Manufacturing executives recognise advanced analytics as critical to the future of the sector. Yet few companies are capturing the full value from them today, according to research from the World Economic Forum and Boston Consulting Group.

In a new joint whitepaper, they argue in the near future manufacturing companies will work together in “hyper-connected value networks” where advanced analytics will be a prerequisite.

But few companies are anywhere near that today, according to the research based on a survey of 1,300 manufacturing executives.

Less than one in five of the surveyed participants had prioritised advanced analytics to promote either short-term cost reductions or longer-term structural cost improvements. And only 39 per cent have managed to scale data-driven use cases beyond the production process of a single product.

In other words, manufacturing companies know advanced analytics will be critical but most can’t even demonstrate the business case today.

The World Economic Forum has established a platform for collaboration on advanced manufacturing and production and is asking stakeholders to contribute to a new manufacturing data excellence Framework.

A hyperconnected data-driven revolution

The future of manufacturing is autonomous processes where smart assets generate troves of data for artificial intelligence to analyse, according to the BCG report.

“These applications will make complex networks more transparent for companies and enhance collaboration across corporate boundaries.”

While some companies will still be able to run manufacturing applications with internal data, many of the more sophisticated apps will require data from beyond corporate boundaries, according to the analysts.

For example, while something like asset maintenance can be achieved with a data platform and internal sources of information, something more advanced like predicting equipment failures relies on machine learning and huge data sets.

“Such models need to be trained by a large amount of data,” the report explains. “Companies can rarely provide this data alone, so they must share data with other asset operators.” 

An example of improved product quality and reliability based on in‑service data. Source: Data Excellence: Transforming manufacturing and supply systems.

Sharing data also brings benefits of transparency and supply chain optimisation.

Manufacturing impediments

According to the report, several manufacturing companies are already implementing such advanced use cases of data sharing and analytics, but they remain the exception, not the rule.

Those surveyed in the sector reported the following five top challenges to scaling and implementing data and analytics solutions:

  • Insufficient skills and capabilities (26 per cent of executives surveyed)
  • Data‑security risks (24 per cent)
  • Lack of effective applications to process and make sense of data (22 per cent)
  • Complex internal governance and processes (22 per cent)
  • Roles and responsibilities not clearly defined (20 per cent)

The solution, according to the analysts, is to establish a clear data‑to‑value strategy and roadmap, incentivise partners, build internal and external capabilities, use open platforms to avoid silos, connect applications with low‑latency, high‑bandwidth data transfers, and ensure strong privacy and security protections.

“Manufacturing is on the verge of a data‑driven revolution,” says Daniel Küpper, BCG managing director and partner and a report coauthor. 

“But many companies have become disillusioned because they lack the technological backbone required to effectively scale data-and-analytics applications. Establishing these prerequisites will be critical to success in the post-pandemic world.”

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