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Learn About Quality

Quality 4.0

Quality Glossary Definition: Quality 4.0

Also called: Industry 4.0, digital transformation

Technological advances of the past decade have resulted in a new industrial revolution often referred to as the fourth industrial revolution or "Industry 4.0." It’s a revolution driven by the exponential growth of disruptive technologies and the changes those technologies are bringing to the workplace, the workforce, and the markets organizations serve.

"Quality 4.0" is a term that references the future of quality and organizational excellence within the context of Industry 4.0 needs and performance expectations. Quality professionals can play a vital role in leading their organizations to apply proven quality disciplines to new, digital, and disruptive technologies.

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Establishing and Implementing Quality 4.0 Principles

To achieve excellence through quality is to embrace the future of quality. It is paramount that quality professionals help their organizations make the vital connection between quality excellence and their ability to thrive in disruption, using quality principles to enable transformation and growth with digital tools.


Quality 4.0 is more than technology. It’s a new way for quality professionals to manage quality with the digital tools available today and understanding how to apply them and achieve excellence through quality. By speaking the digital language and making the case for quality to more effectively handle disruption, quality professionals can elevate their role from enforcers to navigators to successfully guide organizations through digital disruption and toward excellence.


As more work is automated, the need for flawless processes remains the same, if not more important. Existing processes will be broken and the need to educate the next generation of workers to implement new processes and strategies is vital not only to the quality professional, but also business operations. Quality is a vital link and should be included at the strategic level for sustainability during digital transformation.


Technology is growing 10 times faster than it used to, and organizations’ platforms, such as processes, systems, data, operations, and governance, must keep pace. Technology also is a great leveler because it gives any individual with the right idea and intent the capabilities previously available only to large organizations. Quality professionals must move from data analyst roles to data wrangler roles to elevated data management roles by engaging with new technologies, understanding how technologic advancements create various outputs, and determining how and when to use them.

Quality 4.0 Tools

Deploying an organization’s digital strategy won’t be without challenges to overcome. There are common challenges that cut across all industries and digital maturity levels, and others that are specific to an organization. In addition to the timeless and well-known quality tools and principles, the Quality 4.0 tools below should be leveraged to alleviate these challenges when implementing and deploying systems to support digital transformation.

  • Artificial intelligence: visual recognition, language processing, chatbots, personal assistants, navigation, robotics, making complex decisions.
  • Big data: infrastructure (such as MapReduce, Hadoop, Hive, and NoSQL databases), access to data sources, tools for managing and analyzing large data sets without having to use supercomputers.
  • Blockchain: increasing transparency and auditability of transactions (for assets and information), monitoring conditions so transactions don’t occur unless quality objectives are met.
  • Deep learning: image classification, complex pattern recognition, time series forecasting, text generation, creating sound and art, creating fictitious video from real video, adjusting images based on heuristics (make a frowning person in a photo appear to smile, for example).
  • Enabling technologies: affordable sensors and actuators, cloud computing, open-source software, augmented reality (AR), mixed reality, virtual reality (VR), data streaming (such as Kafka and Storm), 5G networks, IPv6, Internet of Things (IoT).
  • Machine learning: text analysis, recommendation systems, spam filters, fraud detection, classifying objects into groups, forecasting.
  • Data science: the practice of bringing together heterogeneous data sets for making predictions, performing classifications, finding patterns in large data sets, reducing large sets of observations to most significant predictors, applying sound traditional techniques (such as visualization, inference, and simulation) to generate viable models and solutions.

Figure 2: The Ecosystem of Quality 4.0 Tools
The Ecosystem of Quality 4.0 Tools

Quality 4.0 Value Propositions

New technology should always be introduced with a clear articulation of the desired benefits it will deliver and impact to the overall organization’s operations and performance. Value propositions for Quality 4.0 initiatives fall into six categories, listed in order of significance:

  1. Augment (or improve upon) human intelligence.
  2. Increase the speed and quality of decision making.
  3. Improve transparency, traceability, and auditability.
  4. Anticipate changes, reveal biases, and adapt to new circumstances and knowledge.
  5. Evolve relationships, organizational boundaries, and concept of trust to reveal opportunities for continuous improvement and new business models.
  6. Learn how to learn by cultivating self awareness and other awareness as skills.

Quality professionals are perfectly positioned to propose and lead digital transformation initiatives because they have deep skills in:

  • Systems thinking
  • Data-driven decision making
  • Leadership for organizational learning
  • Establishing processes for continuous improvement
  • Understanding how decisions affect people: lives, relationships, communities, well-being, health, and society in general

ASQE Quality 4.0 Research

Across all nine of the Insights on Excellence® (IoE) categories—Operations, Voice of the Customer, Workforce, Leadership, Strategy, Technology, Measurements & Results, Barriers & Disruptors, and Environmental, Social and Governance (ESG) practices—ASQE explores the trends, emerging priorities, and shifts in performance to help identify where you and your colleagues can focus your efforts to achieve positive change.

In the Technology section of the 2023 ASQE IoE Category Report, it’s clear that companies have had to get serious about digital transformation roadmaps, and understanding how quickly technology changes. But there remains a need for organizations to fully understand the return on investment and productivity increases or declines that technology provides, especially as it relates to their workforce’s skill sets and operational needs. The following graphs from the IoE Category Report show the year over year trends in which research respondents are either adopting or adapting with digital transformation:
ASQE LAQ IoE Technology data
ASQE LAQ IoE Technology data

By focusing on the degree to which a company has embraced technology, implements effective change management to update and adapt with technology, and how related investment has impacted operational performance, this can provide an even deeper understanding for continuous improvement.

Visit the IoE Research page for the collection of published research focused on real-world insights from global companies to continue engaging with the data.

The Evolution of Quality 4.0

To understand the future of quality, it’s important to understand the roots of quality’s evolution in conjunction with industrial revolutions. During the first industrial revolution in the late 1700s and early 1800s (Industry 1.0), innovations in steam and waterpower made it possible for production facilities to scale up, expand potential production locations away from main waterways, and transport goods farther and more frequently. Increased output was achieved using crude machines for faster, more consistent work versus independent craft work. In Quality 1.0, quality of goods was assured through measurement and inspection, but inspection did not focus on cost reduction, eliminating wastes, or loss and inefficiency. Production volume was emphasized rather than quality, and work conditions or safety were not yet important, only the maximization of worker productivity.

From 1890-1940, the second industrial revolution (Industry 2.0), the discovery of electricity and development of infrastructure enabled engineers to build machinery for mass production, and the application of these new mechanisms enable performance capability gains. Quality 2.0 saw a continued primary focus on maximizing productivity, with labor performance as the main measurement. Adherence to standards that reflect the minimally acceptable quality level was also still prevalent, and financial quality was measured based on scrap and rework.

The third industrial revolution (Industry 3.0) occurred toward the end of World War II—around the time when ASQ (then ASQC) was formed—to the late 1990s, starting with digital computing emerging from its analog roots, first with mainframes, then client-server computing and PCs, followed by the advent of the internet and early e-commerce sites. With the invention of the programmable logic controller at the end of the 1960s, this made it possible to automate processes, such as filling and reloading tanks, turning engines on and off, and controlling sequences of events based on the state of the process and changing environmental conditions. During this time (Quality 3.0), quality and continuous improvement were business imperatives and meeting customer requirements was emphasized. Productivity gains occurred by stabilizing highly efficient processes, standardizing work, and involving all workers in the activities that create quality. Standardization activities (like ISO 9001) and achieving business excellence through organization-wide assessments like the Baldrige Criteria for Performance Excellence emerge.

The fourth industrial revolution (Industry 4.0), which we are currently in, is focused on integrating cyber and physical interfaces, robust connectivity, automating processes with end-to-end systems, machine learning, and artificial intelligence. Quality 4.0 sees quality shift its control-oriented focus from the process operators to the process designers, as machines learn how to self-regulate and manage their own productivity and quality. Human performance is still essential though, with the emphasis shifting from production to system design and integration with the business system.

For a complete chart of industrial advances and the evolution of Quality 4.0, and what it may look like in 20 years, download this article from Quality Progress.

Quality 4.0 Resources

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