Quality is Not Just Fixing Defects in the Digital Era

This article explores the new meaning of Quality against the backdrop of today’s organizational culture, shorter product lifecycles, user expectations, and processes.

“Growth and comfort do not go hand in hand”: The challenges, financial and administrative struggles, and covid-19 have affected all organizations in 2020. To survive and flourish, firms of all sizes, whether compliant or disruptive have embraced digital technologies, by using remote access, working from home, collaborating in teams and serving customers virtually. Even traditional power and utility companies have fully benefited from online collaboration. Productivity has not suffered, instead, managers have seen productivity increases, very much to their surprise. New trust has been built between teams, between managers and employees, and customers.

As we progress through 2021, Covid-19 hopefully will subside, but the digital working trend will continue to grow uninterrupted. The speed of digital transformation is accelerating beyond working from home. Regardless of the industry and the market segment a company serves, product innovation cycle is reduced to months and weeks, from what used to be years. The “Cycles and Speed of Business Value Creation” graph shows how technology has reduced product cycle time from idea to the mark. This is explained in the “x-axis” of the graph.

A second pattern, described on the “y” axis of the graph, evolves from creating products based on more traditional and easily measurable techniques, using hard features and functions, to creating a subjective soft experience that is individually felt and based on time and place. In creating a new need, or filling a product gap, companies are observed to be following Maslow’s hierarchy of human needs: After the basic human needs for food, shelter, clothes, and security are satisfied, a person moves on to addressing the next levels of abstract needs, such as relationships, peer recognition, and prestige.

The automotive industry is transforming from building vehicles to offering “Mobility as a Service” and the power and utility industry is moving toward green energy as a service. Industries are placing more emphasis on user experiences and less on selling hard goods and turning their hard goods into smart goods with embedded intelligence.

Peter Weill, from the MIT Center of Information Science Research, at his 2020 “Goodbye Industry, and Hello Domain” talk, presented at the Center’s annual research Summit, sees a gradual disappearance of classical “Industries” and the coming of “Domains”. A Domain is used to describe a unique user experience that spans across multiple industries. Given these trends, a key question is, what QUALITY would mean in the new experience-based era?

This paper discusses the new scope of Quality in the digital era, in the context of

1. Quality culture and mindset
2. Quality processes, and
3. Quality practice and the digital feedback loops.

These three pillars drive a Continuous Quality scope. DevOps is an approach that is proven to help software development to move from the old waterfall into an agile process as companies embrace cloud computing. For software quality, DevOps advocates for continuous quality emphasizing Quality through the lenses of Culture, Process and Practice. Hard goods manufacturers can borrow the DevOps approach to improve their smart product quality and to improve customer satisfaction and retention.        

1.    Quality Culture and Mindset

In contrast to the previous era, in the digital age, quality is everyone’s job, and the customer is the ultimate judge of success or failure. It is also the suppliers and partners’ job beyond the manufacturer’s four walls. To provide enlightening experiences, companies must offer much more compared to what they did yesterday, as “Yesterday’s miracle is tomorrow’s So-what”, stated by Howard Tullman, the founder of Chicago’s 1871. 

There is no place for organizational silos in the 21st Century. Unfortunately, this phenomenon continues to plaque many organizations. To compete in today’s digital market, continuing to operate in the old way will only leave your company behind. Regardless of where a product defect originates, finger pointing won’t solve the problem. Customers don’t care if your defects came from poor design or poor manufacturing, they just leave for the next provider. Accepting responsibility for quality requires courage, integrity, and a change in mindset. Meeting the quality expectations requires developing and fostering an organizational “I Care” mindset.

Prior to 2015, Microsoft was a shrink-wrap software company. The business evolved and its market share and revenue had suffered. A huge cultural transformation took place under new CEO Satya Nadella’s leadership and Microsoft has become one of the most valued companies defined by market cap, customers, employees, and partners.

Digital and cultural transformation contributed to this impressive turnaround.  Communication was Top down. Every employee took training to understand and develop a ‘growth mindset’, which proved to be a key part of Microsoft’s cultural transformation. Growth mindset is reflected and measured on every employee, as: 1) how an employee reuses co-worker’s invention or best practice, and 2) how an employee is helping others to succeed. The old competitive and secrecy culture was replaced by collaboration and encouragement. A mistake or error is treated as an opportunity to grow, and not an evidence to blame.

Some of the Microsoft learnings from its cultural transformation have proven useful for its partners and customers including developing the “I care” attitude to build a Quality First mindset. If every employee keeps that customer in mind, the employee will shift away from internal procedural view (not my job) to exterior customer focus. This renowned focus will foster a more collaborate culture that results in preventative defects prevention.

Quality KPIs must be re-evaluated. In the DevOps culture, a software package’s quality was measured by the number of bugs the testing department fixed. While this might be useful for yesterday’s products where feature and functions were king, in the digital era where experience dominates, measuring the sheer number of bugs is no longer adequate. It is a false assumption that the more bugs the testing department finds, the better the product quality. If we did not create any bugs, there would be no bugs to find. As humans we are prone to make mistakes. We should change our thinking about finding bugs we created to improving the product experience instead. Question should shift to who is creating the bugs? How might we help to improve the situation? A new set of KPIs will need to be identified to encourage everyone to seek ways to eliminate defects, to emphasize quality over features, to advocate teamwork, and to drive awareness that quality is built-in and not tested-out.

Cultural change is needed to drive new thinking. Change is hard and does not take place automatically after a chief product officer sends a company-wide message. Companies should consider applying Prosci’s ADKAR model for change management. ADKAR stands for Awareness, Desire, Knowledge, Ability and Reinforcement. It describes how individuals respond to change and how companies should design and implement a formal change management program considering individuals responses. Most importantly, an organizational culture that uses mistakes and errors as learning opportunities rather than some form of admonishment will make significant gains more rapidly. This resonates with the reinforcement part of the ADKAR model.

2.    Quality Processes

The notion of Quality can easily trigger the thought of manufacturing assembly operations. Commonly accepted measures such as defects by shift, number of scrapes, number of re-works, machine downtime, etc. have served the manufacturing industry well. Cost Of Poor Quality (COPQ) has been used to measure the financial performance on Quality. These metrics continue to be relevant, however, as stated in the early paragraphs, quality is not just the responsibility of the manufacturing operations. It must be understood and analyzed continuously. Even using the term “end to end” to consider Quality is no not sufficient. Manufacturers ought to consider Quality as a continuous value stream.

End to End entails a linear process with a beginning and an ending. In the software domain, the agile DevOps framework does not target a fixed scope and track resources and time against it; rather, it defines a time-period as the constant whereas scope is open. Agile DevOps encourages collaboration and favors quality over delivering a fixed scope. Fixed scope management serves those industries with multi-year contract or product development cycle, it does not fit today’s digital business where scope is fluid. Agile Process has proven to offer higher success rate over its waterfall counterpart. Product manufacturers would benefit from learning the Agile DevOps process. While there is no end to what can be enhanced and improved, there is also no end to what employees can deliver in a fixed-time period. When employees are motivated to deliver quality and collaboration over trying to meet a fixed scope, Quality will ultimately improve.

Poor quality is usually a direct reflection of a company’s broken process. A broken process that is full of friction could mean delayed communication or miss-communication in the workflow between functional groups, such as marketing group, design team, manufacturing operations, and customer service team. Issues in any step in the process can result in poor quality.

It is important to recognize that the cost of fixing quality issues is not the same from step to step. Manufacturers understand when a sheet metal is cut, fixing design issues is costly, compared to catching the error in the design stage. This is the reason automotive companies are moving from road test and lab test to math-based virtual design/build/test process, where options and scenarios trade-offs are analyzed virtually. Focusing on quality as early as possible in the development cycle results in significant savings of time, effort, and money.

In the software industry, It costs 5X if defect is found in the development phase and It costs 30X if defect is found in post product release. Similar pattern exists in the manufacturing industry with a much higher cost penalty. Therefore, concurrent engineering became what everyone did over 25 years ago, serving projects and programs. Today concurrent engineering must evolve into continuous engineering to achieve the desired Quality outcome of customer experience. The moral of the story is to invest in quality earlier in the process and do that continuously. Manufacturers should consider frequent stand-up meetings, weekly sprint planning, customer demo, backlog grooming and after-action reviews, pulling in all stake holders. 

3.    Quality Practice and the Digital Feedback Loops

Having a good culture and a collaborative process are not enough to achieve product excellence; you also need the right digital tools. Product creation is a collective result of people doing work in many processes cohesively. Digital is shaping how products are designed, built, and served. Digital technology is enabling higher levels of automation to enhance productivity and improve quality. The global impact of digital transformation in the manufacturing sector is expected to increase the GDP by upwards of 3.7 trillion US dollars. Technologies like simulation, machine vision and machine learning allow a faster, higher quality product design, build and service. Those not leveraging digital technologies will see a decline in cashflow.

We can digitize the product creation process. Imagine all product creation processes are plotted digitally like an electrical schematic diagram, where input or output conditions with diverse relationships and conditions such as AND, OR, NOR are depicted to represent parallel, serial or wait activities, you will be able to visualize and gain insight on information flow and spot “high impedance segments” that block or delay signal flow. The information schematics is called the Digital Feedback Loop. In a research published by Forester, Faster Software Delivery Will Accelerate Digital Transformation, March 9, 2017 by Diego Lo Giudice, and etc., 84 days were spotted as the wait time, it is the difference between Lead and Process Time, between the Lead Time of 123 days and Process Time of 39 days, The 84 days (123 minus 39) wait time are opportunities for acceleration. Without the Digital Feedback Loop front and center, the 84 days won't be noticed.

Imagine the product creation process is digitally represented to include stand-alone plants and global factory sites, you will have opportunities to automate many manual hand-offs and transaction based on business rules. The Digital Feedback Loop allows manufacturers to recognize frictions therefore be able to integrate siloed product development systems, change management systems, manufacturing execution systems, enterprise resource planning tools, and share product data signal across the enterprise, resulting in a frictionless practice much like the electrical signals in a circuit that keeps our lights on. Signals are enhanced from as-designed to as-build, from as-build to as-serviced, and from as-serviced to the new design. Artificial intelligence (AI), mixed reality, and Industry 4.0 are technology enablers that allow companies to simulate and then operate the business process to optimize design, production, and service scenarios, resulting in product excellence.

Automation tools come in all sizes and shapes. While tools are applied to improve worker efficiency, they can also create more work if one tool’s output in one activity cannot be directly used by another tool in another activity, any translation in between result in more work and increase quality risks. Enhancing product quality thus requires a holistic strategy and an end-to-end view of the entire design, build, and customer care. Connectivity and interoperability are paramount to the success of product excellence. This holistic strategy requires that all departments, internal and external to an organization, must operate on a common data platform to eliminate hand-offs mistakes. If your data is correct, your information extracted from data will be correct, therefore the insight derived from the information will be value-add, instead of wasted effort. Remember the term “garbage in and garbage out”?

Imagine a scenario where a quality issue is predicted based on incoming supply chain parts quality, assembly process deviation, and factory equipment health. Leveraging AI enables this predictive scenario. A highest level of quality maturity is achieved by becoming cognitive. Cognitive quality leveraging AI to mimic three out of the five human senses, such as image recognition for seeing, digital noses for smelling, digital ears for hearing, to proactively detect abnormal operating conditions in the plant. Images and videos are continuously captured, and live feed to the AI models , to detect abnormal view, thus be able to alert on impending issues. Same methodologies can be used to develop AI model for acoustic and smell, to detect abnormal sound (such as water leakage) and abnormal smells (such as the presence of unsafe gases). Cognitive technologies are applied to proactively improve product quality and yield.

In the above examples, a manufacturer can set up cameras above a production line. The video feed is connected to an AI learning platform in a Digital Twin solution, where the images are scanned for discrepancies. When the video records a fault-condition, the system can recognize the fault, interpret the root cause, and develop a recommendation for a fix, which is sent to technicians in an alert. The fault is also logged in the digital record for that component type, where it can be referenced to help inform design or repair decisions in the future.

Connected field service is redefining the way service organizations are managed. Now we can align the right people, resources, and information to optimize the service operation. In the past, technicians would need to scan through pages of technical material to service a component properly. Now they can recognize a faulty asset and pull up the virtual documentation they need automatically. Through the 3D visualizations, a technician can see inside the machine and identify the faulty component without having to take anything apart. As they begin the repair, the solution can provide augmented step-by-step guidance. It can also inform the technician on how their work will impact the device performance based on historical usage data, saving them time and effort. To close the loop, all service actions and contexts are immediately fed to a case reasoning system to allow for faster diagnostics and even product development.

Microsoft Azure has been found to be an enormously useful, comprehensive suite of technologies that drive digital transformation in a Digital Feedback Loop. The breadth of the offering allows manufacturers to choose specific components that can be deployed on the sensors and the edge of the network or in the cloud. Example Azure offerings include: 

• Cloud-based tracking and visibility
• Predictive Quality
• Camera/video analytics
• Temperature sensitive QR Stickers

Summary: Continuous Quality

Building an enduring Quality Culture into an observable Quality Process guided by the strong Quality Practice produces continuous quality. This is achieved by the Digital Feedback Loop. Getting from where you are today to where you aspire to be demands a change: It is a significant paradigm shift to change from traditional quality assurance to a continuous quality. But the benefits are just too high to be ignored. See a comparison of the advantages and disadvantages between the two approaches below:

• Traditional quality assurance is aiming at Breaking the System, whereas Continuous Quality drives for Improving the System
• Traditional quality assurance does so by Checking Functionalities, whereas Continuous Quality promotes System Understanding
• Traditional quality assurance is the responsibility of the testing department during QA stage, whereas Continuous Quality is the entire team's job and done everywhere
• Traditional quality assurance is measured on Finding Issues, whereas Continuous Quality Prevents Issues
• Traditional quality assurance achieves Minimum Quality, whereas Continuous Quality Improves Quality

Recommendation: The 3 Horizons Approach to Quality

The McKinsey 3 Horizons for Growth is a component of a much broader and comprehensive corporate strategy framework helps organizations accelerate innovation to operation. The 3 Horizons Model can be adopted to address the phases of changes leading to Continuous Quality. The 3 Horizons Model for Quality can be re-written as:

• Horizon 1: Extend current quality control to include digital feedback loop capturing quality relevant people, process, and tools data.
• Horizon 2: Extend the scope of quality to address the lifecycle of product process across key functional areas product design, testing, manufacturing, and customer success.
• Horizon 3: Establish a Continuous Quality mentality supported by quality cultural, quality process and quality practices.

Conclusion

As companies evolve from building feature-rich products to a user experience driven offering that is continuously changing, quality management must be re-evaluated under the broader lenses of culture, process, and practices.

Quality management needs to evolve into a continuous quality framework. It is difficult to pull together various processes into Continuous Quality because doing so requires a combination of people, process and automation working together.

Those organizations with leadership from the top that recognize that cultural transformation is a competitive advantage will lead an effective organizational change. Old quality KPIs must be updated to encourage collaboration, accountability, and growth mindset.

… and with the continuous digital feedback loop facilitated by automated data capture and data insight, manufacturers will be able to deliver enlightened customer experiences, free of issues.