Quality

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1 Introduction

Quality is a universal concept. Whether we are conscious of it or not, quality affects the creation, production, and consumption of all products and services. In this chapter, we look at quality in an enterprise information technology (EIT) context, including what quality is and what that means for an EIT environment (rather than on quality management systems). [1] Our focus is defining quality itself in such a way that its practical application is easily understood.

Quality is a critical concept that spans the software and systems development life cycle. It does not simply live within the quality department, nor is it simply a stage that focuses on delivered products. Rather, it is a set of concepts and ideas that ensure that the product, service, or system being delivered creates the greatest sustainable value when taking account of the various needs of all the stakeholders involved. Quality is about more than just how good a product is.

For consumers of EIT services and products in the enterprise, including those in-stream services and products that contribute to the delivery or creation of other EIT services and products, the idea of quality is inextricably bound with expectations (whether formal, informal, or non-formal). As more high-tech capabilities have become available to consumers at large, expectations for EIT have risen considerably. For this reason, it is crucial that EIT works with their enterprise consumers to understand expectations (and for consumers to understand what can reasonably be delivered).

2 Goals and Guiding Principles

The first goal of any organization is to clarify, understand, and then satisfy the stakeholders’ expectations of the products and services they receive. To do this, it is necessary to enable the organization to make information-based trade-offs when budgets, schedules, technical constraints, or other exigencies do not allow all expectations to be fully met.

The Quality function in the EIT organization includes far more than just testing new or changed services. Its overall responsibility is to provide appropriate structure (usually processes) and mechanisms for EIT personnel that will lead to highly effective development, delivery and operations services. Its specific responsibility for each project that will deliver new or changed services is to ensure that the service's intended users agree with the project's Release Criteria and that products are not released unless those criteria are met.

ISO/IEC/IEEE describes quality as the “ability of a product, service, system, component, or process to meet customer or user needs, expectations, or requirements.” [2] This statement incorporates a number of important principles:

  • Quality is not about what we do — it is about what the customers/users/stakeholders get[3]
  • Quality is not absolute, but is always relative to the particular context.
  • Quality, as an ability (or a set of “-ilities”), is observable, and so is something we can measure and evaluate.
  • Quality is about what the users (or stakeholders) expect, as much as what they might formally require.

This last point is echoed by respected writer on business and entrepreneurism, Peter Drucker, who wrote, “‘Quality’ in a product or service is not what the supplier puts in. It is what the customer gets out and is willing to pay for. A product is not ‘quality’ because it is hard to make and costs a lot of money, as manufacturers typically believe. That is incompetence. Customers pay only for what is of use to them and gives them value. Nothing else constitutes ‘quality’.” [4]

3 Context Diagram

06 Quality CD.png

Figure 1. Context Diagram

4 Key Quality Concepts

4.1 Measuring Quality

Quality is measurable. Quality in a product or service is comprised of a set of measurable attributes. Attributes are things like height, weight, color, reliability, speed, and perceived "friendliness." Attributes are selected for a given product's quality set based on the end users' requirements. The Quality Models described below provide common sets of attributes for EIT products and services.

By measuring quality attributes as the product is developed and tested, aside from knowing whether progress to meet the Release Criteria is being made, and whether it is increasing (or decreasing), we can also use the measurement information to make the kinds of information-based trade-offs that organizations often need to make. Measuring quality also supports the application of accepted management practices to the goal of achieving, improving, and increasing quality.

An important principle from management theory is “what you measure is what you get.” Thus, it is an important principle that product quality should be measured. Measurement of product quality is focused on knowing whether, and to what degree, expectations are satisfied or requirements are met. An example from Agile would be to know whether a component meets its “definition of done.” [5]

4.2 Requirements Management

To be able to measure product quality requires that the organization is capable of good requirements management. Requirements management comprises the set of processes that an organization uses to gather, assess, evaluate, quantify, document, prioritize, communicate, and, ultimately, deliver the requirements of its stakeholders. Requirements might be those illustrated in the graphic below.

RequirementTypeOptions.jpg

Figure 2. Requirement Type Options

Key goals of requirements management are to ensure that requirements are unambiguously stated, are universally agreed, and are understood in terms of their value to stakeholders.

Because requirements are fundamental to the delivery of a quality product, quality models (see Quality Models) are generally used as an aid to ensure that requirements statements are complete and comprehensive.

4.3 Quality Capability

Quality capability is the capacity and ability of the organization’s processes, procedures, methods, controls, and governance to deliver quality products.

In order to be confident about satisfying stakeholder requirements, the organization must also measure its quality capability, and, therefore, measure the quality of its processes, procedures, methods, controls, standards, and so on. The established way to create quality capability is by first introducing standard practices so that all participants in the process know what to expect, and to ensure that these practices are well understood and comprehensively adopted.

An organization’s quality capability often reflects its maturity. In a mature EIT organization, its members have a well-understood concept of their common processes and share a common vocabulary for talking about those processes. Various organizations have published versions of EIT maturity models, but there is a lack of general adoption of any model. In addition to making it easier for people to get their jobs done, standard practices also make it possible to methodically collect and implement lessons learned at specific points in a development project or at regular times during EIT production operations. This reflects the principle of continuous improvement.

4.4 QMS and QC vs. QA

The fundamental approach to achieving quality products and services is to develop processes and mechanisms for quality control (QC) and for quality assurance (QA). These are normally expressed as an organization’s quality management system (QMS), which is the collection of an organization’s business processes, quality policies and quality objectives directed toward meeting customer requirements

Although the terms QC and QA are often used interchangeably, there is a very meaningful difference between them as shown below.

QA QC.jpg

Figure 3. QC vs. QC

A common misconception is that QA and testing are equivalent. In fact, testing is one of the tools of QC, because the aim of testing is the detection and quantification of errors, which then results in defect reports. By assessing information from defect reports (as part of QA), EIT can determine whether it is meeting its quality objectives.

4.5 Technical Debt and the Cost of Rework

For most organizations, software production is based on a balance, or set of compromises between requirements, budget provided, and time available. Whenever a decision is made to limit (or omit or defer) engineering work due to budgetary or time constraints, the resulting loss in quality (quantified as the amount of rework that would need to be done later to rectify the compromise) is commonly referred to as technical debt[6] In essence, technical debt accrues when a “pay now or pay later” situation results in a “pay later” decision. Typical causes of technical debt include:

  • The tendency to decide consciously not to fix known minor bugs prior to delivery because of time (or other) pressures
  • A lack of knowledge about how much, and what kinds of, testing should be done prior to releasing a system into operational status, resulting in errors not being found until the system goes into production

Technical debt is referred to as a debt because the applied design or construction approach (often called a “kludge”), while expedient in the short term, creates a technical context in which the same work will likely have to be redone in the future — incurring a future cost (or debt). The total cost of such rework is typically greater than the cost of doing the work now (including increased cost over time), and escalates as technical debt accumulates.

The cost of rework is usually seen in EIT as fire-fighting. Hidden bugs from poorly designed or built code appear suddenly, usually at the worst possible time, precipitating an urgent fix. People must drop everything to get things running normally again.

The total cost in such situations is both in the work done to fix the bug as well as in the work that had to be dropped so that the bug could be fixed. Technical debt, however just refers to how much it would cost to fix the poor quality issue at hand; it doesn’t include the lost opportunity inherent in new work that had to be put off.

While estimates do vary, some studies suggest that maintenance activities — most of which are rework of some kind — can account for up to 80% of an EIT budget. An inevitable result of this kind of cost burden is that fewer resources are left available to fulfill requests to create new capabilities in support of new business opportunities.

Based on “the analysis of 1400 applications containing 550 million lines of code submitted by 160 organizations, CRL estimates that the technical debt of an average-sized application of 300,000 lines of code (LOC) is $1,083,000. This represents an average technical debt per LOC of $3.61.” [7] CRL considered only those problems that are “highly likely to cause severe business disruption,” not all problems. Several studies have undertaken efforts to quantify the economic impact of technical debt. According to Gartner research (as reported by Deloitte University Press, http://dupress.com/articles/2014-tech-trends-technical-debt-reversal/) “… global EIT debt [in 2014] is estimated to stand at $500 billion, with the potential to rise to $1 trillion in 2015.”

ApplicationAnalysis.jpg

Figure 4. Application Analysis

5 Product and Service Requirements

Everyone understands that EIT must work to provide specified functional requirements, but few understand non-functional quality requirements. While functional requirements describe the functions (often called features) that a product should have (the things it should do), non-functional requirements describe requisite qualities (attributes) of the solution that are necessary to deliver the functionality. [8] Requirements may also be implicit, rather than explicit; for example, a feature may require interfacing with another application in order to deliver the information requested by the user, but the user may not know what other systems the application needs to talk to in order to get the information. Non-functional requirements are also used to judge the operation of the system, and as such are an important part of the requirements gathering and analysis process.

To ensure that all requirements are appropriately considered in product implementation, it is essential that appropriate quality measures are also selected in discussion with the consumer of the product. This facilitates an objective evaluation of product quality. Determining the most appropriate measures requires defining the attributes that are most important. For example, a software product used for creating calendar entries or mailing lists may not need the same degree of timeliness, accuracy, and precision as software used in safety critical applications. Requirements for high levels of certain quality attributes are more prevalent in critical enterprise systems that have impact on productivity, communication and revenues, and in the protection of personal, financial, or business proprietary information.

Quality requirements may be specified in service-level agreement (SLAs) or in release criteria for introducing new capabilities. Quality Models describes commonly accepted quality models, which can be used to help identify the required quality attributes (the quality requirements) to be specified in SLAs and release criteria.

6 Planning for Quality

Quality rarely happens by accident; if it does, it is even more rarely repeatable. Organizations that consistently achieve high quality do so by preparing the groundwork through appropriate planning. Quality planning is the process of "identifying which quality standards are relevant to the project and determining how to satisfy them.” Quality planning means planning how to fulfill process and product (deliverable) quality requirements.

Creating a quality plan for a product or project is related to, but different from, the task of creating a project plan. It takes these factors into account:

  • The stakeholders’ requirements must be fully understood and prioritized.
  • The organization’s appetite for accruing technical debt should be evaluated.
  • The attributes that allow stakeholders to decide that they have received quality must be identified and agreed.
  • Measurements to demonstrate that the required attributes are present must be identified and established.
  • “Lessons learned” from past projects must be applied to the overall project plan.

6.1 Inputs to Quality Planning

Inputs include management information such as planned milestones or checkpoints in the development or acquisition plan, and the plans of other groups who will participate in the delivery. To be effective, quality planning means knowing when the earliest possible opportunities for meaningful measurement will occur. The earlier that the quality control activities can measure artifacts, the earlier that quality assurance can start to compare the results to requirements. The earlier that issues are detected, the earlier that corrective action can be applied, which almost always means less rework downstream, at smaller cost, and with less technical debt.

QA and QC should be planned to occur as part of requirements specification, architecture and data design, and system development, as well as through configuration management, formal testing, and release into production, regardless of the chosen development approach (e.g., so called “waterfall” vs. Agile [9], and so on).

Four of the most important inputs to quality planning are service-level agreements (SLAs), customer relationship management programs, release criteria, and acceptance criteria. Service-level agreements (SLAs) are one of the most common methods used for setting expectations, especially for delivery of EIT services. They are contracts between service providers (e.g., software developers) and service consumers (e.g., customers), and typically exist as agreements between business managers and EIT management for the creation and delivery of software (or other products and services). They specify levels of service quality that business managers require. They are also hugely important where external vendors are involved. Typically, SLAs address such service-related items as business value expectations, security, performance (with metrics), incident management, and dispute resolution.

The establishment of customer relationship management (CRM) programs is becoming more common in EIT organizations. The purpose of CRM programs is to consistently monitor performance to SLAs, to provide a framework for ongoing assessment of user satisfaction, and to establish essential effective ongoing communications with customers.

Similar to SLAs, release criteria are also contracts between those who produce products and services and those who consume them. Again, release criteria are agreements between business managers in the enterprise and EIT management, and are also critically important to contracts with third-party vendors when acquiring a product or component. When initiating projects to deliver new products or services, the expectations — the quality requirements — should be spelled out in the release criteria, so that they can be measured at each delivery point. In addition to requiring that all performance, functional, and similar requirements are verified [10] to have been met and validated [11] to work as the user expects, a simple common release criterion is the stipulation that all highest importance (e.g., “Severity 1” and “Severity 2”) defects must be corrected.

Essential to each of these approaches is agreeing on what to measure, that is, identifying the key attributes of a service or product that should be measured in order to monitor its quality. In some EIT organizations, the project team may depend on the receiving organization to establish acceptance criteria. In those cases, quality planning should embed those criteria in the quality plan, and adjust them as necessary to attain requisite measures.

6.1.1 The Quality Plan

The quality plan, part of the overall project plan (though it may be a physically separate document), is the output from quality planning. While covering all of the areas presented above, at a minimum, it describes these criteria:

  • Product/service quality attributes linked to the release criteria or service levels specified in an SLA
  • Measurements for each attribute, with range of acceptable values
  • How and when measurements are collected and stored
  • Location of all relevant documents, such as test plans, checklists, management plans, etc.
  • Specific process improvements to be implemented
  • Resources responsible for the above

7 Quality Models

Because quality is typically thought of very subjectively (and thus as very different from other factors affecting software delivery, such as resources, or time), practical need saw the development of various quality models by many large high-tech companies. In the US, the national drive to higher quality was captured in the US government’s Baldrige National Quality Program and its Award in 1987. We list a few of the most common quality models below. (They are contained in ISO/IEC 25010:2010.)

IBM’s CUPRMD (pronounced “cooperMD”) specified capability, usability, performance, reliability, maintainability, and documentation as key quality vectors for product quality. This was a good start, as it provided a framework of measurable product characteristics for assessing when a product was good enough to ship.

Under Bob Grady’s [12] impetus, HP developed FLURPS (functionality, localizability, usability, reliability, performance, supportability) and its successor, FURPS+, which enabled different parts of the company to emphasize particular qualities on top of the four FURPS categories.

In the UK, ICL introduced the Strategic Quality Model as part of its quality improvement process (developed with Philip Crosby). The SQM was ICL’s implementation of the European Quality Award model (created by the European Foundation for Quality Management).

Standardization efforts for software product metrics began in the 1990s. After several rounds of evolution, FRUEMPS (ISO/IEC/IEEE Std 25010) is the current product quality model. Its perspectives can be applied to hardware and software systems as well as to software products. ISO/IEC/IEEE Std 25010 also presents a model for quality in use, while ISO/IEC 25012 provides a complementary data-quality model.

7.1 The Product Quality Model

The Product Quality Model (ISO/IEC 25010:2010) focuses on internal and external perspectives of a product (or other organizational output, such as a service or system). It can be used by those specifying or evaluating software and systems, and can be applied from the perspective of their acquisition, requirements, development, use, evaluation, support, maintenance, quality assurance and control, and audit. The model can also be a very useful checklist when determining the adequacy of a set of a requirements.

The quality attributes or characteristics of the product that can be assessed or measured, which are commonly abbreviated as FRUEMPS are shown in the graphic below.

QualityAttributes.jpg

Figure 5. Quality Attributes

7.2 The Quality in Use Model

The Quality in Use Model (ISO/IEC 25010:2011) takes a different perspective. Rather than focusing on the product, it focuses on the effect of the product in a given context of use and the experience of using it. It stipulates the following characteristics [13] for measuring the quality of a product in use:

  1. Effectiveness — The product does what the user needs (what the user wants it to do)
  2. Efficiency — The product does not impede the task at hand
  3. Satisfaction — The user appreciates the product’s usefulness, trusts it, and finds pleasure, comfort, in using it
  4. Freedom from risk — The product mitigates economic risk, health and safety risk, and environmental risk
  5. Context coverage — The context of the product is complete

7.3 The Data Quality Model

A user’s experience of quality depends on how efficiently and effectively a software product works. In most cases, the correct working of a product depends on data. Therefore, it is important, from a software development perspective, to pay attention to the quality of that data. The Data Quality Model (ISO/IEC 25012:2008) applies to structured data acquired, manipulated, or used by a computer system to satisfy users’ needs, including data that can be shared within the same computer system or by different computer systems. Data quality concerns itself with such characteristics as accuracy, completeness, consistency, credibility, currency, and precision, as well as various data usage characteristics such as accessibility, availability, efficiency, and understandability.

8 Summary

Quality is an important concept in software and service development. It is defined as the degree to which stakeholder requirements and expectations have been satisfied. While quality is primarily concerned with requirements satisfaction, it also has some impact on how software products and services are created: creating a quality product is dependent on the quality of underlying tools, methods, processes and resources. A mature quality capability underpins the delivery of quality products and services.

Quality, as defined, is measurable. Achieving quality, then, is strongly supported through the use of a robust quality plan, which specifies which quality controls (measures) will be used by quality assurance to guide product development to maximizing quality (and avoiding technical debt).

It is important to understand that quality is not the act of doing quality management, quality control, or quality assurance, though these are important tools. Rather, quality is something that is perceived by the recipient of the product or service. Because of this, effective requirements management, with clear acceptance criteria is critical to success.

Finally, making appropriate use of the various quality models is a great way of ensuring that a quality plan has taken account of all essential factors.

9 Key Maturity Frameworks

Capability maturity for EIT refers to its ability to reliably perform. Maturity is a measured by an organization’s readiness and capability expressed through its people, processes, data and technologies and the consistent measurement practices that are in place. Please see Appendix F for additional information about maturity frameworks.

Many specialized frameworks have been developed since the original Capability Maturity Model (CMM) that was developed by the Software Engineering Institute in the late 1980s. This section describes how some of those apply to the activities described in this chapter.

9.1 IT-Capability Maturity Framework (IT-CMF)

The IT-CMF was developed by the Innovation Value Institute in Ireland. It helps organizations to measure, develop, and monitor their EIT capability maturity progression. It consists of 35 IT management capabilities that are organized into four macro capabilities:

  • Managing IT like a business
  • Managing the IT budget
  • Managing the IT capability
  • Managing IT for business value

The two most relevant critical capabilities are Organization Design and Planning (ODP) and IT Leadership and Governance (ITG).

9.1.1 Organization Design and Planning Maturity

The following statements provide a high-level overview of the Organization Design and Planning (ODP) capability at successive levels of maturity.

Level 1 The organization structure of the IT function is not well defined or is defined in an ad hoc manner. Internal structures are unclear, as are the interfaces between the IT function and other business units, suppliers, and business partners.
Level 2 A basic organization structure is defined for the IT function, focused primarily on internal roles, responsibilities, and accountabilities. A limited number of key interfaces between IT and other business units, suppliers, and business partners are designed.
Level 3 The IT function’s organization structure is harmonized across internal functions, with a primary focus on enabling the mission and values of the business. Most interfaces between IT and other business units, suppliers, and business partners are designed.
Level 4 The IT function is able to adopt a range of organization structures simultaneously, from industrialized IT to innovation centres, in support of the organization’s strategic direction. All interfaces to entities external to the IT function are designed.
Level 5 The organization structure(s) adopted by the IT function are continually reviewed, taking into account insights from industry benchmarks. All interfaces are continually reviewed and adapted in response to changes in the business environment.

9.1.2 IT Leadership and Governance Maturity

The following statements provide a high-level overview of the IT Leadership and Governance (ITG) capability at successive levels of maturity.

Level 1 IT leadership and governance are non-existent or are carried out in an ad hoc manner.
Level 2 Leadership with respect to a unifying purpose and direction for IT is beginning to emerge. Some decision rules and governance bodies are in place, but these are typically not applied or considered in a consistent manner.
Level 3 Leadership instils commitment to a common purpose and direction for IT across the IT function and some other business units. IT decision-making forums collectively oversee key IT decisions and monitor performance of the IT function.
Level 4 Leadership instils commitment to a common purpose and direction for IT across the organization. Both the IT function and other business units are held accountable for the outcomes from IT.
Level 5 IT governance is fully integrated into the corporate governance model, and governance approaches are continually reviewed for improvement, regularly including insights from relevant business ecosystem partners.



10 Key Competence Frameworks

While many large companies have defined their own sets of skills for purposes of talent management (to recruit, retain, and further develop the highest quality staff members that they can find, afford and hire), the advancement of EIT professionalism will require common definitions of EIT skills that can be used not just across enterprises, but also across countries. We have selected 3 major sources of skill definitions. While none of them is used universally, they provide a good cross-section of options.

Creating mappings between these frameworks and our chapters is challenging, because they come from different perspectives and have different goals. There is rarely a 100% correspondence between the frameworks and our chapters, and, despite careful consideration some subjectivity was used to create the mappings. Please take that in consideration as you review them.

10.1 Skills Framework for the Information Age

The Skills Framework for the Information Age (SFIA) has defined nearly 100 skills. SFIA describes 7 levels of competency which can be applied to each skill. Not all skills, however, cover all seven levels. Some reach only partially up the seven step ladder. Others are based on mastering foundational skills, and start at the fourth or fifth level of competency. It is used in nearly 200 countries, from Britain to South Africa, South America, to the Pacific Rim, to the United States. (http://www.sfia-online.org)

Skill Skill Description Competency Levels
Quality management The application of techniques for monitoring and improvement of quality to any aspect of a function or process. The achievement of, and maintenance of compliance to, national and international standards, as appropriate, and to internal policies, including those relating to sustainability and security. 4-7
Quality assurance The process of ensuring that the agreed quality standards within an organisation are adhered to and that best practice is promulgated throughout the organisation. 3-6
Quality standards The development, maintenance, control and distribution of quality standards. 2-5
Testing description levels
Skill The planning, design, management, execution and reporting of tests, using appropriate testing tools and techniques and conforming to agreed process standards and industry specific regulations. The purpose of testing is to ensure that new and amended systems, configurations, packages, or services, together with any interfaces, perform as specified (including security requirements) , and that the risks associated with deployment are adequately understood and documented. Testing includes the process of engineering, using and maintaining testware (test cases, test scripts, test reports, test plans, etc) to measure and improve the quality of the software being tested. 1-6
Methods and tools Ensuring that appropriate methods and tools for the planning, development, testing, operation, management and maintenance of systems are adopted and used effectively throughout the organisation. 4-6
Business process testing The planning, design, management, execution and reporting of business process tests and usability evaluations. The application of evaluation skills to the assessment of the ergonomics, usability and fitness for purpose of defined processes. This includes the synthesis of test tasks to be performed (from statement of user needs and user interface specification), the design of an evaluation programme, the selection of user samples, the analysis of performance, and inputting results to the development team. 4-6
Systems integration The incremental and logical integration and testing of components and/or subsystems and their interfaces in order to create operational services. ??
Conformance review The independent assessment of the conformity of any activity, process, deliverable, product or service to the criteria of specified standards, best practice, or other documented requirements. May relate to, for example, asset management, network security tools, firewalls and internet security, sustainability, real-time systems, application design and specific certifications. 3-6
User experience evaluation Evaluation of systems, products or services, to assure that the stakeholder and organisational requirements have been met, required practice has been followed, and systems in use continue to meet organisational and user needs. Iterative assessment (from early prototypes to final live implementation) of effectiveness, efficiency, user satisfaction, health and safety, and accessibility to measure or improve the usability of new or existing processes, with the intention of achieving optimum levels of product or service usability. 2-6


10.2 European Competency Framework

The European Union’s European e-Competence Framework (e-CF) has 40 competences and is used by a large number of companies, qualification providers and others in public and private sectors across the EU. It uses five levels of competence proficiency (e-1 to e-5). No competence is subject to all five levels.

The e-CF is published and legally owned by CEN, the European Committee for Standardization, and its National Member Bodies (www.cen.eu). Its creation and maintenance has been co-financed and politically supported by the European Commission, in particular, DG (Directorate General) Enterprise and Industry, with contributions from the EU ICT multi-stakeholder community, to support competitiveness, innovation, and job creation in European industry. The Commission works on a number of initiatives to boost ICT skills in the workforce. Version 1.0 to 3.0 were published as CEN Workshop Agreements (CWA). The e-CF 3.0 CWA 16234-1 was published as an official European Norm (EN), EN 16234-1. For complete information, please see http://www.ecompetences.eu.

e-CF Dimension 2 e-CF Dimension 3
D.2. ICT Quality Strategy Development (Enable)
Defines, improves and refines a formal strategy to satisfy customer expectations and improve business performance (balance between cost and risks). Identifies critical processes influencing service delivery and product performance for definition in the ICT quality management system. Uses defined standards to formulate objectives for service management, product and process quality. Identifies ICT quality management accountability.
Level 4-5
E.5. Process Improvement (MANAGE)
Measures effectiveness of existing ICT processes. Researches and benchmarks ICT process design from a variety of sources. Follows a systematic methodology to evaluate, design and implement process or technology changes for measurable business benefit. Assesses potential adverse consequences of process change.
Level 3-4
E.6. ICT Quality Management (MANAGE)
Implements ICT quality policy to maintain and enhance service and product provision. Plans and defines indicators to manage quality with respect to ICT strategy. Reviews quality measures and recommends enhancements to influence continuous quality improvement.
Level 2-4

10.3 i Competency Dictionary

The Information Technology Promotion Agency (IPA) of Japan has developed the i Competency Dictionary (iCD), translated it into English, and describes it at https://www.ipa.go.jp/english/humandev/icd.html. It is an extensive skills and tasks database, used in Japan and southeast Asian countries. It establishes a taxonomy of tasks and the skills required to perform the tasks. The IPA is also responsible for the Information Technology Engineers Examination (ITEE), which has grown into one of the largest scale national examinations in Japan, with approximately 600,000 applicants each year.

The iCD consists of a Task Dictionary and a Skill Dictionary. Skills for a specific task are identified via a “Task x Skill” table. (Please see Appendix A for the task layer and skill layer structures.) EITBOK activities in each chapter require several tasks in the Task Dictionary.

The table below shows a sample task from iCD Task Dictionary Layer 2 (with Layer 1 in parentheses) that correspond to activities in this chapter. It also shows the Layer 2 (Skill Classification), Layer 3 (Skill Item), and Layer 4 (knowledge item from the IPA Body of Knowledge) prerequisite skills associated with the sample task, as identified by the Task x Skill Table of the iCD Skill Dictionary. The complete iCD Task Dictionary (Layer 1-4) and Skill Dictionary (Layer 1-4) can be obtained by returning the request form provided at http://www.ipa.go.jp/english/humandev/icd.html.

Task DictionarySkill Dictionary
Task Layer 1 (Task Layer 2)Skill ClassificationSkill ItemAssociated Knowledge Items
Quality management control
(Quality Management)
Quality management methods Quality assurance methods
  • Independent form of IV&V organization
  • IV&V (Independent V&V)
  • V&V plan
  • V&V (IEEE 610.12)
  • Stress test
  • Usability
  • Techniques
  • Verification (IEEE 610.12, 1012)
  • Verification (ISO 9000)
  • Acceptance/contract conformity
  • Performance
  • Validation (IEEE 610.12, 1012)
  • Validation (ISO 9000)
  • Standard specification
  • Quality management
  • Concept of quality assurance

(More)


11 Key Roles

The following roles are typical ITSM roles:

  • Availability Manager
  • Capacity Manager
  • Change Manager
  • Configuration Manager
  • Enterprise Architect
  • Information Security Manager
  • Problem Manager
  • Process Owner
  • Project Manager
  • Release Manager
  • Service Design Manager
  • Test and QA Manager

12 Standards

IEEE Std 730™-2014, IEEE Standard for Software Quality Assurance Processes

ISO 9000:2015, Quality management systems — Fundamentals and vocabulary

ISO 9001:2015, Quality management systems — Requirements

In addition, the SQuaRE series (ISO/IEC 250NN) includes over30 standards on Systems and software Quality Requirements and Evaluation (SQuaRE), such as:

ISO/IEC 25001:2014 Systems and software engineering -- Systems and software Quality Requirements and Evaluation (SQuaRE) -- Planning and management

ISO/IEC 25010:2011, Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – System and software quality models

ISO/IEC 25012:2008, Software engineering -- Software product Quality Requirements and Evaluation (SQuaRE) -- Data quality model

ISO/IEC 25030:2007, Software engineering — Software product Quality Requirements and Evaluation (SQuaRE) — Quality requirements


13 References

[1] For a detailed explanation of the quality management system (QMS), there is the ISO 9000 family of standards. ISO 9000:2005 Quality management systems — Fundamentals and vocabulary provides a good introduction, and ISO 9001:2008 Quality management systems — Requirements (approximately 30 pages) describes the requirements for a formal quality management system. If it is important for your organization to be certified as ISO 9000-compliant, you want to learn about those standards.

[2] SEVOCAB (http://pascal.computer.org/sev_display/index.action), which is formalized as ISO/IEC/IEEE 24765.

[3] What we do is the subject of quality management systems and their associated fields of quality control and quality assurance.

[4] Drucker, P. F. (1986). Innovation and Entrepreneurship: Practice and Principles. New York: Harper Row, p. 228.

[5] And knowing, of course, how complete is the “definition of done” itself.

[6] Cunningham first coined the term technical debt in 1992 as a software design metaphor that highlights the underlying costs associated with the compromise between the short term gain of getting software out the door and getting the release done on time versus the long term viability of the software system. http://www.ontechnicaldebt.com/blog/ward-cunningham-capers-jones- a-discussion-on-technical-debt/ (accessed 8/26/2014).

[7] http://www.castsoftware.com/research-labs/technical-debt-estimation (accessed 8/26/2014).

[8] For a good list of non-functional requirements, check ISO/IEC/IEEE Std. 29148.

[9] Completion of QA and QC items should be an essential component of the definition of done.

[10] Verification is the “process of providing objective evidence that the system, software, or hardware and its associated products conform to requirements (e.g., for correctness, completeness, consistency, and accuracy) for all life cycle activities during each life cycle process (acquisition, supply, development, operation, and maintenance), satisfy standards, practices, and conventions during life cycle processes, and successfully complete each life cycle activity and satisfy all the criteria for initiating succeeding life cycle activities” (IEEE 1012-2012 IEEE Standard for System and Software Verification and Validation).

[11] Validation is the “process of providing evidence that the system, software, or hardware and its associated products satisfy requirements allocated to it at the end of each life cycle activity, solve the right problem (e.g., correctly model physical laws, implement business rules, and use the proper system assumptions), and, and satisfy intended use and user needs” (IEEE 1012-2012 IEEE Standard for System and Software Verification and Validation.

[12] Robert B. Grady, Practical Software Metrics for Project Management and Process Improvement, Prentice Hall, 1992 (ISBN 0-13-72084-5).

[13] Although flexibility is not included in this standard, it is often requested by stakeholders.