13
Quality Related Risks

13.1 INTRODUCTION

Quality management is a philosophy that seeks to prevent defects in products or services rather than relying on inspection to sort out defects after they occur. Therefore, improper implementation of quality management or lack of it leads to many quality problems which then lead to quality risks. Many organisations use a quality management system (QMS) to mitigate risks, particularly risks inherent in the organisation. Many risks are in fact not risks but bad practice. Bad practice by definition is a risk in itself. A QMS helps create best practice and thus reduces many inherent risks and the risk of not meeting customer expectation.

13.2 DEFINING QUALITY RISKS

Risk refers to a lack of predictability about a problem structure, outcome or consequences in a decision or planning situation (Hertz and Thomas 1984). Quality risk has been defined as the potentiality that a product or service will not meet a consumer’s minimum quality standards (Peterson and Wilson 1985).
Quality risks of products and services are often counted as operational risks. Operational risk is defined as the weakness or fallacies in the organisational processes and transactions (Ruin 2001). Managing operational risks not only ensures the comfort that the desired product or service is achieved, but also ensures that the required product or service is constantly of the quality that an organisation can boast of, for customer satisfaction and value for money.
Quality risks arise due to quality problems in products or services. Smith (2000) classified quality problems into performance problems and design problems. These were then categorised into five specific types of quality problems:
Conformance problems – unsatisfactory performance by a wellspecified system; users not happy with system outputs.
* Reproduced by permission of A. Merna.
Unstructured performance problems – unsatisfactory performance by a poorly specified system.
Efficiency problems – unsatisfactory performance from the standpoint of system owners and operators.
Product design problems – devising new products that satisfy user needs.
Process design problems – devising new processes or substantially revising existing processes.
Crosby (1985) states that ‘there is no such a thing as a quality problem’; quality is seen as a series of managerial problems. He placed a heavy emphasis on top management’s role in motivating quality improvement throughout the organisation in addition to targeting the problems to be eliminated.
Poor quality of goods and services can also lead to quality related risks which represents an impact on the survival of any economic unit. Figure 13.1 summarises the risks due to poor quality.
Figure 13.1 Risks encountered by poor quality (Edosomwan 1995)
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BM Trade Certification Ltd (Ambrose 2005) stated that it is often found that organisations such as professional services are reluctant to admit that there is any risk of non-conformity in what they do. They are therefore reluctant to allocate resources to controlling something they believe could not exist in their organisation. Non-conformities can often be present but are continually corrected in the course of work, not recorded and therefore repeated.
Feigenbaum (1983) defined a non-conforming unit as ‘a unit or service containing at least one departure of a quality characteristic from its intended level or state that occurs with a severity sufficient to cause an associated product or service to not meet a specification requirement’.

13.3 STANDARDISATION – ISO 9000 SERIES

One of the necessary conditions for entry and prestige on the international market is the possession of the ISO standard’s certificate. If an enterprise endorses these standards, they maintain QMS, which will ensure that its products/services satisfy the needs and requests of the customers. The aim of this standard’s implementation is to gain customer confidence through supplier reliability leading to a more efficient business.
ISO 9000 series was developed by the ISO Technical Committee (TC) 176. It was published in 1987 and is updated approximately every five years. The series consists of five documents whose focus is quality assurance systems: ISO 9000, ISO 9001, ISO 9002, ISO 9003 and ISO 9004 (Lamprecht 1993):
• ISO 9000: Quality Management and Quality Assurance Standards – Guidelines for Selection and Use
• ISO 9001: Quality Systems – Model for Quality Assurance in Design, Production, Installation, and Servicing
• ISO 9002: Quality Systems – Model for Quality Assurance in Production and Installation
• ISO 9003: Quality Systems – Model for Quality Assurance in Final Inspection and Test
• ISO 9004: Quality Management and Quality System Elements – Guidelines.
ISO standards developed in 1987 were revised in 1994 by the International Organisation for Standardisation and had a new version published in 2000. ISO 9000:2000 is far more process oriented than ISO 9000:1994 which was primarily based on procedures. ISO 9001:2000 sets new and different standards. It demands continuously assessing the processes and investigating how to improve them. In this case, it is important to differentiate between process and procedure, procedure is a number of processes.
ISO 9001:2000 identifies a set of outcomes to be achieved and is not specific about how the requirement is met, thus the fundamental responsibility for the design of the management system lies with the organisation creating it. Therefore for the quality system to be truly effective an organisation must consider all the influences on the system – including cultural – especially where this has a direct effect on the customers’ experience (Lawson 2003).
Al-Khalifa (2000) stated that the benefits of ISO series certification are:
• creates a quality system and provides a base for a management system
• promotes trade through assurance of contract performance
• opens new markets
• meets EU business requirements
• provides a potential for less waste
• diminishes customer audits
• improves documentation and enhances creditability and
• promotes good working practices.
However, Ackers (2000) stated that in practice the benefits which have been obtained have been variable. He stated that ‘the present drafting and audit controls allow scope for companies to comply with the letter of the standard but not its spirit, and companies which have chosen to do this have incurred the costs of implementation without gaining all of the benefits’. Therefore, while an enterprise will not resolve all of their problems upon receiving certification, it will aid the enterprise in winning over the clients and becoming more open (Kumburovic 2000).
Jacobs (2004) noted that optimists will argue that ISO 9001 certificated companies have a better survival rate than non-certificated ones. That may be a statistical fact but it is irrelevant to the fledging business just trying to survive in a relentless market with customers squeezing down prices and pushing up quality demands.

13.4 QUALITY RISKS IN MANUFACTURING PRODUCTS

Among the reasons offered for the failure of total quality management (TQM) initiatives is that firms do not measure quality effectively; they lack essential measures to monitor customer satisfaction, employee morale and management leadership (Sebastianelli and Tamimi 2002). But before quality is measured, organisations must understand the important dimensions they consider for competing on quality. Merna and Patel (2000) suggest that TQM has several facets, those being:
• identifying what (standards, performance, requirements) the customer rally wants
• defining the organisation’s mission
• involving all personnel in identifying how the above can be better achieved
• designing ways in which performance can be improved
• measuring how well performance meets the required standard throughout the total production process and
• analysing continually how performance can be improved.
In their research Merna and Patel (2000) noted that of the 35 project management topics considered over the project life cycle risk management and quality management had been ranked 7th and 8th in terms of importance in the management of projects.
Garvin (1987) provides a well-known framework for thinking about product quality that is based on eight dimensions: performance, features, reliability, conformance, durability, serviceability, aesthetic, and perceived quality. Yet, product quality is a complex, multidimensional factor for which a global definition does not exist.
Building customer satisfaction is the next logical step in a chain that leads from product and process quality towards a complete, mutually beneficial relationship of loyalty and trust between customer and supplier (Hampshire 2003). The consequence of faulty products was that the level of customer satisfaction was low, profit margins were being eroded and administration staff spent a disproportionate amount of time and effort correcting these errors, in effect bad practice. Therefore, companies must contain potential quality problems before the product leaves the plant, while providing detailed product genealogy information to trading partners.
To be fair, even organisations with the highest quality reputation might be taken off guard by the emergence of a new quality problem; however, it is presupposed they will soon begin to search for the cause of the defects.
Juran (1988) defined defect as ‘any state of unfitness for use, or non-conformance to specification, such as, oversize, low mean time between failures, illegible invoice’. Typical examples of defects are found in products constructed with materials of insufficient strength or durability. The consequence of design defect can be crippling: massive recalls, costly modifications, loss of reputation and sales, even going out of business.
The following deals with the consequences of product defect or non-conformance.

13.4.1 Product Recall

The most severe outcome of poor quality is product recall. Product recall is a term used to describe the actions taken due to non-conformity in products which have already been dispatched to consumers. The actions may consist of amendments made in the field. The actions may also consist of removing the product from the field. Recalled products are as diverse as automobiles, bicycles, chemical sprays, toys, food, and medical devices, to name but a few.
Companies which have the highest standards of quality in design and manufacturing may on occasions find it necessary to withdraw products from service for replacement, modification or refit (Dale and Plunkett 1990).
Recall is a costly and time-consuming event that should be avoided entirely, but without adequate quality programmes of process traceability, too many customers will receive defective products and too many products will be recalled for repair or replacement even though they are not defective. This has enormous implications for the quality-conscious manufacturer that gets rated on the number of recalls it performs, not to mention the risks associated with the direct and indirect costs.
The managing director of Aon’s Crisis Management, Harrison (2005), mentioned that ‘In addition to obvious food safety risks, many food manufacturers have begun to outsource the production and distribution of their products – lending recipes, production techniques and brand names to third parties. This high level of outsourcing has generated product recall and contamination exposures for third parties and their suppliers. Most suppliers are fully aware of general risks, but many fail to consider the damage their products could do to another company’s reputation or its bottom line. The lack of awareness about this exposure means that many small companies are at risk for losses that could put them out of business altogether.’ One of the supposed benefits of outsourcing is the risk transfer element. However, many organisations increase the risks associated with their product or service by outsourcing to suppliers. In some cases organisations outsourcing elements of work will mitigate their own risks by insisting on their own personnel being involved and their QMSs are adhered to by the supplier. This is evident in the manufacture of materials for pharmaceutical products.
To decide if a recall is necessary a firm must:
• gather all available information on the suspected defect (arrange testing, talk to consumers who have complained) and assess the reliability of that information (data risk)
• undertake a comprehensive risk analysis
• identify how the problem occurred – consider the possibility of tampering after the product left the firm’s premises, or misuse or abuse of the product
• look at all possible ways of addressing the defect and decide whether
• the firm can repair or modify the product and
• decide what needs to be done.
Such trends underscore for producers the urgent need for quality programmes which not only will enhance the likelihood of turning out products of high initial quality but will provide the necessary records and logs and product-tracking mechanisms that are vitally important in the event of product recall (Feigenbaum 1983).

13.4.2 Re-work

Re-work represents all actions required to transform products which do not meet a pre-specified quality standard into such, fulfilling all requirements (Inderfurth et al. 2005). Re-work, in a broad sense, is wasted labour and if continued indicates the quality of work produced by one or more groups of people or departments (Moulis 1992). Re-work can be an expensive risk mitigation method.
Reasons for the existence of re-work include:
• unreliable production processes
• engineering/design defects
• improper interpretation of customer requirements
• inability of used tools or test equipment to meet the desired tolerance
• improper revision level in use and
• improper selection of people for desired operation.
Baker (2000) states that ‘re-work is a challenging business. There are still a large number of things that can go wrong (making bad things worse), and by the time you figure out that you need to re-work a production run, your deadlines are either very near or have already passed.’
Figures on the amount of re-work do not provide a signpost on how to reduce it. They do provide, however, a basis for understanding the magnitude of the problem. Moulis (1992) indicated that excessive and repetitive re-work usually results in the following:
• excessive and unauthorised use of man-hours reflected in a drain on profit
• excessive manufacturing flow time
• delays in schedule commitments – between departments as well as to customers
• unplanned use of fixed assets – test equipment, fixtures, special tooling, etc. and
• negative effect on morale; people just do not like to continuously go over their work or someone else’s work without some indication that the cause is being corrected.
In many cases, defective items incorporate substantial value, such as those caused by expensive input materials, and hence there is an economical incentive to rework those products into ’as new’ condition.

13.4.3 Scrap and Wastage

Scrap means scrapping the installed parts and those in stock. It involves the defective products that cannot be repaired, used or sold.
Scrap generation and defect origins are one of the major, basic concepts of evaluating manufacturing performance. They are the criteria and major contributors to the realisation of profit, productivity, quality, on time delivery, maximisation of capabilities, acceptable vendor performance, product redesign, scheduled preventive maintenance, and the list goes on. Since undue scrap losses may reflect poorly on individuals and groups, including supervisors responsible, a temptation to hide scrap losses may often presume to exist (Lester et al. 1985).
The major causes of scrap include:
• equipment failure, troubleshooting and waiting for repair
• a non-reported, or unscheduled for repair problem
• in-line production equipment installation and
• in-line production equipment installation and
• incorrect or lack of maintenance procedure (human factor).
Regardless of how a company handles scrap, everyone can agree that scrap is a bad thing. But companies vary as to what they actually do to reduce scrap. Companies should be willing to do more to minimise scrap if raw material is costly (Lynch 2002).
Wastage, on the other hand, is all the activities associated with doing unnecessary work or holding stocks as a result of errors, poor organization, the wrong materials, exceptional as well as generally accepted losses (Oakland and Porter 1995).
Generally speaking, waste is generated due to different types of causes. The following six types of waste are very common, according to Samaddar and Heiko (1993):
• waste due to overproduction
• waste of movement/transport and double handling
• processing waste
• waste due to waiting
• waste due to defects and
• waste due to lack of integration.
What we are concerned about here is wastage due to defects. Product defects themselves, such as scrap, may be a direct source of waste, but by a multiple effect can also bring about additional waste in production. First, rework costs may be incurred. Second, if defects are found in one station all other subsequent stations may have to stop and wait. The latter adds to the cost of the product and increases production lead time. While some defects may appear to be inevitable, the focus should be on designing the process to pre-empt such defects from occurring rather than finding them by inspection.
Waste costs companies money. The more waste that can be eliminated or reduced the greater the opportunity to create an effective and profitable manufacturing operation.

13.4.4 Consumer Complaints

Every organisation offering products to the public is likely to receive complaints at some time. Juran (1988) defined complaints about quality as an assertion of quality deficiency. The complaint may concern the product or it may concern other activities such as incorrect invoicing or shipment of incorrect goods.
Consumer complaints come from a wide variety of sources. Many are made by unsatisfied users of the product. However, many also come from consumers who are satisfied users of the product, non-users of the product, and even non-purchasers of the product (Jacoby and Jaccard 1981). The reason underlying complaints differ between each type of consumer; it thus becomes necessary to identify who is complaining and why, in order to determine if the complaints received are indicative of product defect.
There are a number of factors that influence whether the consumer complains:
The manufacturer’s reputation – if a firm has a strong image for quality and a well-known reputation for making adjustments, consumers are more likely to complain when they are unsatisfied (holistic risk).
The accessibility of the firm for lodging a complaint – the consumer is more likely to make a complaint if it can be done at a conveniently located retail outlet.
Willingness of the firm to provide redress – some consumers seek redress or complain only when they are reasonably confident of obtaining a favourable outcome.
Perception of organisation’s intentions with respect to the problem – consumers who believe that a firm intentionally deceived them or acted to dissatisfy them would be more likely to complain than those without this perception.
Product satisfaction is why clients buy the product. Product dissatisfaction has its origin in product failures. Customers buy products because of a positive attitude that they have toward the product. Complaints do shed some useful light on field performance but such data must be supplemented by market research to draw conclusions about customer satisfaction. Study of complaints is certainly necessary but it gives a biased picture of performance of a product or of a service (Deming 1986).

13.5 QUALITY RISKS IN SERVICES

Service quality perceptions often arise out of the service delivery process, that is, the interaction of service providers with customers, rather than from the production process (Zeithaml et al. 1988).
Unfortunately, interest and research in service quality seems to be running about 60 years behind interest in product quality (Gummesson 1988). One emerging view argues that service purchases are probably perceived as riskier than product purchases (Turley 1990). Since researchers have recognised that services tend to be less uniform than products, quality risk appears to be an issue that service managers need to be aware of when setting strategies.
Service quality perceptions are caused by: professionalism and skills, attitudes and behaviour, acceptability and flexibility, reliability and trustworthiness, recovery reputation, and control (Gronroos 1988). However, an understanding of how consumers evaluate quality is vitally important. It is, after all, the consumer’s perception of quality that counts, not management’s.
Turley (1990) reviewed a study in which it was concluded that the highest quality-risk service was savings and loans/banks. Therefore, managers of such services need to be particularly concerned with quality-risk perceptions.
Harrow (1997) indicated that public service managers know that, whatever attitude to managing and assessing risk they adopt, there is always the likelihood of public rejection, not only when decisions go disastrously wrong but also when outcomes are not quite as planned. From a competitive point of view, service firms that implement quality-risk reducing approaches should have an advantage over firms that do not.
Dr Joseph Juran, quoted by Hetland (2003), stated that if you continue to do the same thing you will get the same result. Improvement will require changes in the processes. The risks associated with changes, particularly in terms of quality, can result in loss of profit and loss of customers.
Hillier (2004), quoted in Elliott and Atkinson (2007), notes that price falls in recent years have not been what they seemed stating that a new phenomenon, ‘stealth inflation’, in which the quality of goods and services decline along with price is now prevalent in global markets. The authors suggest that the risks associated with this must be addressed by organisations in the same way as destructive technology. Customers will always seek value for money; however, most customers will have a minimum benchmark and should quality drop below that benchmark they seek alternatives. Similarly with destructive technology customers will seek more efficient ways of meeting specification by insisting on the latest technology available, usually at a more competitive price and with greater efficiency and reliability.

13.6 QUALITY CONTROL AND APPROACHES TO MINIMISE PRODUCT QUALITY RISKS

Productivity and profit improve if adequate quality control tools are applied in organisations. Deming (1986) states that quality to the production worker means that his performance satisfies him, provides him with pride of workmanship.
Improvement of quality shifts waste of man-hours and of machine time into the manufacture of good products. The result is lower costs, better competitive position, and hence better reputation as represented in Figure 13.2.
Early in the twentieth century, the term ‘quality control’ began to be used as a synonym for ‘defect prevention’ (Juran 1988). However, later on, the term included tools, skills and techniques through which quality is carried out. Quality control is defined as ‘activities designed to minimise the incidence of non-conformance during and after production. Specifications and tolerances are established, process capabilities ascertained,
Figure 13.2 Schematic representation of the consequences of quality improvement (Al-Derham 2005)
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and tests and inspections performed to compare actual against standard performance’ (Enrick 1985).
The seven well-known tools of quality control are as follows (Mizuno 1988):
Cause and effect diagram – a pictorial representation of the main inputs to a process, problem or goal, with detailed sub-features attached to each of the main inputs (also referred to as Ishikawa or fishbone diagrams).
Pareto chart – a bar chart illustrating causes of defects, arranged in decreasing order. Superimposed is a line chart indicating the cumulative percentages of these defects.
Check Sheet – generally in the form of a data sheet, used to display how often specific problems occur.
Histogram – a diagram of the frequency distribution of a set of data observed in a process. The data are not plotted in sequence, but are placed in the appropriate cells to construct a bar chart.
Scatter diagram – a collection of sets of data which attempts to relate a potential cause with an effect. Data are collected in pairs at random.
Control chart – a graph of a process characteristic plotted in sequence, which includes the calculated processes mean and statistical control limits.
Flow chart – a picture of a process, using engineering symbols, pictures, or block diagrams, which indicates the main steps of a process.
Smith (2000) introduced strategies and techniques for solving his classification of quality problems mentioned previously as shown in Table 13.1.
A quality aware company can eliminate most of the cost caused by a quality problem by directly and immediately focusing on quality improvement (Freiesleben 2004). Continuous improvement of processes and systems can be effectively achieved using statistical and associated techniques that help identify, predict and reduce process variation, and so improve consistency and quality (Grigg 2004).
Although we must accept the fact that variability does exist, there are methods to control it within satisfactory boundaries. Statistical tools are available to identify quality problems but must have support of management to improve quality. Deming has stated that 85% of the causes of quality problems are faults of the systems which will remain with the system until they are reduced by management. The following is a list of the more common statistical tools used in quality control application (Hubbard 2003). These tools have specific applications in industry, and care should be taken to select proper one, as shown in Table 13.2.
Table 13.1 Types of quality problems and their problem solving techniques (Smith 2000)
Quality problem typeSolving strategies and techniques
1. Conformance problemsUse statistical process control to identify problems, cause and effect diagrams to diagnose causes.
2. Unstructured performance problemsDiagnostic methods; use incentives to inspire improvement; develop expertise; add structure appropriately.
3. Efficiency problemsUse employees to identify problems; eliminate unnecessary activities; reduce input costs, errors and variety.
4. Product design problemsQuality function deployment translates user needs into product characteristics. Value analysis and ‘design for’ methods support design activity.
5. Process design problemsUse flowcharts to represent processes, process analysis to improve existing processes, re-engineering to devise new processes and benchmarking to adapt processes from others.
Tassoglou (2006) identifies both qualitative and quantitative tools and techniques that are used to determine quality related issues. These include decision collecting tools, decision assessing tools and statistical process control tools which he concludes can be used in the data collection and data processing stages of a risk assessment.
Table 13.2 Common statistical tools used in quality control application (Hubbard 2003)
Statistical toolUse
1. Acceptance sampling plansEvaluate product attribute quality.
2. Analysis of varianceEstablish significance of difference between two sets of data.
3. Cusum chartCumulative subgroup difference plot.
4. Design of experimentsProvide valid data with minimum test.
5. Process capabilityLevel of yield uniformity.
6. Statistical inferenceSignificance of data difference.
7. Taguchi methodSpecification and tolerance technique.
Figure 13.3 The financial loss incurred by the increase in the number of defective units (Al-Derham 2005)
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Above all, the focus should be on eliminating core issues that cause problems, and taking steps to re-engineer processes and continuously monitoring and reviewing operational procedures. Management must accept any potential or known problem as a challenge and, more importantly, an opportunity to improve and control deficiencies.
Cost of poor quality measurement has proven to be a useful tool for focusing management attention on the profit impact of poor quality. Figures 13.3 and 13.4 illustrate a general representation of the relationship between defects and profit.
Figure 13.4 A graph showing the decrease in the number of defective units as the prevention costs increase (Al-Derham 2005)
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Figure 13.5 The effects of quality risks on the cash flow (Al-Derham 2005)
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These defects lead to quality risks which consequently affect the cash flow negatively as illustrated in Figure 13.5.
Clearly, the costs associated with pure risk, that being negative effects, can have a major affect on a project’s or investment’s cash flow. The QMS helps to mitigate risks associated with quality and provides the first step to avoiding inherent risks in an organisation.

13.7 SUMMARY

Quality management systems and the tools and techniques used in assessing quality problems are used extensively to avoid bad practice. Bad practice alone is a major risk to any organisation. The risks associated with not meeting the required quality standards in terms of specification, delivery, quality and quantity can have serious financial implications.
All organisations require QMS. The ISO Standards form a framework for creating best practice and traceability. The processes associated with any service or product or project can not only be addressed in terms of conformance but also assessed in terms of the risks associated with each process.
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