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PRINCE2 Methodology Project Management Framework

PRINCE2 Methodology Project Management

The PRINCE2 Methodology is a project management framework that ensures project success through the engagement of all stakeholders. It ensures identification, analysis, and understanding of these stakeholders early in the project lifecycle. This ensures the project scope is focused on what stakeholders need and does not include elements that will harm stakeholders.

Seven principles

The PRINCE2 Methodology project management framework emphasizes the importance of communication between project management and team members. This includes assigning hard deadlines and deliverables to all project team members. It also encourages project reviews and adaptations. Stage boundaries help identify the project’s end goal and help define metrics and responsibilities.

The project manager must establish a viable business case for the project. This means clearly defining the project’s goal and the benefits it will bring to the company. The manager must also consider the return on investment of the project. This approach ensures business justification for the entire project lifecycle.

PRINCE2 principles are a great way to ensure project management is effective. They help project managers avoid common problems and provide structure to their projects. They are useful in any industry and for projects of any scope or size.

Seven themes

The PRINCE2 Methodology is a framework for project management. It has seven main themes that define the various aspects of the project. These themes are determined prior to the beginning of the project. They include defining the project’s purpose and its scope, developing a business case to justify the project, and developing project plans.

The first theme is quality. PRINCE2 defines quality as being fit for purpose and meeting requirements. It assumes that all work is done with a view to delivering value. This means that the project’s work must meet quality standards. The second theme is the role of the customer.

The last theme, Progress, deals with assessing the project’s progress and outcome. The project team must continually monitor the project’s performance to see if it’s meeting expectations. The project team must also assess if changes are necessary.

Seven processes

The PRINCE2 Methodology provides a structured approach for project management. Its seven processes provide guidelines on how to carry out a project. The processes serve as points of reference for all project stakeholders and guide them through any hurdles that may arise. The process begins with a project mandate, which defines the project purpose and outcome. It also defines the project team, project resources, and project risks. It involves detailed planning, and is often called the “Project Initiation Document”.

The project board is a group of high-level decision-makers. They typically consist of business executives, but may also include end-users. The project manager will assign roles to team members and delegate tasks to them. The project board will also evaluate the project and approve the deliverables.

The project mandate is a written or verbal instruction for the project. This may result from an existing organisational strategy or a perceived need to target new markets, improve existing business processes, or solve a problem. As long as the project has a clear goal and a clear purpose, PRINCE2 will help to ensure that it is successful. The end product is the key value that the project brings to its stakeholders.

Prioritisation of projects

Prioritisation of projects is a fundamental step in project management. A well-defined process can save time and effort. Project managers who follow best practice often develop skills in this area through formal training and on-the-job experience. They often have the knowledge and experience needed to identify the most important projects.

Prioritisation is a challenging task in a project-driven environment. This is particularly true when a project is large and complex. However, the process can be simplified by reducing the impact of scope creep. This process requires a clear definition of priorities and the engagement of stakeholders at early stages.

Many organizations are not able to prioritise projects effectively. In fact, a third of projects become obsolete before the half-way mark. The main reasons for this are a lack of alignment and prioritisation. When people are rushed or working under pressure, they can make mistakes.

Breakpoints

PRINCE2 Methodology is a project management methodology that emphasizes communication between project management and the project team. It also encourages regular progress monitoring. The methodology is “product-based”, meaning that the objectives of the project are defined by the business case. The business case should justify the project’s justification and commitment, and it should be regularly reviewed. The project’s end goal should be clearly defined so that the team knows when a project is complete and delivered.

Project managers and stakeholders are accountable for ensuring that projects deliverables meet requirements and specifications. These stakeholders include the customer, end-user, and supplier. The project manager manages the team and organizes the work to ensure the project’s delivery meets the agreed project objectives.

PRINCE2 emphasizes the use of the business case, the most important document in project management. The business case is reviewed throughout the project life cycle, ensuring that it is a viable undertaking. Another essential document is the project’s lesson log, which serves as the repository of lessons learned. The project manager uses the lesson log to ensure that the business case is still viable at the end of the project.

Communication with customers

The PRINCE2 Methodology project management process emphasizes communication between project management and the project team. It also emphasizes change management and the systematic collection of lessons learned. This process allows organizations to streamline the project management process and save time and money. This methodology also requires project managers to write a clear project mandate.

The PRINCE2 Methodology has three main parts: the principles, the themes, and the project charter. The principles are high-level commitments that should not be compromised; themes are specific areas that should be given more attention. These parts of the process are used to focus project team members on specific aspects of the project. They are also flexible and adaptable to the project.

The PRINCE2 Methodology is often used in government, construction, finance, and IT projects. This method is opposed to other PM methods that try to manage every aspect of the project. Other alternative methods include Scrum methodology and ITIL methodology.

Communication with stakeholders

Communication with stakeholders is critical to the PRINCE2 Methodology process. It helps to define roles and responsibilities within a project team. The processes help define who is responsible for a given task, what the end product is, and how to communicate with stakeholders. The project board and project manager play an important role in PRINCE2 project management. The project manager is responsible for defining the project’s stage boundaries.

The project’s success depends on ensuring that the stakeholders are properly involved. As a result, PRINCE2 project management ensures that stakeholders are identified, understood, and included at all stages of the project. The goal is to ensure that the project scope is appropriate to the needs of the stakeholders and avoids harmful or unnecessary elements.

During the project’s lifecycle, communication with stakeholders should take place on a regular basis. This can include the creation of reports, a regular update of progress, and an opportunity for stakeholders to provide feedback. The communication process should be facilitated by a trained facilitator, who can help the team build the plan and make it effective.

Design Methods

Design methods are procedures, techniques, aids, or tools for designing. They offer a number of different kinds of activities that a designer might use within an overall design process. Conventional procedures of design, such as drawing, can be regarded as design methods, but since the 1950s new procedures have been developed that are more usually grouped together under the name of “design methods”. What design methods have in common is that they “are attempts to make public the hitherto private thinking of designers; to externalise the design process”.

Design methodology is the broader study of method in design: the study of the principles, practices and procedures of designing.

Design methods originated in new approaches to problem solving developed in the mid-20th Century, and also in response to industrialisation and mass-production, which changed the nature of designing. A “Conference on Systematic and Intuitive Methods in Engineering, Industrial Design, Architecture and Communications”, held in London in 1962 is regarded as a key event marking the beginning of what became known within design studies as the “design methods movement”, leading to the founding of the Design Research Society and influencing design education and practice. Leading figures in this movement in the UK were J. Christopher Jones at the University of Manchester and L. Bruce Archer at the Royal College of Art.

The movement developed through further conferences on new design methods in the UK and USA in the 1960s. The first books on rational design methods, and on creative methods also appeared in this period.

New approaches to design were developing at the same time in Germany, notably at the Ulm School of Design (Hochschule fur Gestaltung-HfG Ulm) (1953-1968) under the leadership of Tomas Maldonado. Design teaching at Ulm integrated design with science (including social sciences) and introduced new fields of study such as cybernetics, systems theory and semiotics into design education. Bruce Archer also taught at Ulm, and another influential teacher was Horst Rittel. In 1963 Rittel moved to the School of Architecture at the University of California, Berkeley, where he helped found the Design Methods Group, a society focused on developing and promoting new methods especially in architecture and planning.

At the end of the 1960s two influential, but quite different works were published: Herbert A. Simon’s The Sciences of the Artificial and J. Christopher Jones’s Design Methods. Simon proposed the “science of design” as “a body of intellectually tough, analytic, partly formalizable, partly empirical, teachable doctrine about the design process”, whereas Jones catalogued a variety of approaches to design, both rational and creative, within a context of a broad, futures creating, systems view of design.

The 1970s saw some reaction against the rationality of design methods, notably from two of its pioneers, Christopher Alexander and J. Christopher Jones. Fundamental issues were also raised by Rittel, who characterised design and planning problems as wicked problems, un-amenable to the techniques of science and engineering, which deal with “tame” problems. The criticisms turned some in the movement away from rationalised approaches to design problem solving and towards “argumentative”, participatory processes in which designers worked in partnership with the problem stakeholders (clients, customers, users, the community). This led to participatory design, user centered design and the role of design thinking as a creative process in problem solving and innovation.

However, interest in systematic and rational design methods continued to develop strongly in engineering design during the 1980s; for example, through the Conference on Engineering Design series of The Design Society and the work of the Verein Deutscher Ingenieure association in Germany, and also in Japan, where the Japanese Society for the Science of Design had been established as early as 1954. Books on systematic engineering design methods were published in Germany and the UK. In the USA the American Society of Mechanical Engineers Design Engineering Division began a stream on design theory and methodology within its annual conferences. The interest in systematic, rational approaches to design has led to design science and design science (methodology) in engineering and computer science.

The development of design methods has been closely associated with prescriptions for a systematic process of designing. These process models usually comprise a number of phases or stages, beginning with a statement or recognition of a problem or a need for a new design and culminating in a finalised solution proposal. In his ‘Systematic Method for Designers’ L. Bruce Archer produced a very elaborate, 229 step model of a systematic design process for industrial design, but also a summary model consisting of three phases: Analytical phase (programming and data collection, analysis), Creative phase (synthesis, development), and Executive phase (communication). The UK’s Design Council models the creative design process in four phases: Discover (insight into the problem), Define (the area to focus upon), Develop (potential solutions), Deliver (solutions that work). A systematic model for engineering design by Pahl and Beitz has phases of Clarification of the task, Conceptual design, Embodiment design, and Detail design. A less prescriptive approach to designing a basic design process for oneself has been outlined by J. Christopher Jones.

In the engineering design process systematic models tend to be linear, in sequential steps, but acknowledging the necessity of iteration. In architectural design, process models tend to be cyclical and spiral, with iteration as essential to progression towards a final design. In industrial and product design, process models tend to comprise a sequence of stages of divergent and convergent thinking. The Dubberly Design Office has compiled examples of more than 80 design process models, but it is not an exhaustive list.

Within these process models there are numerous design methods that can be applied. In his book of ‘Design Methods’ J. C. Jones grouped 26 methods according to their purposes within a design process: Methods of exploring design situations (e.g. Stating Objectives, Investigating User Behaviour, Interviewing Users), Methods of searching for ideas (e.g. Brainstorming, Synectics, Morphological Charts), Methods of exploring problem structure (e.g. Interaction Matrix, Functional Innovation, Information Sorting), Methods of evaluation (e.g. Checklists, Ranking and Weighting).

Nigel Cross outlined eight stages in a process of engineering product design, each with an associated method: Identifying Opportunities – User Scenarios; Clarifying Objectives – Objectives Tree; Establishing Functions – Function Analysis; Setting Requirements – Performance Specification; Determining Characteristics – Quality Function Deployment; Generating Alternatives – Morphological Chart; Evaluating Alternatives – Weighted Objectives; Improving Details – Value Engineering.

Many design methods still currently in use originated in the design methods movement of the 1960s and 70s, adapted to modern design practices. Recent developments have seen the introduction of more qualitative techniques, including ethnographic methods such as cultural probes and situated methods.

The design methods movement had a profound influence on the development of academic interest in design and designing and the emergence of design research and design studies. Arising directly from the 1962 Conference on Design Methods, the Design Research Society (DRS) was founded in the UK in 1966. The purpose of the Society is to promote “the study of and research into the process of designing in all its many fields” and is an interdisciplinary group with many professions represented.

In the USA, a similar Design Methods Group (DMG) was also established in 1966 by Horst Rittel and others at the University of California, Berkeley. The DMG held a conference at MIT in 1968 with a focus on environmental design and planning, and that led to the foundation of the Environmental Design Research Association (EDRA), which held its first conference in 1969. A group interested in design methods and theory in architecture and engineering formed at MIT in the early 1980s, including Donald Schon, who was studying the working practices of architects, engineers and other professionals and developing his theory of reflective practice. In 1984 the National Science Foundation created a Design Theory and Methodology Program to promote methods and process research in engineering design.

Meanwhile in Europe, Vladimir Hubka established the Workshop Design-Konstruction (WDK),which led to a series of International Conferences on Engineering Design (ICED) beginning in 1981 and later became the Design Society.

Academic research journals in design also began publication. DRS initiated Design Studies in 1979, Design Issues appeared in 1984, and Research in Engineering Design in 1989.

Several pioneers of design methods developed their work in association with industry. The Ulm school established a significant partnership with the German consumer products company Braun through their designer Dieter Rams. J. Christopher Jones began his approach to systematic design as an ergonomist at the electrical engineering company AEI. L. Bruce Archer developed his systematic approach in projects for medical equipment for the UK National Health Service.

In the USA, designer Henry Dreyfuss had a profound impact on the practice of industrial design by developing systematic processes and promoting the use of anthropometrics, ergonomics and human factors in design, including through his 1955 book ‘Designing for People’. Another successful designer, Jay Doblin, was also influential on the theory and practice of design as a systematic process.

Much of current design practice has been influenced and guided by design methods. For example, the influential IDEO consultancy uses design methods extensively in its ‘Design Kit’ and ‘Method Cards’. Increasingly, the intersections of design methods with business and government through the application of design thinking have been championed by numerous consultancies within the design profession. Wide influence has also come through Christopher Alexander’s pattern language method, originally developed for architectural and urban design, which has been adopted in software design, interaction design, pedagogical design and other domains.

Design for Six Sigma

Design for Six Sigma (DFSS) is a business process management method related to traditional Six Sigma. It is used in many industries, like finance, marketing, basic engineering, process industries, waste management, and electronics. It is based on the use of statistical tools like linear regression and enables empirical research similar to that performed in other fields, such as social science. While the tools and order used in Six Sigma require a process to be in place and functioning, DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. DFSS is relevant for relatively simple items / systems. It is used for product or process design in contrast with process improvement. Measurement is the most important part of most Six Sigma or DFSS tools, but whereas in Six Sigma measurements are made from an existing process, DFSS focuses on gaining a deep insight into customer needs and using these to inform every design decision and trade-off.

There are different options for the implementation of DFSS. Unlike Six Sigma, which is commonly driven via DMAIC (Define – Measure – Analyze – Improve – Control) projects, DFSS has spawned a number of stepwise processes, all in the style of the DMAIC procedure.

DMADV, define – measure – analyze – design – verify, is sometimes synonymously referred to as DFSS, although alternatives such as IDOV (Identify, Design, Optimize, Verify) are also used. The traditional DMAIC Six Sigma process, as it is usually practiced, which is focused on evolutionary and continuous improvement manufacturing or service process development, usually occurs after initial system or product design and development have been largely completed. DMAIC Six Sigma as practiced is usually consumed with solving existing manufacturing or service process problems and removal of the defects and variation associated with defects. It is clear that manufacturing variations may impact product reliability. So, a clear link should exist between reliability engineering and Six Sigma (quality). In contrast, DFSS (or DMADV and IDOV) strives to generate a new process where none existed, or where an existing process is deemed to be inadequate and in need of replacement. DFSS aims to create a process with the end in mind of optimally building the efficiencies of Six Sigma methodology into the process before implementation; traditional Six Sigma seeks for continuous improvement after a process already exists.

DFSS seeks to avoid manufacturing/service process problems by using advanced techniques to avoid process problems at the outset (e.g., fire prevention). When combined, these methods obtain the proper needs of the customer, and derive engineering system parameter requirements that increase product and service effectiveness in the eyes of the customer and all other people. This yields products and services that provide great customer satisfaction and increased market share. These techniques also include tools and processes to predict, model and simulate the product delivery system (the processes/tools, personnel and organization, training, facilities, and logistics to produce the product/service). In this way, DFSS is closely related to operations research (solving the knapsack problem), workflow balancing. DFSS is largely a design activity requiring tools including: quality function deployment (QFD), axiomatic design, TRIZ, Design for X, design of experiments (DOE), Taguchi methods, tolerance design, robustification and Response Surface Methodology for a single or multiple response optimization. While these tools are sometimes used in the classic DMAIC Six Sigma process, they are uniquely used by DFSS to analyze new and unprecedented products and processes. It is a concurrent analyzes directed to manufacturing optimization related to the design.

Response surface methodology and other DFSS tools uses statistical (often empirical) models, and therefore practitioners need to be aware that even the best statistical model is an approximation to reality. In practice, both the models and the parameter values are unknown, and subject to uncertainty on top of ignorance. Of course, an estimated optimum point need not be optimum in reality, because of the errors of the estimates and of the inadequacies of the model.

Nonetheless, response surface methodology has an effective track-record of helping researchers improve products and services: For example, George Box’s original response-surface modeling enabled chemical engineers to improve a process that had been stuck at a saddle-point for years.

Proponents of DMAIC, DDICA (Design Develop Initialize Control and Allocate) and Lean techniques might claim that DFSS falls under the general rubric of Six Sigma or Lean Six Sigma (LSS). Both methodologies focus on meeting customer needs and business priorities as the starting-point for analysis.

It is often seen that[weasel words] the tools used for DFSS techniques vary widely from those used for DMAIC Six Sigma. In particular, DMAIC, DDICA practitioners often use new or existing mechanical drawings and manufacturing process instructions as the originating information to perform their analysis, while DFSS practitioners often use simulations and parametric system design/analysis tools to predict both cost and performance of candidate system architectures. While it can be claimed that[weasel words] two processes are similar, in practice the working medium differs enough so that DFSS requires different tool sets in order to perform its design tasks. DMAIC, IDOV and Six Sigma may still be used during depth-first plunges into the system architecture analysis and for “back end” Six Sigma processes; DFSS provides system design processes used in front-end complex system designs. Back-front systems also are used. This makes 3.4 defects per million design opportunities if done well.

Traditional six sigma methodology, DMAIC, has become a standard process optimization tool for the chemical process industries.
However, it has become clear that[weasel words] the promise of six sigma, specifically, 3.4 defects per million opportunities (DPMO), is simply unachievable after the fact. Consequently, there has been a growing movement to implement six sigma design usually called design for six sigma DFSS and DDICA tools. This methodology begins with defining customer needs and leads to the development of robust processes to deliver those needs.

Design for Six Sigma emerged from the Six Sigma and the Define-Measure-Analyze-Improve-Control (DMAIC) quality methodologies, which were originally developed by Motorola to systematically improve processes by eliminating defects. Unlike its traditional Six Sigma/DMAIC predecessors, which are usually focused on solving existing manufacturing issues (i.e., “fire fighting”), DFSS aims at avoiding manufacturing problems by taking a more proactive approach to problem solving and engaging the company efforts at an early stage to reduce problems that could occur (i.e., “fire prevention”). The primary goal of DFSS is to achieve a significant reduction in the number of nonconforming units and production variation. It starts from an understanding of the customer expectations, needs and Critical to Quality issues (CTQs) before a design can be completed. Typically in a DFSS program, only a small portion of the CTQs are reliability-related (CTR), and therefore, reliability does not get center stage attention in DFSS. DFSS rarely looks at the long-term (after manufacturing) issues that might arise in the product (e.g. complex fatigue issues or electrical wear-out, chemical issues, cascade effects of failures, system level interactions).

Arguments about what makes DFSS different from Six Sigma demonstrate the similarities between DFSS and other established engineering practices such as probabilistic design and design for quality. In general Six Sigma with its DMAIC roadmap focuses on improvement of an existing process or processes. DFSS focuses on the creation of new value with inputs from customers, suppliers and business needs. While traditional Six Sigma may also use those inputs, the focus is again on improvement and not design of some new product or system. It also shows the engineering background of DFSS. However, like other methods developed in engineering, there is no theoretical reason why DFSS cannot be used in areas outside of engineering.

Historically, although the first successful Design for Six Sigma projects in 1989 and 1991 predate establishment of the DMAIC process improvement process, Design for Six Sigma (DFSS) is accepted in part because Six Sigma organisations found that they could not optimise products past three or four Sigma without fundamentally redesigning the product, and because improving a process or product after launch is considered less efficient and effective than designing in quality. ‘Six Sigma’ levels of performance have to be ‘built-in’.

DFSS for software is essentially a non superficial modification of “classical DFSS” since the character and nature of software is different from other fields of engineering. The methodology describes the detailed process for successfully applying DFSS methods and tools throughout the software product design, covering the overall Software Development life cycle: requirements, architecture, design, implementation, integration, optimization, verification and validation (RADIOV). The methodology explains how to build predictive statistical models for software reliability and robustness and shows how simulation and analysis techniques can be combined with structural design and architecture methods to effectively produce software and information systems at Six Sigma levels.

DFSS in software acts as a glue to blend the classical modelling techniques of software engineering such as object-oriented design or Evolutionary Rapid Development with statistical, predictive models and simulation techniques. The methodology provides Software Engineers with practical tools for measuring and predicting the quality attributes of the software product and also enables them to include software in system reliability models.

Although many tools used in DFSS consulting such as response surface methodology, transfer function via linear and non linear modeling, axiomatic design, simulation have their origin in inferential statistics, statistical modeling may overlap with data analytics and mining,

However, despite that DFSS as a methodology has been successfully used as an end-to-end [technical project frameworks ] for analytic and mining projects, this has been observed by domain experts to be somewhat similar to the lines of CRISP-DM

DFSS is claimed to be better suited for encapsulating and effectively handling higher number of uncertainties including missing and uncertain data, both in terms of acuteness of definition and their absolute total numbers with respect to analytic s and data-mining tasks, six sigma approaches to data-mining are popularly known as DFSS over CRISP [ CRISP- DM referring to data-mining application framework methodology of SPSS ]

With DFSS data mining projects have been observed to have considerably shortened development life cycle . This is typically achieved by conducting data analysis to pre-designed template match tests via a techno-functional approach using multilevel quality function deployment on the data-set.

Practitioners claim that progressively complex KDD templates are created by multiple DOE runs on simulated complex multivariate data, then the templates along with logs are extensively documented via a decision tree based algorithm

DFSS uses Quality Function Deployment and SIPOC for feature engineering of known independent variables, thereby aiding in techno-functional computation of derived attributes

Once the predictive model has been computed, DFSS studies can also be used to provide stronger probabilistic estimations of predictive model rank in a real world scenario

DFSS framework has been successfully applied for predictive analytics pertaining to the HR analytics field, This application field has been considered to be traditionally very challenging due to the peculiar complexities of predicting human behavior.