3 Ways to Unlock the Value of Data in Manufacturing

Shaping the Future of Advanced Manufacturing with the World Economic Forum

A recent BCG survey of more than 1,300 manufacturing execs found that 72% of manufacturing companies consider advanced analytics to be more important now compared to three years ago. In the same survey, 91% consider data sharing to be at least somewhat important, and 71% think it has significant importance. The applications for data sharing and analytics in this space are vast. You’ll hear about predictive asset maintenance, improved product and raw material traceability, improving the reliability of deliveries, and so on. All of these initiatives revolve around 3 themes:

Speaking of lead times, manufacturers are also using data to enable “just-in-time” delivery of critical goods. This application is especially common in the area of medical goods or perishables. Here, real-time tracking and tracing of critical materials prevents stock-outs and improves availability. Original Equipment Manufacturers are doing something similar to secure critical components. Long lead times can be a very big problem for OEMs trying to secure parts for service, maintenance and repair.

An appliance manufacturer, for instance, works with us to secure critical components for customer service. Instead of overstocking these components, they order just the right amount to deliver a timely service. The result? Higher customer satisfaction, better product reviews, and more sales — with no tied up working capital.

A similar situation occurs with parts that have high demand unpredictability. Traditionally, purchasing managers would respond to this situation by overstocking. Now, they can stop worrying about predicting the future, and can simply get parts when they need them, in smaller quantities. This prevents unnecessary logistics in the short-term, and waste in the long run.

As mentioned in the Forum’s report, there are some challenges that often get in the way of analytics efforts. These are typically insufficient skills, data security risks, complex internal governance and processes, and roles and responsibilities that are not clearly defined. We would definitely agree that change management is a common challenge.

We’ve successfully solved this challenge in cooperation with our customers, based on a mapped out strategy and a crystal clear set of objectives and deliverables. What we’ve realized is that there are different phases in this journey to unlock the value of data. These phases are:

In a number of cases, we’ve worked first on accuracy and data quality. With other clients, we managed to present insights that were hard to get on the table until now. The most advanced stage of capturing value from data is what we’ve developed and worked on with many of our customers: new metrics and actionable insights driving supply chain optimization.

We managed to build actionable insights combining data from traditional manufacturing and additive manufacturing, and enriched this with deep supply chain insights. This allows our customers to make decisions which contribute immediately to increased productivity, enhanced customer experience, and a positive impact on society and the environment.

Sharing data with partners is also crucial, as supply chains operate in networks that are increasingly more vast and interconnected. To facilitate safe data exchange, consider using a cloud-based platform that supports real-time data sharing across your ecosystem in a secure way. For example, companies that use our platform are able to connect to the world’s best manufacturing facilities, going from data to parts delivered in a secure and controlled workflow.

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