- A Taxonomy of Quality Problems
- Taxonomy Diagram of Quality Problems
- Types of Quality Problems
- Problem Solving Table
Categorizing Your Problems In Solution Relevant Ways
Among the most useful taxonomies is one proposed by Frederick Nickols. Clearly recognizing the need to fit problem solving responses to the nature of the situation, Nickols differentiated three types of problems or tasks:
- Repair: To restore a malfunctioning system to its intended level of performance.
- Improve: To improve a system so performance goals are achieved.
- Engineer: To design a new system or solution that will satisfy pertinent goals.
A Taxonomy of Quality Problems
The distinction between performance and design problems was highlighted by recent research on quality problem solving (QPS). The study employed more than a thousand published cases describing quality problem solving activities conducted in organizations. A total of 719 cases drawn from 242 sources were analyzed to identify generalizable problem solving lessons. To organize these lessons, a taxonomy of quality problems that would encompass the variety of cases in this data set was devised. The result is shown on below picture.
Types of Quality Problems
The table bellow provides a closer look at the five kinds of quality problems. For each type, it identifies defining characteristics, critical problem solving tasks posed by such situations, and relevant solution strategies and techniques.
| Problem type | Defining characteristics | Key problem solving tasks | Strategies and techniques |
|---|---|---|---|
| Conformance | Unsatisfactory performance by a well-specified system; users not happy with system outputs. | Diagnosis; determining why the system is not performing as intended. | Use statistical process control to identify problems, cause and effect diagrams to diagnose causes. |
| Unstructured performance | Unsatisfactory performance by a poorly specified system. | Setting performance goals; diagnosis; generating viable solution alternatives. | Diagnostic methods; Use incentives to inspire improvement; develop expertise; add structure appropriately. |
| Efficiency | Unsatisfactory performance from the standpoint of system owners and operators. | Setting performance goals; localizing inefficiencies; devising cost effective solution alternatives. | Use employees to identify problems; eliminate unnecessary activities; reduce input costs, errors and variety. |
| Product design | Devising new products that satisfy user needs. | Determining user requirements; generating new product concepts and elaborating them into viable artifacts. | Quality function deployment translates user needs into product characteristics. Value analysis and “design for” methods support design activity. |
| Process design | Devising new processes or substantially revising existing processes. | Problem definition, including requirements determination; generating and elaborating new process alternatives. | Use flowcharts to represent processes, process analysis to improve existing processes, reengineering to devise new processes and benchmarking to adapt processes from others. |
Conformance Problems
A conformance problem is a situation in which a highly structured system, having standardized inputs, processes and outputs, is performing unacceptably from the standpoint of product users.
These are classic quality deficiencies addressed by traditional quality control activities, such as an assembly line producing rejects or mistakes being made in the processing of insurance claims. The key feature of a conformance problem is that there is a known right way of doing things. The system has worked before, but now, for some reason, it is not performing acceptably.
One or more aspects of the system—its inputs or processing activities—have deviated from the norm, so outputs are not as they should be. Problem solving is a matter of finding the causes of deviations and restoring the system to its intended mode of functioning. The identification of conformance problems is aided by the existence of standards.
System inputs, works in process and outputs can become pared with standards—problems being identified when mismatches are observed. Statistical process control, a powerful means of identifying conformance problems, is much less useful for identifying other types of quality problems. The existence of a known right way of doing things makes problem solving relatively easy once the causes of unwanted deviation have been localized— putting the system back on track so it functions as intended.
The major challenge with conformance problems is to identify the causes of deviations or defects. This is the task of diagnosis or determining causes. Though diagnostic efforts can be aided by techniques such as cause and effect diagrams, the Kepner-Tregoe method and why-why diagrams, there is no general procedure for determining causes. Every production process is incredibly complex. Therefore, there are literally thousands of ways for things to go wrong. Due to the existence of strong standards, conformance problems are the easiest of the five types of quality problems to identify and solve.
Nonetheless, the difficulty of establishing the causes of deviation in complex performance systems can make these problems extremely challenging, such that weeks or even months of production can be lost before the situation is remedied. Conformance problems often result from human error, which, in turn, can occur because workers are not adequately motivated toward error-free performance. A useful heuristic is to make sure that errors have costs or consequences for the people who make them—for instance, returning faulty inputs to their originators.
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Unstructured Performance Problems
An unstructured performance problem (UPP) is a situation in which a nonstandardized task, one not fully specified by procedures or requirements, is not being performed acceptably. Poor performance can affect customers or the company itself—increasing costs or reducing throughput for example. But the hallmark of UPPs is that the poorly performing process or system is unstructured; it is not laid out in detail by rules and requirements. For instance, sales shortfalls indicate unsatisfactory performance of the sales system. Since there is no one right way of selling a product, sales shortfalls cannot be cured by enforcing standards that don’t exist.
Why wouldn’t an activity be standardized? It can be relatively new or may only be employed on occasion. Knowledge work cannot be standardized if tasks involve judgment and creativity. Many service activities aren’t standardized because they must be adapted to fit varying circumstances and customer needs.
Because they are performance problems, diagnosis—determining the cause of the performance deficit—is critical when solving UPPs. Unlike compliance problems, UPPs often result from multiple causes. Other tasks are equally challenging. Problem identification can be difficult if performance goals and criteria are not clear. Even if one knows the cause of a UPP, it can be difficult to devise an effective solution. Because unstructured performance problems are so diverse, the most important tool for solving them is analysis, thinking carefully about the situation at hand. Several other strategies are also useful. Providing incentives can motivate people to find solutions.
Efficiency Problems
A rarely recognized anomaly in the quality movement is the fact that while quality is typically defined in terms of satisfying customer needs—many quality improvement activities are aimed at reducing costs, increasing throughput and improving worker safety. These are matters that are of no direct concern to customers. This apparent paradox can be resolved by adopting a stakeholder perspective on quality, viewing product quality in terms of the interests of different stakeholders—a company’s owners, managers, employees and customers.
Efficiency problems reflect this broader view of quality, being situations in which the interests of stakeholders other than customers aren’t satisfied. Cost and productivity concerns are the most common issues of this kind, hence the category’s name. In a typical efficiency problem, while the outputs of a relatively well-specified system are acceptable to their users, the system’s performance does not achieve internal organizational goals. Goal setting is a challenge with efficiency problems as it can be difficult to determine what level of performance is attainable. Diagnosis is a matter of localizing inefficiencies; it is not always easy to identify promising opportunities for improvement.
Effective identification of efficiency problems depends on worker involvement. An organization’s employees are its most valuable resource for identifying ways of reducing costs and improving safety.
Problem solving can adopt various general strategies: Focus on major cost items; reduce input costs, errors, and variety; eliminate unnecessary activities and outputs; improve inputs and activities; and increase outputs, assuming they can be sold, to exploit economies of scale. Implementing these strategies requires detailed analysis of all inputs, activities and outputs for all organizational processes.
Product Design Problems
The problems discussed thus far have all been performance problems, situations in which an existing system isn’t performing acceptably. Quality improvement activities also address design problems—situations in which a new system must be created or an existing system substantially revised. Product design problems require one to create a system or artifact that satisfies user needs. These are familiar concerns, especially in competitive, technology driven industries.
Most organizations have new product development departments, though product design work increasingly involves a broader set of participants. One key task in product design is requirements determination, identifying user needs and other demands that the intended artifact must satisfy. Quality function deployment is the quality movement’s primary contribution to this endeavor.
The technique maps user needs into product characteristics and, from there, into production procedures and specifications. The major challenge in product design is design itself, envisioning and creating artifacts. This is a top-down process that begins with the generation of high level design concepts.
A promising concept is selected for development, being elaborated into components and subcomponents until, finally, a detailed design specification of an acceptable artifact is achieved. One reason product design involves the contributions of so many people is that a design must encompass many considerations that reflect different areas of expertise. The product must be manufacturable, reliable, maintainable, repairable and disposable, to name a few. These considerations have given rise to “design for” methods. Value analysis, a technique for minimizing product costs, is a design-for-cost method, similar to design-for-manufacturing, design-for-reliability and other methods.
Effective product design reaches beyond expressed customer needs—customers don’t always know what they want, much less what they can have—to consider the product’s total context of use and any environment it can be expected to encounter during its life cycle. Increased competition and the faster pace of innovation in many industries has motivated companies to shorten the product design process. The quality movement’s traditional concern—that products satisfy customer needs— inevitably led quality improvement activities to address product design issues.
Other fields, notably engineering, have produced more significant advances in product design methodology. But the quality movement has contributed to the improvement of product design. Its major contribution, is the enhancement of organizational product design processes. This suggests the fifth and final type of quality problem.
Process Design Problems
A process is an organized set of activities aimed at achieving a goal. Process design is the task of devising processes that achieve their goals. Arguably, if all processes were correctly designed, there would be few problems of any kind.
Many performance problems can be traced to process inadequacies, so the two types of issues—performance and process design— often blend. Process inadequacies were only identified as a result of serious performance problems.
During the past 20 years, the quality movement has changed this thinking. It has fostered increased management awareness of organizational processes, establishing process design and improvement as ongoing requirements for organizational success. If the identification of process design problems is institutionalized, problem definition will continue to be a challenge. Effective definitional activity determines how the existing process operates, how comparable functions are performed in other organizations and what process possibilities have been created by technological advances.
As with products, design work is the most critical activity in process design problem solving. Since processes have a start-to-finish time dimension that products lack, process design often parallels the process flow and is less top-down than product design.
A major challenge is striking a balance between old and new.
Designers must respond to legitimate process requirements— reflected in the existing process and those used in other organizations— without losing the ability to envision radical new processing alternatives. The danger of becoming mentally trapped in old ways of doing things is matched by the risk of reinventing the wheel or devising a revolutionary new process that doesn’t work. The flowchart is the cornerstone of most process design activities. It is a means of representing existing and envisioned processes. Benchmarking allows one to learn from processes in other organizations.
Conclusion
Quality problems in organizations are far from one-size-fits-all. As this article demonstrates, effective problem solving begins with accurately identifying the type of problem—whether it’s a matter of conformance, performance, efficiency, product design, or process design. Each category presents distinct challenges, from diagnosing deviations in structured systems to engineering entirely new solutions that meet user and stakeholder needs.
By applying the appropriate tools and strategies—be it statistical process control, incentive systems, value analysis, or benchmarking—leaders and teams can better align their responses with the nature of the issue. Ultimately, understanding the taxonomy of quality problems enables organizations to approach continuous improvement more systematically, ensuring not only higher quality outputs but also more resilient and efficient processes.
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