Data gets results
It's a numbers game
A clear divide emerges in our research between the product innovators who describe their current product data strategy as “limited” (47%) and those who say theirs is “advanced” (53%): the advanced organizations are outperforming the limited organizations.
Organizations with advanced data strategies outperform across every metric
Chart shows product innovators who say their organization’s performance in these areas has improved over the past 12 months
To understand the differences between advanced and limited organizations, we asked product innovators the extent to which they are able to use product data strategically to perform different functions.
We found that, while companies with advanced strategies do a better job capitalizing on their product data than those with limited strategies, even they are not using it to its full potential.
Only 29% say they are fully capable of using manufacturing data to improve manufacturing processes
Only 24% are combining their engineering, manufacturing, and in-use data to gain advanced insights
And 74% still are not using product data to implement digital twins
Organizations with advanced data strategies use strategic insights to improve their product lifecycles—but they still have work to do
Chart shows organizations that can use data strategically to a full extent for different purposes
Connected data gives the bigger picture
For all the advantages it offers, data alone is not enough.
Product data and analytics are most effective when they are seamlessly integrated across the whole product lifecycle. That means companies must use all data at their disposal to improve product or product-related processes—extracting maximum value from insights and making testing more efficient and more effective at identifying key issues that affect quality and performance.
52% of companies with an integrated company-wide product data strategy experienced faster time-to-market in the last 12 months
Compared to 33% of companies without this advantage
Yet the fact remains that less than one-third of those with an advanced data strategy are combining the full extent of their engineering, manufacturing, and in-use data to gain advanced insights. And 37% point to an inability to gain insights via data analytics as a barrier to product lifecycle improvement.
Even within companies that are making good progress in their product data journeys, there is more to be done.
Our big focus is the digital twin space—being able to become more of a streamlined organization in terms of fully linked data throughout the whole lifecycle. That means everything from the initial requirements through to simulation data, to refine our designs before we even start to cut metal or have parts created.
Eric Schickler
Engineering Section Manager, Northrop Grumman
Tap into the test data goldmine
Organizations both limited and advanced are underutilizing the product data they currently have to reduce the time and cost required to bring ever more complex products to market.
Our research identifies test data as the most underutilized resource, revealing that many organizations are struggling with inadequate data analysis and testing bottlenecks. One-third say that an inability to integrate or gain insights from test data prevents them from improving their product lifecycle.
38% say they rarely use test data to inform product design
52% say the way they capture, store, and manage test data prevents them from extracting meaningful insights
51% say they could extract more value from their test data if they started testing earlier in the product lifecycle
The product revolution doesn’t just need test—it runs on it. Test data is the result of the lifecycle processes. When combined with design, simulation, process, and other critical product data sources, it gives an end-to-end lifecycle view that offers more impactful product analysis.
As innovators face ever-growing product complexity, they need detailed insights into their products and how they are behaving. The answers often lie in test data, but all too often, this valuable asset and source of vital insight is not used to its full potential.
We know that, in many industries, there is a natural lag between design and test phases, which can cause production bottlenecks. But overlooking test data could cause you to miss out on an opportunity to streamline your processes. In today’s competitive market, this could be the difference between success and failure.
Test is a last-minute thought, without a doubt. Everybody thinks test is easy. But there's an art to testing that you don't always deal with when you're doing the design side of things, because we have to be more precise than the units we're investigating. That doesn't always resonate with the people who are creating the new products we're testing.
Eric Schickler
Engineering Section Manager, Northrop Grumman
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Data gets results
It's a numbers game
A clear divide emerges in our research between the product innovators who describe their current product data strategy as “limited” (47%) and those who say theirs is “advanced” (53%): the advanced organizations are outperforming the limited organizations.
Organizations with advanced data strategies outperform across every metric
Chart shows product innovators who say their organization’s performance in these areas has improved over the past 12 months
To understand the differences between advanced and limited organizations, we asked product innovators the extent to which they are able to use product data strategically to perform different functions.
We found that, while companies with advanced strategies do a better job capitalizing on their product data than those with limited strategies, even they are not using it to its full potential.
Only 29% say they are fully capable of using manufacturing data to improve manufacturing processes
Only 24% are combining their engineering, manufacturing, and in-use data to gain advanced insights
And 74% still are not using product data to implement digital twins
Organizations with advanced data strategies use strategic insights to improve their product lifecycles—but they still have work to do
Chart shows organizations that can use data strategically to a full extent for different purposes
Connected data gives the bigger picture
For all the advantages it offers, data alone is not enough.
Product data and analytics are most effective when they are seamlessly integrated across the whole product lifecycle. That means companies must use all data at their disposal to improve product or product-related processes—extracting maximum value from insights and making testing more efficient and more effective at identifying key issues that affect quality and performance.
52% of companies with an integrated company-wide product data strategy experienced faster time-to-market in the last 12 months
Compared to 33% of companies without this advantage
Yet the fact remains that less than one-third of those with an advanced data strategy are combining the full extent of their engineering, manufacturing, and in-use data to gain advanced insights. And 37% point to an inability to gain insights via data analytics as a barrier to product lifecycle improvement.
Even within companies that are making good progress in their product data journeys, there is more to be done.
Our big focus is the digital twin space—being able to become more of a streamlined organization in terms of fully linked data throughout the whole lifecycle. That means everything from the initial requirements through to simulation data, to refine our designs before we even start to cut metal or have parts created.
Eric Schickler
Engineering Section Manager, Northrop Grumman
Tap into the test data goldmine
Organizations both limited and advanced are underutilizing the product data they currently have to reduce the time and cost required to bring ever more complex products to market.
Our research identifies test data as the most underutilized resource, revealing that many organizations are struggling with inadequate data analysis and testing bottlenecks. One-third say that an inability to integrate or gain insights from test data prevents them from improving their product lifecycle.
38% say they rarely use test data to inform product design
52% say the way they capture, store, and manage test data prevents them from extracting meaningful insights
51% say they could extract more value from their test data if they started testing earlier in the product lifecycle
The product revolution doesn’t just need test—it runs on it. Test data is the result of the lifecycle processes. When combined with design, simulation, process, and other critical product data sources, it gives an end-to-end lifecycle view that offers more impactful product analysis.
As innovators face ever-growing product complexity, they need detailed insights into their products and how they are behaving. The answers often lie in test data, but all too often, this valuable asset and source of vital insight is not used to its full potential.
We know that, in many industries, there is a natural lag between design and test phases, which can cause production bottlenecks. But overlooking test data could cause you to miss out on an opportunity to streamline your processes. In today’s competitive market, this could be the difference between success and failure.
Test is a last-minute thought, without a doubt. Everybody thinks test is easy. But there's an art to testing that you don't always deal with when you're doing the design side of things, because we have to be more precise than the units we're investigating. That doesn't always resonate with the people who are creating the new products we're testing.
Eric Schickler
Engineering Section Manager, Northrop Grumman
SHARE THIS
