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From the raw materials to investment, logistics and of course, the final product, manufacturing is an intricate process with many moving parts. Besides the non-tangible aspects of the manufacturing industry, there are financial and managerial aspects to oversee, not to mention a perpetually changing consumer demand and aggressive competition. However, in spite of all these complexities, there is a constant generation of data reflecting the manufacturing process. datapine’s manufacturing analytics software allows the nuances of this data to be harnessed and translated it into meaningful information that can then be used to improve all aspects of the process, at any scale.

"datapine gives us all the insights we need in a compact space. Thanks to datapine we are able to review all relevant customer data and react on trends and opportunities much faster."

Kai Hansen


In the manufacturing industry, there are simply too many moving parts, both literally and figuratively. Advanced manufacturing analytics can be applied for a more comprehensive and robust decision making process.

  • Enhance process efficiency and improve final product safety
  • Don’t miss any relevant information at any production stage
  • Gain a competitive edge by predicting future market trends
  • Maintain a profound consumer base and ensure its satisfaction
  • Analyze and optimize your product inventory management
If you can visualize it, you can manage it.

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Manufacturing analytics is all about manipulating raw data gathered from existing manufacturing processes and translating it into actionable information. This information can later be used to improve and modify all dimensions of existing processes, in order to maximize profit margins, manage logistics and improve product efficiency, quality or safety. Manufacturing business intelligence software helps you to develop industry-specific forecasts and to translate demand signals to allow for the most appropriate and cost-effective response. It will ultimately improve existing processes and dominate the competition. There are hundreds of moving parts in the manufacturing industry and thousands of steps to monitor. Data can be easily lost and important decisions neglected without the help of clear objectives, systematically driven methods of gathering and studying existing data. A business analytics software like datapine takes every piece of information and merges them to create a top-down overview of manufacturing processes that could not have been completed if only relying on manpower alone.

Learn how the Internet of Things and advanced analytics are revolutionizing the manufacturing industry.

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Why is manufacturing analytics software important?

Raw materials being more expensive, harder to source, and a growing need to streamline operations: manufacturers are facing many transformations in their industry that lead them to find new ways to boost their productivity and profitability. Like many others, the manufacturing industry has dealt with disruptive changes over the past decade, and is still in an in-between situation of adaptation. Globalization, vertical integration or margin pressure are some of the many business challenges that force manufacturers to find new innovative ways to improve their decision-making, so as to perform better.

Historically, the manufacturing sector has been a slow-changer, especially in integrating innovative IT solution. That is partly due to the fact their “IT” infrastructures were developed before the cloud was born, or before the inexpensive storage of data and the omnipresent connectivity were easily accessible. But the disruption forced the manufacturing industry to adopt new ways of working, and it is now catching up with the use of modern manufacturing analytics, applying it to different areas of the industry – from product development to finance and supply chain.

The impact of modern Manufacturing Analytics

The manufacturing revolution, generated a century ago with the invention of the assembly line, is still going on: automated processes and mechanization enabled by the information technologies provide the sector with an incredible amount of data that most company don’t exactly know what to do with. This is where business intelligence steps in, and helps you connect the dots: by gathering all your data sources in one single point of truth, you are able to analyze them conjointly, and to visualize trends and patterns in the data that wouldn’t have been otherwise possible. Besides, these cross-database analyses yield valuable information for manufacturers to improve their processes, by saving costs, improving the quality and the safety, improving the workforce efficiency, enhancing collaboration, and generally increasing the productivity.

At datapine, we believe that manufacturing analytics can bring an incredible change to the way processes, logistics, or product quality are managed. We want to ease the access to your data, and provide you with the manufacturing business intelligence software you need for advanced analytics. Decode complex manufacturing processes and improve their operability, optimize maintenance costs, calibrate time reduction, assess risk and failure, implement root cause analysis, and detect anomalies: all of these insights are within your data, and you just need the right tools to uncover them.

Don’t focus exclusively on your production process

Products are usually the core of any manufacturing business, so when it comes to implementing analytics, they naturally are oriented towards product development. But it is not restricted to this area, and supply chain optimization or financial management overall improvement are also in the frontline of change. Whichever you decide to choose, focus your analytics on one targeted business area to produce better results, even if the launch of an enterprise-wide analytics initiative can be tempting – such strategy is much riskier, time-consuming, and expensive. Direct your attention on specific business questions that you need to answer to glean actionable insights that can have a major impact on your performance.

The use of manufacturing analytics can also enable new revenue models designed around selling services and not only improving the production process. Focus on some business issues, how to address them, and implement the right metrics to measure advancement in the project. With the business objectives set, develop your strategy that complies with the priorities pre-fixed, and assess the results after a certain time. Depending on your findings and what you learn, adjust the strategy or reinforce the measures in place.


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