In today’s industrial scenario, analytics programs are seen as an important pillar and key enabler of not just Quality 4.0 but several other Industrial Transformation (IX) programs. As part of our Quality 4.0 research, LNS Research is seeing that quality teams, just like other functional teams pursuing industrial analytics, are only finding small pockets of success that often stagnate after some initial momentum - falling short of the dramatic step change benefits promised by analytics solution vendors, system integrators, and management consultants.
Our recent Analytics That Matter study confirms 58% of companies are deploying industrial analytics solutions but only 11% have realized the promised dramatic business impacts
. While there are several reasons we find accountable for this disparity, the one reason that is most pertinent to Quality 4.0 is data management.
In this Research Spotlight,
we provide some of our recent research on Quality 4.0 and industrial analytics, and explore:
- The shift in Industrial Analytics from a "Low-Hanging Fruit" focus to more complex "hard-benefit" use cases.
- Challenges resulting from common Quality Data Management Practices with recommendations on how to overcome them.
- How building an Industrial Data Hub strategy can help Quality 4.0 teams pursue the complex hard-benefit use cases by addressing data management challenges.
Most importantly, this report provides actionable insights for Quality leaders on how a data hub approach helps companies bring the plethora of quality data together to overcome existing challenges, enabling leaders to be able to pursue sophisticated Quality 4.0 use cases and maximize returns on investment.
Download the full research report below.