on machine learning capabilities and analytics, manufacturers accurately identify potential failures long before catastrophe strikes. Sensors on a piece of equipment can gather just about any information that is required and store it for analysis.
Not only can big data analytics help determine the best time to carry out , it can help identify the right time for to occur based on demand.
Drive Value Creation and Innovation
For manufacturers all over the world, methods for processing and analysing these large volumes of data (big data) are an essential resource for driving value creation, fostering new products, , and markets, as well as enabling the creation of new knowledge (OECD 2014). Manufacturers can drive value creation and innovation in their company by utilising predictive analytics coupled with big data, to produce insights into every aspect of their business and identify new processes for adopting and maximising these insights.
Insights gathered through big data analysis can be used to improve , financial decision-making and planning, examine customer trends and introduce dynamic pricing. The possibilities are endless.
Big data has the potential to create a single source of truth within a that drives innovation, protects margins and improves customer relationships. Successful manufacturers who streamline processes will be the ones that can adapt and move faster than their competitors using big data to give them the insights they need to make the right call.
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