DMADV is a structured methodology in Six Sigma used for developing high-quality processes or products. It consists of five phases: Define, Measure, Analyze, Design, and Verify. It aims to enhance quality, reduce defects, and ensure solutions meet customer needs through data-driven analysis and design.

DMADV (Define, Measure, Analyze, Design, Verify)DescriptionImplicationsExamplesApplications
DefineIn the “Define” phase of DMADV, the project’s goals, objectives, scope, and customer requirements are clearly defined. This stage sets the foundation for the entire process.– Establishes a clear understanding of project objectives and customer needs. – Defines project scope and boundaries. – Identifies stakeholders and their expectations.– Defining the scope and objectives of a new product development project. – Identifying customer requirements and expectations for a service improvement initiative.– New Product Development: Clearly define the goals, scope, and customer requirements before embarking on a product development project. – Process Improvement: Understand the scope of process improvement initiatives and customer expectations. – Project Management: Ensure alignment with project objectives and stakeholder needs from the beginning.
MeasureThe “Measure” phase focuses on gathering data and measuring current processes or performance related to the project. Data collection and analysis techniques are used to establish baseline metrics and understand the current state of affairs.– Provides a data-driven understanding of the current situation. – Identifies key performance indicators (KPIs) and baseline measurements. – Reveals areas that require improvement or redesign.– Conducting performance measurements to assess the efficiency of an existing process. – Collecting data on product quality to identify areas of improvement.– Process Analysis: Measure current process performance using data and metrics. – Quality Improvement: Collect and analyze data to identify defects or variations in product quality. – Performance Evaluation: Measure and assess the performance of systems, services, or operations.
AnalyzeDuring the “Analyze” phase, the collected data is analyzed to identify root causes, patterns, and factors influencing the current state. Various analytical methods and tools, such as root cause analysis, statistical analysis, and process mapping, are applied to gain insights into the issues and challenges.– Identifies the underlying causes of problems or inefficiencies. – Helps prioritize improvement areas based on data-driven insights. – Enables informed decision-making for the design phase.– Using statistical analysis to identify the primary causes of defects in a manufacturing process. – Conducting a process flow analysis to pinpoint bottlenecks and areas of delay.– Root Cause Analysis: Identify and address the root causes of issues to prevent recurrence. – Process Optimization: Analyze process data to optimize workflow and efficiency. – Quality Control: Investigate quality-related problems to improve product quality. – Decision Support: Use data analysis to make informed decisions about process redesign.
DesignThe “Design” phase involves developing and designing solutions or improvements based on the insights gained from the previous phases. This phase focuses on creating new processes, products, or services that address the identified issues and align with customer requirements. Detailed planning and design activities take place in this stage.– Develops solutions that align with customer requirements and address identified issues. – Involves the creation of detailed plans and designs for the proposed improvements. – Ensures that the new processes or products are well-defined and ready for implementation.– Designing a new production process based on the insights gained from the analysis phase. – Developing a redesigned service delivery model to enhance customer satisfaction.– Product Development: Create new products or redesign existing ones based on customer needs and data-driven insights. – Process Redesign: Develop improved processes that address identified inefficiencies or issues. – Service Innovation: Design new service models that enhance customer experiences. – Project Planning: Prepare detailed plans for implementing the proposed solutions.
VerifyIn the “Verify” phase, the designed solutions are tested, validated, and verified to ensure they meet the defined objectives and customer requirements. This phase involves pilot testing, validation against performance metrics, and verification that the improvements are effective and sustainable.– Validates that the designed solutions effectively address the identified issues. – Ensures that the improvements meet performance criteria and customer expectations. – Verifies the long-term sustainability and success of the changes.– Conducting pilot testing of a redesigned manufacturing process to assess its effectiveness. – Verifying that the new software system meets performance and functionality requirements.– Quality Assurance: Verify that the implemented improvements meet quality standards and performance criteria. – Sustainability Assessment: Assess the long-term viability and sustainability of process changes. – Validation Testing: Ensure that newly designed products or systems perform as intended. – Performance Evaluation: Confirm that the improvements meet or exceed performance expectations.

Introduction to DMADV

The DMADV methodology, also known as Design for Six Sigma (DFSS), is a data-driven and customer-focused approach for creating new processes, products, or services with a high level of quality and efficiency. It is a complementary approach to DMAIC (Define, Measure, Analyze, Improve, and Control), which is used for improving existing processes. DMADV is often applied in situations where significant changes or innovations are required, such as developing new products, redesigning processes, or launching new services.

The key phases of the DMADV methodology are as follows:

  1. Define: In this phase, the project team defines the goals and objectives of the project, identifies customer requirements, and establishes a clear project scope. It is crucial to have a well-defined problem statement and a deep understanding of customer needs.
  2. Measure: The Measure phase focuses on gathering data and quantifying the current state of the process or product. Data collection methods and measurement systems are established to assess the performance of the existing process or product.
  3. Analyze: During the Analyze phase, the team analyzes the collected data to identify factors that are critical to quality (CTQ) and potential sources of variation or defects. Statistical tools and techniques are used to gain insights into the process or product.
  4. Design: In the Design phase, the team uses the information gathered in the previous phases to develop and design a new process, product, or service. The design is based on meeting customer requirements and achieving the desired level of quality and performance.
  5. Verify: The Verify phase involves testing and validating the newly designed process, product, or service to ensure it meets the defined goals and customer requirements. This phase also includes pilot testing and implementation planning.

Principles of DMADV

The DMADV methodology is guided by several principles:

  1. Customer-Centric: DMADV places a strong emphasis on understanding and meeting customer needs and expectations. Customer requirements drive the design and development process.
  2. Data-Driven: Data and statistical analysis are central to DMADV. Decisions are based on objective data and evidence rather than assumptions or intuition.
  3. Structured Approach: DMADV follows a structured and systematic approach with well-defined phases and milestones. Each phase builds on the insights gained in the previous phases.
  4. Proactive Quality: DMADV aims to prevent defects and errors by designing quality into the process, product, or service from the outset. It is a proactive quality improvement approach.
  5. Cross-Functional Collaboration: Collaboration among cross-functional teams is essential in DMADV. Different expertise and perspectives contribute to better design and development outcomes.

Importance of DMADV

DMADV holds significant importance in various industries and contexts:

  1. Innovation: It is a valuable methodology for fostering innovation by enabling organizations to create new and improved processes, products, or services that meet emerging market demands.
  2. Customer Satisfaction: By focusing on understanding and meeting customer requirements, DMADV helps enhance customer satisfaction and loyalty.
  3. Quality Improvement: DMADV is instrumental in achieving and maintaining high levels of quality by preventing defects and errors during the design and development stages.
  4. Efficiency: It contributes to process and operational efficiency by designing processes that are optimized for performance and resource utilization.
  5. Risk Reduction: DMADV reduces the risk of launching products or services that do not meet customer expectations or encounter unforeseen issues.
  6. Competitive Advantage: Organizations that successfully apply DMADV can gain a competitive advantage by offering superior products or services in the market.

Benefits of DMADV

Utilizing the DMADV methodology offers numerous benefits to organizations:

  1. Higher Quality: DMADV helps organizations design processes, products, or services with a higher level of quality, resulting in fewer defects and errors.
  2. Customer-Centric: The focus on customer requirements ensures that the final product or service aligns closely with customer expectations.
  3. Cost Reduction: By designing processes that are efficient and optimized, DMADV can lead to cost savings in the long run.
  4. Innovation: It encourages innovation and creativity in designing new solutions that meet customer needs.
  5. Risk Mitigation: DMADV reduces the risk of failures or issues in newly developed processes, products, or services.
  6. Time Savings: A well-executed DMADV project can save time by avoiding rework and post-launch modifications.

Challenges in Implementing DMADV

While DMADV offers substantial benefits, it is not without its challenges:

  1. Resource Intensive: DMADV projects can be resource-intensive in terms of time, personnel, and data collection efforts.
  2. Data Availability: Availability and quality of data can pose challenges, particularly in situations where historical data may be limited.
  3. Complexity: The methodology can be complex, especially for organizations new to Six Sigma or data-driven approaches.
  4. Resistance to Change: Teams and stakeholders may resist changes or innovations proposed in the design phase.
  5. Scope Creep: Defining a clear and manageable scope in the Define phase is essential to avoid scope creep as the project progresses.

Real-World Applications of DMADV

The DMADV methodology finds application in various industries and sectors:

  1. Product Development: Organizations use DMADV to design new products or enhance existing ones, ensuring they meet customer requirements and quality standards.
  2. Service Design: Service industries employ DMADV to develop new services or improve existing ones, enhancing customer experiences.
  3. Process Redesign: Manufacturing and operational processes are redesigned to improve efficiency, reduce defects, and optimize resource utilization.
  4. Healthcare: Healthcare organizations use DMADV to design clinical processes, improve patient care, and enhance the overall healthcare experience.
  5. Software Development: DMADV is applied to the development of software applications to ensure they are user-friendly, reliable, and meet user requirements.
  6. Financial Services: Financial institutions use DMADV to design new financial products or optimize operational processes to minimize errors and improve customer service.

Practical Tips for Implementing DMADV

Here are some practical tips for organizations looking to implement the DMADV methodology effectively:

  1. Executive Support: Ensure that top leadership supports and champions DMADV initiatives, as they often require significant resources and commitment.
  2. Cross-Functional Teams: Assemble cross-functional teams with diverse expertise to contribute to the design and development process.
  3. Data Collection: Invest time and effort in robust data collection and analysis to inform decisions and validate designs.
  4. Pilot Testing: Conduct pilot tests or trials to validate the effectiveness of the new design before full implementation.
  5. Continuous Improvement: Apply the principles of continuous improvement to refine the design and address any issues that may arise post-implementation.
  6. Training and Education: Provide training and education to team members on the DMADV methodology and related tools and techniques.


The DMADV methodology, or Design for Six Sigma (DFSS), is a structured and data-driven approach to design and develop processes, products, or services that meet customer requirements and have minimal defects or errors. It offers a systematic and proactive approach to quality improvement and innovation. By following its defined phases and principles, organizations can create solutions that are customer-centric, efficient, and of high quality. While challenges may arise during implementation, the benefits of higher quality, cost savings, and customer satisfaction make DMADV a valuable methodology for organizations seeking to excel in today’s competitive landscape.

Key Highlights

  • Structured Process: DMADV is a structured methodology with five sequential phases: Define, Measure, Analyze, Design, and Verify.
  • Quality Enhancement: DMADV is focused on improving the quality of processes and products, ensuring they meet or exceed customer expectations.
  • Customer-Centric: The methodology emphasizes understanding and addressing customer needs and requirements throughout the project lifecycle.
  • Data-Driven Approach: DMADV relies on data analysis and measurements to make informed decisions and identify improvement opportunities.
  • Risk Reduction: By thoroughly analyzing and designing processes, DMADV helps reduce the risk of defects, failures, and costly errors.
  • Continuous Improvement: DMADV is aligned with the principles of continuous improvement and Six Sigma, aiming to achieve higher levels of performance and efficiency.
  • Resource Intensive: Implementing DMADV requires substantial resources, including time, manpower, and data collection tools.
  • Applicability: DMADV is particularly useful for creating new processes or products from scratch or significantly redesigning existing ones.
  • Validation and Testing: The Verify phase ensures that the new design meets the defined goals and specifications through validation and testing.
  • Integration with DMAIC: DMADV complements the DMAIC (Define, Measure, Analyze, Improve, Control) methodology in Six Sigma, with both approaches aiming for process excellence.
  • Strategic Impact: DMADV projects can have a strategic impact on organizations, leading to competitive advantages and improved customer satisfaction.

Connected Agile & Lean Frameworks


AIOps is the application of artificial intelligence to IT operations. It has become particularly useful for modern IT management in hybridized, distributed, and dynamic environments. AIOps has become a key operational component of modern digital-based organizations, built around software and algorithms.


AgileSHIFT is a framework that prepares individuals for transformational change by creating a culture of agility.

Agile Methodology

Agile started as a lightweight development method compared to heavyweight software development, which is the core paradigm of the previous decades of software development. By 2001 the Manifesto for Agile Software Development was born as a set of principles that defined the new paradigm for software development as a continuous iteration. This would also influence the way of doing business.

Agile Program Management

Agile Program Management is a means of managing, planning, and coordinating interrelated work in such a way that value delivery is emphasized for all key stakeholders. Agile Program Management (AgilePgM) is a disciplined yet flexible agile approach to managing transformational change within an organization.

Agile Project Management

Agile project management (APM) is a strategy that breaks large projects into smaller, more manageable tasks. In the APM methodology, each project is completed in small sections – often referred to as iterations. Each iteration is completed according to its project life cycle, beginning with the initial design and progressing to testing and then quality assurance.

Agile Modeling

Agile Modeling (AM) is a methodology for modeling and documenting software-based systems. Agile Modeling is critical to the rapid and continuous delivery of software. It is a collection of values, principles, and practices that guide effective, lightweight software modeling.

Agile Business Analysis

Agile Business Analysis (AgileBA) is certification in the form of guidance and training for business analysts seeking to work in agile environments. To support this shift, AgileBA also helps the business analyst relate Agile projects to a wider organizational mission or strategy. To ensure that analysts have the necessary skills and expertise, AgileBA certification was developed.

Agile Leadership

Agile leadership is the embodiment of agile manifesto principles by a manager or management team. Agile leadership impacts two important levels of a business. The structural level defines the roles, responsibilities, and key performance indicators. The behavioral level describes the actions leaders exhibit to others based on agile principles. 

Andon System

The andon system alerts managerial, maintenance, or other staff of a production process problem. The alert itself can be activated manually with a button or pull cord, but it can also be activated automatically by production equipment. Most Andon boards utilize three colored lights similar to a traffic signal: green (no errors), yellow or amber (problem identified, or quality check needed), and red (production stopped due to unidentified issue).

Bimodal Portfolio Management

Bimodal Portfolio Management (BimodalPfM) helps an organization manage both agile and traditional portfolios concurrently. Bimodal Portfolio Management – sometimes referred to as bimodal development – was coined by research and advisory company Gartner. The firm argued that many agile organizations still needed to run some aspects of their operations using traditional delivery models.

Business Innovation Matrix

Business innovation is about creating new opportunities for an organization to reinvent its core offerings, revenue streams, and enhance the value proposition for existing or new customers, thus renewing its whole business model. Business innovation springs by understanding the structure of the market, thus adapting or anticipating those changes.

Business Model Innovation

Business model innovation is about increasing the success of an organization with existing products and technologies by crafting a compelling value proposition able to propel a new business model to scale up customers and create a lasting competitive advantage. And it all starts by mastering the key customers.

Constructive Disruption

A consumer brand company like Procter & Gamble (P&G) defines “Constructive Disruption” as: a willingness to change, adapt, and create new trends and technologies that will shape our industry for the future. According to P&G, it moves around four pillars: lean innovation, brand building, supply chain, and digitalization & data analytics.

Continuous Innovation

That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problem and not the technical solution of its founders.

Design Sprint

A design sprint is a proven five-day process where critical business questions are answered through speedy design and prototyping, focusing on the end-user. A design sprint starts with a weekly challenge that should finish with a prototype, test at the end, and therefore a lesson learned to be iterated.

Design Thinking

Tim Brown, Executive Chair of IDEO, defined design thinking as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Therefore, desirability, feasibility, and viability are balanced to solve critical problems.


DevOps refers to a series of practices performed to perform automated software development processes. It is a conjugation of the term “development” and “operations” to emphasize how functions integrate across IT teams. DevOps strategies promote seamless building, testing, and deployment of products. It aims to bridge a gap between development and operations teams to streamline the development altogether.

Dual Track Agile

Product discovery is a critical part of agile methodologies, as its aim is to ensure that products customers love are built. Product discovery involves learning through a raft of methods, including design thinking, lean start-up, and A/B testing to name a few. Dual Track Agile is an agile methodology containing two separate tracks: the “discovery” track and the “delivery” track.

eXtreme Programming

eXtreme Programming was developed in the late 1990s by Ken Beck, Ron Jeffries, and Ward Cunningham. During this time, the trio was working on the Chrysler Comprehensive Compensation System (C3) to help manage the company payroll system. eXtreme Programming (XP) is a software development methodology. It is designed to improve software quality and the ability of software to adapt to changing customer needs.

Feature-Driven Development

Feature-Driven Development is a pragmatic software process that is client and architecture-centric. Feature-Driven Development (FDD) is an agile software development model that organizes workflow according to which features need to be developed next.

Gemba Walk

A Gemba Walk is a fundamental component of lean management. It describes the personal observation of work to learn more about it. Gemba is a Japanese word that loosely translates as “the real place”, or in business, “the place where value is created”. The Gemba Walk as a concept was created by Taiichi Ohno, the father of the Toyota Production System of lean manufacturing. Ohno wanted to encourage management executives to leave their offices and see where the real work happened. This, he hoped, would build relationships between employees with vastly different skillsets and build trust.

GIST Planning

GIST Planning is a relatively easy and lightweight agile approach to product planning that favors autonomous working. GIST Planning is a lean and agile methodology that was created by former Google product manager Itamar Gilad. GIST Planning seeks to address this situation by creating lightweight plans that are responsive and adaptable to change. GIST Planning also improves team velocity, autonomy, and alignment by reducing the pervasive influence of management. It consists of four blocks: goals, ideas, step-projects, and tasks.

ICE Scoring

The ICE Scoring Model is an agile methodology that prioritizes features using data according to three components: impact, confidence, and ease of implementation. The ICE Scoring Model was initially created by author and growth expert Sean Ellis to help companies expand. Today, the model is broadly used to prioritize projects, features, initiatives, and rollouts. It is ideally suited for early-stage product development where there is a continuous flow of ideas and momentum must be maintained.

Innovation Funnel

An innovation funnel is a tool or process ensuring only the best ideas are executed. In a metaphorical sense, the funnel screens innovative ideas for viability so that only the best products, processes, or business models are launched to the market. An innovation funnel provides a framework for the screening and testing of innovative ideas for viability.

Innovation Matrix

According to how well defined is the problem and how well defined the domain, we have four main types of innovations: basic research (problem and domain or not well defined); breakthrough innovation (domain is not well defined, the problem is well defined); sustaining innovation (both problem and domain are well defined); and disruptive innovation (domain is well defined, the problem is not well defined).

Innovation Theory

The innovation loop is a methodology/framework derived from the Bell Labs, which produced innovation at scale throughout the 20th century. They learned how to leverage a hybrid innovation management model based on science, invention, engineering, and manufacturing at scale. By leveraging individual genius, creativity, and small/large groups.

Lean vs. Agile

The Agile methodology has been primarily thought of for software development (and other business disciplines have also adopted it). Lean thinking is a process improvement technique where teams prioritize the value streams to improve it continuously. Both methodologies look at the customer as the key driver to improvement and waste reduction. Both methodologies look at improvement as something continuous.

Lean Startup

A startup company is a high-tech business that tries to build a scalable business model in tech-driven industries. A startup company usually follows a lean methodology, where continuous innovation, driven by built-in viral loops is the rule. Thus, driving growth and building network effects as a consequence of this strategy.

Minimum Viable Product

As pointed out by Eric Ries, a minimum viable product is that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort through a cycle of build, measure, learn; that is the foundation of the lean startup methodology.

Leaner MVP

A leaner MVP is the evolution of the MPV approach. Where the market risk is validated before anything else


Kanban is a lean manufacturing framework first developed by Toyota in the late 1940s. The Kanban framework is a means of visualizing work as it moves through identifying potential bottlenecks. It does that through a process called just-in-time (JIT) manufacturing to optimize engineering processes, speed up manufacturing products, and improve the go-to-market strategy.


Jidoka was first used in 1896 by Sakichi Toyoda, who invented a textile loom that would stop automatically when it encountered a defective thread. Jidoka is a Japanese term used in lean manufacturing. The term describes a scenario where machines cease operating without human intervention when a problem or defect is discovered.

PDCA Cycle

The PDCA (Plan-Do-Check-Act) cycle was first proposed by American physicist and engineer Walter A. Shewhart in the 1920s. The PDCA cycle is a continuous process and product improvement method and an essential component of the lean manufacturing philosophy.

Rational Unified Process

Rational unified process (RUP) is an agile software development methodology that breaks the project life cycle down into four distinct phases.

Rapid Application Development

RAD was first introduced by author and consultant James Martin in 1991. Martin recognized and then took advantage of the endless malleability of software in designing development models. Rapid Application Development (RAD) is a methodology focusing on delivering rapidly through continuous feedback and frequent iterations.

Retrospective Analysis

Retrospective analyses are held after a project to determine what worked well and what did not. They are also conducted at the end of an iteration in Agile project management. Agile practitioners call these meetings retrospectives or retros. They are an effective way to check the pulse of a project team, reflect on the work performed to date, and reach a consensus on how to tackle the next sprint cycle. These are the five stages of a retrospective analysis for effective Agile project management: set the stage, gather the data, generate insights, decide on the next steps, and close the retrospective.

Scaled Agile

Scaled Agile Lean Development (ScALeD) helps businesses discover a balanced approach to agile transition and scaling questions. The ScALed approach helps businesses successfully respond to change. Inspired by a combination of lean and agile values, ScALed is practitioner-based and can be completed through various agile frameworks and practices.


The SMED (single minute exchange of die) method is a lean production framework to reduce waste and increase production efficiency. The SMED method is a framework for reducing the time associated with completing an equipment changeover.

Spotify Model

The Spotify Model is an autonomous approach to scaling agile, focusing on culture communication, accountability, and quality. The Spotify model was first recognized in 2012 after Henrik Kniberg, and Anders Ivarsson released a white paper detailing how streaming company Spotify approached agility. Therefore, the Spotify model represents an evolution of agile.

Test-Driven Development

As the name suggests, TDD is a test-driven technique for delivering high-quality software rapidly and sustainably. It is an iterative approach based on the idea that a failing test should be written before any code for a feature or function is written. Test-Driven Development (TDD) is an approach to software development that relies on very short development cycles.


Timeboxing is a simple yet powerful time-management technique for improving productivity. Timeboxing describes the process of proactively scheduling a block of time to spend on a task in the future. It was first described by author James Martin in a book about agile software development.


Scrum is a methodology co-created by Ken Schwaber and Jeff Sutherland for effective team collaboration on complex products. Scrum was primarily thought for software development projects to deliver new software capability every 2-4 weeks. It is a sub-group of agile also used in project management to improve startups’ productivity.


Scrumban is a project management framework that is a hybrid of two popular agile methodologies: Scrum and Kanban. Scrumban is a popular approach to helping businesses focus on the right strategic tasks while simultaneously strengthening their processes.

Scrum Anti-Patterns

Scrum anti-patterns describe any attractive, easy-to-implement solution that ultimately makes a problem worse. Therefore, these are the practice not to follow to prevent issues from emerging. Some classic examples of scrum anti-patterns comprise absent product owners, pre-assigned tickets (making individuals work in isolation), and discounting retrospectives (where review meetings are not useful to really make improvements).

Scrum At Scale

Scrum at Scale (Scrum@Scale) is a framework that Scrum teams use to address complex problems and deliver high-value products. Scrum at Scale was created through a joint venture between the Scrum Alliance and Scrum Inc. The joint venture was overseen by Jeff Sutherland, a co-creator of Scrum and one of the principal authors of the Agile Manifesto.

Six Sigma

Six Sigma is a data-driven approach and methodology for eliminating errors or defects in a product, service, or process. Six Sigma was developed by Motorola as a management approach based on quality fundamentals in the early 1980s. A decade later, it was popularized by General Electric who estimated that the methodology saved them $12 billion in the first five years of operation.

Stretch Objectives

Stretch objectives describe any task an agile team plans to complete without expressly committing to do so. Teams incorporate stretch objectives during a Sprint or Program Increment (PI) as part of Scaled Agile. They are used when the agile team is unsure of its capacity to attain an objective. Therefore, stretch objectives are instead outcomes that, while extremely desirable, are not the difference between the success or failure of each sprint.

Toyota Production System

The Toyota Production System (TPS) is an early form of lean manufacturing created by auto-manufacturer Toyota. Created by the Toyota Motor Corporation in the 1940s and 50s, the Toyota Production System seeks to manufacture vehicles ordered by customers most quickly and efficiently possible.

Total Quality Management

The Total Quality Management (TQM) framework is a technique based on the premise that employees continuously work on their ability to provide value to customers. Importantly, the word “total” means that all employees are involved in the process – regardless of whether they work in development, production, or fulfillment.


The waterfall model was first described by Herbert D. Benington in 1956 during a presentation about the software used in radar imaging during the Cold War. Since there were no knowledge-based, creative software development strategies at the time, the waterfall method became standard practice. The waterfall model is a linear and sequential project management framework. 

Read Also: Continuous InnovationAgile MethodologyLean StartupBusiness Model InnovationProject Management.

Read Next: Agile Methodology, Lean Methodology, Agile Project Management, Scrum, Kanban, Six Sigma.

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