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Even as global macro trends continue to challenge the way of doing business, companies are not fully leveraging data to optimize their manufacturing processes. A new survey from NIE (National Instruments) reveals that as many as 47% of companies operate with a limited data strategy – using product data from just a handful of functional areas.
According to the questionnaire, involving 300 product innovators from a variety of industries, most of these organizations do not leverage manufacturing and engineering data and deliver business outcomes as impactful as those with an advanced enterprise-wide product data strategy. In the past 12 months, only 33% of the parties saw a faster time to market, compared to 52% of the advanced companies. Levels of innovation (51% vs. 63%), employee productivity (50% vs. 62%) and production efficiency (41% vs. 58%) were also lower.
The metrics are important because they show how effective unlocking data from the entire product lifecycle — design, validation, manufacturing and deployment — can be for refining processes and delivering breakthrough products. This is the need of the hour in today’s market landscape, where organizations must continue to deliver cutting-edge products at speed and scale to remain competitive.
Gaps in Advanced Strategy
While companies with advanced product strategies have achieved better results, even they don’t make the most of product data. The NI survey found that only 29% of companies with advanced data strategies used manufacturing data to improve manufacturing processes, and 24% combined the full scope of their engineering, manufacturing and in-use data to gain advanced insights. Many also signaled the inability to gain insights through data analysis and underutilization of test data to inform product design.
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“We know that in many industries there is a natural delay between design and testing phases, which can lead to production bottlenecks. But if you overlook test data, you could miss an opportunity to streamline your processes. In today’s competitive market, this can be the difference between success and failure,” the research report reads.
Organizations catching up
By addressing these gaps, organizations are now catching up to address their data gaps and transform the product lifecycle.
In the past 12 months, 70% of organizations with limited data strategies have prioritized product data and analytics. Meanwhile, the advanced players, who have already laid the groundwork, now want to prioritize advanced technologies such as machine learning, digital twins and robotic process automation (RPA).
“Effective maturation in product data strategy involves planning the set of steps that best address specific problems. Start by identifying the challenges that need solutions today, then the tools needed for those solutions can be obtained. From there, shape the data strategy to support those tools,” NI colleague Mike Santori told VentureBeat.
“For many enterprises, product-centric data will be an important part of the data strategy, providing the granularity needed for the required analytics. That plan needs to be centralized and standardized across the enterprise so that all efforts come together to create a connected (advanced) data strategy for the entire company,” he added.
In the survey, 65% of respondents emphasized that a data strategy is essential for optimizing the product lifecycle. Meanwhile, 46% said they will lose market share within two years if legacy product lifecycle processes are not optimized.
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