Future Directions in Quality Journey – Some Views

Quality as a profession has evolved over time. In the prehistoric period, quality was practiced as a regulatory requirement. The Hammurabi Code is known for the punishment given to builders or masons if a house collapsed and the people living in it suffered injury or death.

Evolution is a process characterized by variation, or change in a more generic sense, and by the selection of the variant most suitable, following the principle of evolution known as survival of the fittest.

Industrialization and Inspection

The quality journey in a formal sense became necessary with industrialization. Before mass production, individual artisans managed the quality of their own output. The initial methods of managing quality were driven by inspection, controlled by a profession we know as inspectors and testers. This new role created a significant divide between the producer and the inspector. This divide is still visible in many organizations today, and eliminating it remains one of the biggest change management exercises for the quality professional.

Statistical Quality Control

The use of statistics was well known in the scientific community. The tools used by researchers crept into organizations to manage business processes. These got the formal name Statistical Quality Control, initially used mainly by inspectors, and later Statistical Process Control, expected to be used by process owners and operators.

In the 1920s, Shewhart introduced the concepts of statistical quality control. It provided the foundation for understanding and reducing variability through the application of statistical theories. SPC tools gave the ability to keep processes and variability under control, delivering consistent, high quality telephones and networks for Western Electric and AT&T.

Dr. Deming provided the management philosophy behind his theory of profound knowledge and his 14 points, which were quite radical for his time.

The process orientation led organizations to think in terms of using tools to improve the effectiveness and efficiency of the process. The lack of these is expressed or reflected as problems in operations.

The analysis of processes led to the concept of Business Process Reengineering. BPR focused on making business processes meaningful and eliminating unnecessary steps or activities. This concept later grew stronger with Lean methodologies.

Productivity, Lean, and Six Sigma

On the productivity side, in the early 20th century, Henry Ford introduced the Ford Production System, which allowed mass production of a Model T Ford in any color the customer wanted, as long as it was black. The Ford Production System became the basis for the Toyota Production System, which for the first time emphasized employee learning and empowerment. In the 1980s, Just-in-Time principles arose as an offshoot of the Toyota Production System. The focus of JIT was to pull supplies and components through a system so they arrive where and when they are needed.

As the Toyota Production System and JIT evolved and coalesced into Lean, the philosophies of TQM and the statistical theories of SQC evolved into Six Sigma.

Lean starts with an external focus on supplying the customer with exactly what they want, when they want it, through the value chain.

Six Sigma captured the voice of the customer and critical to quality characteristics, along with a rigorous and structured problem solving methodology, a formal knowledge and tool structure, a focus on the bottom line impact of process improvement, and measurement and metrics.

Information Technology and Integration

Information technology evolved alongside these management philosophies and problem solving tools, moving from standalone software packages with non-integrated modules, such as financials separate from MRP, separate from engineering, process, and production data, as well as customer information. ERP evolved to integrate the wide spectrum of processes and information that was not possible in the MRP and MRP II days.

The integration of Lean and Six Sigma enhanced the focus on eliminating waste and reducing variability at the same time. Supply chain concepts and tools have integrated the value chain with the information chain.

Further integration of the supply chain with Lean Six Sigma is already a widely discussed concept today. This will lead to a focus on improving processes upstream and downstream through the supply chain with suppliers and distributors.

TQM, Total Quality Management, became prominent in the 80s and 90s, bringing together the management philosophies of many quality gurus, including Deming, Juran, Crosby, and Feigenbaum. It was light on statistical tools and problem solving methodology, largely leaving that to chance, but it provided for employee involvement, team based brainstorming and problem solving, and employee empowerment.

Innovation

Innovation has remained part of human evolution in different forms. The use of the wheel and fire to enhance quality of life are examples of early innovations.

Innovation as an economic concept includes the development of new:

• Products and services, such as the Ginger Hotel Chain
• Methods of production or provision, such as the cellular manufacturing concept
• Methods of transportation or service delivery, such as the ATM
• Business models, such as crowd sourcing and social networking platforms for business
• Markets
• Forms of organization

Stereotypically, innovation is considered a product of genius, a flash of light. However, practitioners have evolved systematically planned and organized innovation.

Future of the Quality Tools

Tools that have developed and evolved can be broadly classified into two categories.

People centric tools have evolved and become stronger due to the availability of better skills, the aspiration of more skilled employees to be part of the improvement journey, and most employees reaching and striving for a higher level of Maslow's hierarchy of motivation.

Data centric tools were largely built through statistics and the application of statistical approaches. Initially this was largely Bayesian statistics, and later inferential statistics became the stronghold. This is becoming stronger with the quantity of data now available for studies. It was easier to implement, largely due to the availability of skilled manpower and software that assists in using these tools easily.

Some direction for specific areas could include:

• Six Sigma, with reduction in cycle time being the most common project area and considered most beneficial to the customer and industry
• Inclusion of the vendor's organization in Six Sigma projects
• Integrating Six Sigma with other initiatives
• Restructuring of time allocation within the DMAIC and PDCA structure
• The impact of technological advancements
• Modeling tools
• The impact of global recession
• Open source innovation
• Quality tools deployment through automation and the building of AI and neural network concepts
• Documentation of learning and projects becoming a specialized skill

Challenges in Quality Management

The challenges include a larger base of knowledge and data, the pace at which options are available to consumers, and the fast pace of consumer life, leading to changes in demand at high speed.

Ever demanding customers. Increased options and greater knowledge of the product life cycle have led to ever increasing demands.

Shifting customer value perception. The life of a value perception is shorter as the product life itself comes down. New product introductions, which used to take years, now take months. Value perception is also frequently changed by the presence of strong media and internet, which provide faster information about products and businesses.

Increasing economic pressures. Demand on all resources has increased sharply. The pressure on organizations to perform at a higher level is increasing. Organizational performance is being micro viewed by investors in the short run. In fact, the long term has become either obsolete or significantly shorter.

Reduced control over data and information. With the internet and computerization, access to and availability of data is relatively easier. RTI has further changed the dimension of data availability for analysis and working.

Recognition of softer issues in business processes. With the growth in the knowledge of the worker, and the trend of businesses becoming more knowledge focused, management processes now call for looking into the softer issues of human relations, within and outside the business process. In the early 20th century, Ford wanted only two hands and two legs, but today organizations want the matter above the shoulder more than the limbs. This has forced organizations to look into the softer side of human management. Human resource management has moved from treating humans as another article to treating them as a resource that can contribute and enable better use of other resources.

Risk based management approach. Risk based management approaches emerged more strongly toward the end of the 20th century and are becoming a stronger area of specialization and focus for business entities. Initially, risk was associated only with financial management, but today the risk based approach has extended to product development, process, employees, and environment. The risk based approach itself has moved from being subjective to an objective evaluation of risk.